Four-State Dairy Nutritionand Management Conference

June 9 & 10, 2010 • Dubuque, Iowa

Cooperative Extension for:Iowa State UniversityUniversity of IllinoisUniversity of MinnesotaUniversity of Wisconsin

Table of Contents

Sponsors and Speakers

Getting Cows Pregnant and Keeping Them Pregnantin Coordination with Practical Omega Nutrition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Economic Returns of Improved Reproductive Performance in Dairy Cattle. . . . . . . . . . . . . . . 9

Where Do All These Fatty Acids Come From And What Do They Do To My Cow?. . . . . . . . . 15

The Compatibility between Diary Productivity and Carbon Footprint . . . . . . . . . . . . . . . . . . . 21

Feeding Economics For 2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

4-State Dairy Nutrition & Management Conference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Coordination of Reproductive and Nutritional Management of Lactating Dairy Cows . . . . 32

Demystifying the Environmental Sustainability of Food Production. . . . . . . . . . . . . . . . . . . . . . 38

The Use of Records to Evaluate and Improve Transition Cow Performance . . . . . . . . . . . . . . 43

Comparison of Immune Function, Uterine Health and More in Holstein and Crossbred Transition Cows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Manureology 101 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Troubleshooting Silage Yeast, Mold and VFA Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

Improving Feeding Consistency Through TMR Audits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

The Chemistry of High Moisture Corn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

Improving Starch Digestibility in Dairy Cows: Opportunities with Reduced-Starch Diets . . . . 90

FARM Dairy Well-Being Program. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94

Dairy calf liquid feeding strategies to cope with new antibiotic use regulations . . . . . . . . . . 96

Improving the Value of Cull Cows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

The Wisconsin Dairy Feed Cost Evaluator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

Improving Reproductive Efficiency using Double Ovsynch . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

Food Economics and Consumer Choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119

Sponsors and SpeakersThe program committee deeply appreciates the following for their support and commitment tostrengthening the Midwest dairy industry.

Platinum Co-Sponsors

Elanco Animal Health

Virtus Nutrition

Gold Co-Sponsors

Analab

Dairyland Laboratories

Diamond V Mills

Kemin Industries

Nutriad, Inc.

Pioneer, A DuPont Business

Quali Tech, Inc.

Vi-COR

Silver Co-Sponsors

Adisseo

Ag Processing, Inc./Amino Plus

AgSource Cooperative Services

Alltech, Inc.

AMTS

Arm & Hammer Animal Nutrition

Balchem Corporation

BASF Plant Science

BIOMIN USA

Biozyme Incorporated

Byron Seeds, LLC

Central Life Sciences

Citura

Cumberland Valley AnalyticalServices

Digi-Star LLC

Galdwin A Read Co.

Milk Specialties Global AnimalHealth

MIN-AD Inc.

Mycogen Seeds

Novus International, Inc.

Papillon Agricultural Company

Prince Agri Products, Inc.

Quality Roasting Inc.

Rock River Laboratory Inc.

SoyBest

SoyPLUS/Soy Chlor

Supervisor Systems

Trouw Nutrition USA

Zeeland Farm Services, Inc.

Zinpro Corp.

Bronze Co-Sponsors

Agri-Nutrition Consulting Inc.

Calf-Tel By Hampel

CHR Hansen

Lallemand Specialties

Speakers:Bill Thatcher

University of FloridaMike Overton

University of GeorgiaTom Jenkins

Clemson UniversityJude Capper

Washington StateMike Hutjens

University of IllinoisJim Barmore

GPS Dairy ConsultingEd Kreykes

Dairy Health ServicesDoug Scheider

Scheidairy Farms Inc.Gary Sipiorski

Vita Plus Corp.Ricardo Chebel

University of Minnesota

Bill MahannaPioneer

Rob AukermanElanco Animal Health

Tom OelbergDiamond V Mills

Pat HoffmanUniversity of Wisconsin

Randy ShaverUniversity of Wisconsin

Marcia EndresUniversity of Minnesota

Noah LitherlandUniversity of Minnesota

Dick WallaceUniversity of Illinois

Victor CabreraUniversity of Wisconsin Extension

Milo WiltbankUniversity of Wisconsin

IntroductionIntensive genetic selection for milk productionwithout attention to reproductive performance hascontributed to an inverse relationship between milkproduction and reproduction (Lucy, 2001). Inclusionof Productive Life, Daughter Pregnancy Rate, andmore recently the availability of Sire Conception Rate,as a measurement of phenotypic service-sire fertility,appear to have reduced the rate of decline in fertilityin the USA (Norman et al., 2007). Reproductivemanagement of the lactating dairy cow has been achallenge because of poor expression of estrus andlow fertility to insemination at a detected estrus. Theduration of estrus is reduced as milk productionincreases, and the frequency of double ovulations andsubsequent occurrence of twins also is increased incows with high levels of milk production at the timeof the breeding period (Lopez et al., 2005) The highproducing dairy cow of today expresses estrus forapproximately 7 hours during which time an averageof 6.5 standing events takes place with anaccumulative period of standing of 20 seconds (i.e., 3seconds per standing event; Lopez et al., 2004).

Pregnancy rate over a 21 day period for the nationalherd of dairy cows in the United States isapproximately 16.2%. The component parts ofpregnancy rate are the rate of estrus detection andconception rate. Technology is available for systemsto detect estrus accurately, but a major issue is thatlactating dairy cows don’t display strong symptomsof estrus. Expression of estrus has been affectedadversely by high milk production and associatedmetabolism of hormones, as well as housing facilities(e.g., concrete floors) that reduce the cow’swillingness to be sexually active. An additionalchallenge is the high occurrence of non-ovulatorydairy cows that either have re-occurring folliclewaves without ovulation or development of ovariancysts.

A major advance in reproductive management thathas addressed how to improve pregnancy rate hasbeen development of timed artificial insemination(TAI) programs based on development of systems tocontrol or program optimal development of ovarianfollicles, induce ovulation, and develop a corpus

luteum (CL) capable of supporting pregnancy (Mooreand Thatcher 2006). The component pharmaceuticalagents available to the dairy industry in manycountries for use with dairy cattle are GnRH,luteolytic prostaglandins, and intravaginalprogesterone (using a controlled internal drug-releasing insert, CIDR, or similar device). These arepharmaceuticals that mimic the actions of the cow’sendogenous hormones, are physiological, and poseno health hazard to the cow. The original TAIprotocol is the Ovsynch procedure (Pursley et al.,1997a). This protocol has been in use forapproximately 12 years. During this period, bothbasic and applied research has lead to majoradvancements in optimizing the system. As aconsequence, pregnancy responses have increased,the system has been extended to resynchronization ofnonpregnant cows, and programs have beendeveloped for TAI in dairy heifers. The dynamics ofvarious cow factors such as body condition score,parity, and health status in the transitional-periparturient period have been shown to influencepregnancy rates to the controlled breeding program.The present objective is to update majoradvancements in ìgetting cows pregnant and keepingthem pregnantî and coordination of reproductivemanagement with practical omega nutrition.

Lactating Dairy CattleIt is essential that nutritionists, producers andveterinarians understand the physiologicalunderlying reasons why certain components of thereproductive management program are able toimprove reproductive performance or converselywhy a misunderstanding of the program can lead tocatastrophic pregnancy results. No one reproductivebreeding program is practical and economicallyoptimal for all dairy production units due todifferences in available facilities, size of the unit,labor that places reproduction as a high priority, anda functionally dynamic record system.

Optimizing stage of the estrous cycle at onset ofOvsynchThe original Ovsynch program involved twoinjections of GnRH administered 7 days before and

Getting Cows Pregnant and Keeping ThemPregnant in Coordination with Practical

Omega NutritionW.W. Thatcher, C.R. Staples and J.E.P. Santos

Department of Animal Sciences, University of FloridaThatcher@ufl.edu

1

48 hours after an injection of PGF2a, and cows areinseminated 16–20 h after the second injection ofGnRH (Pursley et al., 1997a). If TAI in the OvSynchprotocol is performed at the same time as the secondGnRH injection than the protocol is referred to as Co-

Synch.Optimization of stage of the estrous cycle (i.e.,days 5 to 9) at the onset of the Ovsynch protocol isimportant to achieve a subsequent synchronizedovulation at the second GnRH preceding the TAI(Figure 1). Programming the stage of the estrous cycleat the time the Ovsynch protocol is implemented(e.g., Days 5-9 of estrous cycle) insures there isprogesterone availability throughout the periodbetween the first injection of GnRH and injection ofPGF2a·, and that there is a CL to respond to theluteolytic injection of PGF2a· (Figure 1). The continualexposure to progesterone is important forsequentially programming the brain, oviduct anduterus with the appropriate changes in hormones,receptors and secretions leading to an inducedovulation, fertilization and development of anembryo capable of maintaining a pregnancy withminimal embryonic and fetal losses. Programmingthe start of the Ovsynch protocol to occur betweenDays 5 to 9 of the estrous cycle increases theprobability that the first injection of GnRH willinduce ovulation of the first wave follicle andrecruitment of a new follicle wave (Figure 1), whichupon induction of ovulation to the second GnRHincreases the probability of producing a viable oocytefor fertilization and a robust CL. Indeed ovulation ofthe first follicle wave results in presence of both theoriginal CL and an accessory CL, induced by theGnRH injection, which are responsive to the injectionof PGF2a.

The Ovsynch protocol preceded by a PGF2a·presynchronization program (Presync-Ovsynch) hasbecome the nucleus program for reproductivemanagement in the industry (Moreira et al., 2001; El-Zarkouny et al., 2004). Successful use of such aprogram is dependent highly upon obtaining goodcompliance in implementing all component parts of

the protocol. The original Presynch-Ovsynch programentailed two injections of PGF2a· given 14 days apartwith the Ovsynch protocol initiated 12 days after thesecond injection of PGF2a· for presynchronization(Figure 2). This system increased pregnancy ratescompared to Ovsynch alone for the reasons outlinedabove, when the Ovsynch protocol is initiated inearly diestrus (Table 1). Dairy producers were keento extend the period when Ovsynch was initiated to a14 day interval such that four of the five sequentialhormonal injections would be given on the same dayof week. Field experiences indicate that 60% ofdetected estruses occur on days 3-6 after the secondinjection of PGF2a· of presynchronization. A recentstudy indicated that an 11 day interval afterpresynchronization (i.e., cows would bepredominately 5-8 days of the estrous cycle) is betterthan a 14 day interval to begin the TAI protocol(Galv„o et al., 2007). The overall ovulation rate to thefirst injection of GnRH was greater for an 11 day thana 14 day interval (62% > 44.7%). This was attributedto GnRH being given at 11 days when the first wavefollicle will ovulate whereas the 14 day intervalincreased the proportion of cows injected early in thesecond follicle wave at a time the follicle wasdeveloped insufficiently to ovulate in response toGnRH. The latter follicle would continue to developand be slightly more aged and/or dominantcompared to the newly recruited follicle from the day11 injection interval for GnRH. Indeed Pregnancy perTAI was 6.6% greater for the 11 day interval (40.1% >33.5% at day 38 after TAI; Table 1). Thus subtlechanges in presynchronization protocols can causesubstantial increases in pregnancy rate and theoptimal period to start the Ovsynch protocol is 10 to12 days after the second PGF2a· injection ofpresynchronization (Figure 2).

2

Table 1. Pregnancy rates for lactating dairy cowsreceiving various reproductive management systemsfor timed insemination

Interval from PGF2a· to ovulatory injection of GnRHand timing of AIIt has been well documented that cows should be

inseminated 8 to 16 hours after the onset of estrus foran optimal conception rate (Pursley et al., 1997a). Thepreovulatory surge of LH occurs very close to theonset of estrus with ovulation occurringapproximately 28 h after the LH surge. It isimportant to recognize that the second injection ofGnRH of an Ovsynch program is analogous to theonset of estrus since an LH surge is inducedimmediately. Indeed maximal rate of pregnancies perAI was achieved when a timed insemination wasmade at 16 h after the injection of GnRH. In contrastpercent pregnant to AI was decreased wheninseminations were made at the time of GnRHinjection or 28 h later. Producers often favor theconvenience of carrying out a TAI at the time ofGnRH injection (i.e., referred to as a Co-synchprogram) to reduce the number of times cows need tobe held up. Alternatively, some producers prefer toperform TAI on the following day at approximately24-28 h after the GnRH injection for convenience.Either option likely will reduce percent pregnant toAI. The importance of the correct timing is indicatedby a study completed at the University of Wisconsin(Brusveen et al., 2008). All cows werepresynchronized with two injections of PGF2a·, andthe Ovsynch protocol was started 11 days later. Theoptimal timing program was to inject GnRH 56 hafter injection of PGF2a· and inseminate the cows 16 hafter GnRH, which was 72 h after the injection ofPGF2a· (e.g., Figure 2). Percent pregnant to AI was36.1% compared to a Co-synch 48h (26.7%) or 72 h(27.3%) programs. The latter two programs injectedGnRH and TAI concurrently at 48 h or 72 h,respectively. Clearly, subtle changes in timing of theGnRH injection and time of insemination result insubstantial differences in percent pregnant to AIresponses. If a Co-synch program is to be followed,one needs to understand the physiology of theinjection sequence so that functionally active ovarian

follicles are at an optimal stage analogous to a folliclein the close periestrus period when GnRH/TAI isperformed.

Application of a Presynchronization/ 5-Day Co-Synch Program in Lactating Dairy CowsHigh-producing lactating dairy cows have a greaterincidence of two waves of follicle growth during theestrous cycle compared with growing heifers that aremore likely to have three follicular waves (Savio etal.,1988). The interval from follicle emergence toestrus is ~3.5 days greater for cows with twofollicular waves than for those with three follicularwaves (Bleach et al., 2004). In a comparison ofOvsynch programs initiated at day 3 or 6 of theestrous cycle, Cerri et al. (2009) reported thatovulatory follicles with shorter length of dominance(5 to 6 days) yielded a greater proportion of grades 1and 2 embryos, whereas cows with a longer period ofdominance had increased proportion of poor qualityand degenerated embryos. Fertilization rate remainedunaffected by the period of dominance.

One means of reducing the period of ovulatoryfollicle dominance is to shorten the interval fromfollicle recruitment to luteal regression (i.e.,implement a 5 day interval between GnRH andPGF2a· injection) to possibly increase pregnancy perTAI in lactating dairy cows. Following two injectionsof PGF2a· at 36 and 50 d in milk, Santos et al. (2010)randomly assigned 933 cows to a Cosynch 72 hprotocol (CoS72: d 61 GnRH, d 68 PGF2a, d 71 GnRH)or to a 5d-Cosynch 72 h with two injections of PGF2a

(5dCoS2: d 61 GnRH, d 66 and 67 PGF2a, d 69 GnRH).Blood was sampled for progesterone analyses at thefirst GnRH, first PGF2a, second GnRH and 7 day aftertimed AI. Regression of CL was lesser (91.5 vs. 96.3%)and P/AI was greater (39.3 vs. 33.9%) for 5dCoS2than CoS72, respectively. It was essential to inject twodoses of PGF2a given 24 h apart (i.e., d 66 and 67) toinsure complete regression of the CL, whereas indairy heifers described above CL regression wascompleted with one injection of PGF2a.

Following two injections of PGF2a at 46 and 60 days inmilk, Bisinotto R. and Santos J.E.P (Unpublishedobservations, 2010) randomly assigned 1227 lactatingdairy cows to a 5-day OVS56h or to a 5-dayCosynch72h as depicted in Figure 3.Pregnancy/TAI did not differ between groups whenevaluated at either d32 or d 60 after TAI (Table 2).Indeed, overall mean Pregnancy/TAI of 45.9%(n=1227) at d32 is excellent with overall pregnancyloss estimated d 60 to be 13.1% (n=557). Thus, the 5-dayCosynch 72 h program with two injections ofPGF2a· is very efficient in getting cows pregnant.

3

Re-synchronization of nonpregnant cows followingfirst serviceA reproductive management challenge followingfirst service is to re-inseminate cows that did notconceive as quickly as possible (Bartolome et al.,2005). The same principles to optimize the Presynch-Ovsynch program are applicable to development of aresynchronization program. However, aresynchronization system is somewhat constrained inthat programming nonpregnant cows to ovulate mustbe done in a manner that will not interfere with cowsthat are pregnant to first service. Thus, accurateidentification of non-pregnant and pregnant cows isimportant, and timing of the diagnosis is dependentupon the technology applied (i.e., rectal palpation at35-42 days, ultrasound diagnosis at 30-32 days, bloodpregnancy test 27, 28 to 30 days [measurement ofPregnancy Associated Glycoprotein; PAG]; Silva etal., 2007). To some degree, there is a naturalpresynchronization of non-pregnant cows becausethose detected in estrus have a median return toestrus interval of 22 days in which 64.3% show estruswithin 17–24 days after first service. Thus, initation ofOvsynch at 30 days after first service would meanmost cows would be at approximately Day 8 of thecycle. GnRH injection would induce ovulation of afirst wave follicle and initiate recruitment of a newfollicular wave under a high progesteroneenvironment. At 37 days after first service, a decisioncan be made to inject PGF2a in cows diagnosednonpregnant (e.g., rectal palpation). These cowswould then be injected with GnRH and TAI at 56 hand 72 h after the PGF2a injection, respectively.

Several days after first service (days 19, 26 and 33)have been examined to begin a resynchronization ofnonpregnant cows with Ovsynch (Fricke et al., 2003).Starting the resynchronization on day 33 resulted inthe highest pregnancy rate for the second service.Ultrasound technology was used for detection of nonpregnant cows at 26 or 33 days after first service forthe day 19-26 and 33 resynchronization groups,respectively. Hypothetically, the timing of GnRH atday 26 would tend to target the majority of cows tooearly in their follicle wave (i.e., day 4 of the wave) toinduce follicle turnover, whereas at day 33 theywould be ovulating potential first or second wavefollicles and a sustained progesterone environmentwould be present for cows potentially returning toestrus between 17 to 24 days after first service.Experimental results clearly document that fertilitywas increased for the Day 33 resynchronizationgroup (i.e., 33.7%) compared to the Day 19 and 26groups (27.1% and 26.6%, respectively). The benefit ofthe day 33 resynchronization on pregnancy per TAIcompared to the day 26 resynchronization group wasrepeated (39.4% > 28.6%; Table 1) with the benefitmost apparent in primiparous cows (Sterry et al.,2006). In the latter study, insertion of a CIDR insertin cows without a CL improved pregnancy rate perTAI in the multiparous cows to a level comparable tothat of primiparous with or without a CL.

An alternative resynchronization strategy is a moreconventional system based solely on pregnancydiagnosis per rectal palpation at day 38 (Figure 4;Dewey et al., 2009). In this scenario, an Ovsynch 72 hCo-synch (GnRH, 7 d later PGF, and 72 h later GnRHand TAI) was initiated at day 38 after first service inthree groups of non-pregnant cows (Group 1 control,GnRH/Group 2 received a GnRH injection on Day 31at 7 days before pregnancy diagnosis, Group 3/CIDRreceived a CIDR insert on D 38 that was removed atthe time of PGF2a injection; Figure 4). Pregnancy rateper TAI was and tended to be greater forGnRH/Group 2 (33.6%) and Group3/CIDR (31.3%)cows, respectively, than Group 1 (24.6%) cows. It islikely that presynchronization with a single injectionof GnRH at Day 31 programmed a new follicle waveand increased the occurrence of a CL at the beginningof the Ovsynch 72 h Cosynch protocol. Insertion of aCIDR insert likely improved the synchronization ofovulation associated with the 72 h Co-synch responsebecause it held ovarian follicles from ovulatingprematurely in cows that were in late diestrus at thetime the Ovsynch 72h program was started.

4

It is clear that several alternatives are available forresynchronization of lactating dairy cows. With theacquisition of new technology for a cow sidediagnosis of nonpregnant cows early afterinsemination (e.g., 18, 27, 28 or 30 days), it will bepossible to implement even earlier resynchronizationsystems for TAI within 3 days (e.g., d 21, 30, 31 or 33)after the diagnosis of a nonpregnancy. This wouldoffer a further reduction interval to re-inseminationof 9.5 to 17 days compared to the promising systemsdescribed above.

Improving Embryo Survival: Induction of accessoryCL with hCG after inseminationIt is clear that lactating dairy cows have lower plasmaconcentrations of progesterone due to greaterprogesterone metabolism by the liver. Associatedwith high dry matter intake during lactation andassociated increases of liver blood flow steroidmetabolism is increased. Strategies to increaseprogesterone production are a challenge. Forexample insertion of a CIDR device causes only aslight chronic increase in progesterone ofapproximately 1 ng/ml far less than concentrations ofprogesterone achieved with a functional CL. On Day5 of the estrous cycle, granulosa cells of the dominantfollicle contan LH receptors such that hCG willinduce ovulation and formation of an accessory CL(Diaz et al., 1998; Schmitt et al., 1996a,b). Therefore,administration of hCG 5 d after AI has the potentialto increase progesterone secretion during earlypregnancy, and to alter ovarian follicular dynamics sothat cows have three follicular waves within theperiod approaching the time of CL maintenance (Diazet al., 1998). Injection of 3,300 IU hCG in lactatingcows on Day 5 after AI increased the number of CLand substantially elevated plasma progesteroneconcentrations (Santos etal., 2001). Conception rateson Days 28, 42, and 90 were increased by hCGtreatment, but late embryonic and fetal lossesremained unaltered. Therefore, the positive effect ofhCG on conception rates was mediated by reducing

early embryonic losses. In addition, most of thebenefit of hCG treatment was observed in lactatingdairy cows that were losing body condition duringthe breeding period and were likely those cowsproducing more milk. Furthermore, use of hCGshould be targeted to populations of cows that aresubfertile such as the high producing, lactating cowthat is losing body condition. It is important torecognize that use of GnRH, as opposed to hCG, isassociated with a shorter duration of LH exposure,with the induction of an accessory CL that is lessresponsive to LH in vitro, and a substantially lowerincrease in plasma progesterone concentrationsduring the subsequent luteal phase (Schmitt et al.,1996b). Recent study from Kansas (Stevenson et al.,2007) reported that hCG effectively inducedovulation between 4 to 9 days after insemination,increased number of CL and serum P4, and increasedconception rates but only in some herds. In contrastGnRH failed to increase progesterone or alterconception rate.

Integration of Reproductive Management withOmega NutritionCollectively, the above experimental approaches,which have fine tuned the dynamics of follicledevelopment, CL development and regression, andtiming of ovulation and insemination, result in goodon farm responses in getting cows pregnant.Development of such programs provides a platformto address what sources of variation are contributingto animals that do not conceive following theperiparturient and postpartum periods. A majornutritional focus has been undertaken in lactatingdairy cows involving the feeding of supplementalfats and has been reviewed extensively (Palmquist,2009). We have recently, developed a program ofdifferential feeding of supplemental fats that are pro-inflammatory during the transition period and anti-inflammatory during the transition subsequentbreeding period.

Rationale and DesignFeeding supplemental fatty acids (e.g., C18:2n-6

linoleic acid) during the transition period is a strategyto increase the energy density of the diet, but fattyacids could act also as a precursor for thebiosynthesis of prostaglandins of the 2 series thatexert a pro-inflammatory effect that may benefitpostpartum health of the cow. Later on after 30 dayspostpartum period, it may be reasonable to feed fattyacids (e.g.,C20:5n-3 eicosapentaenoic) that lead tosuppression in the the biosynthesis of inflammatorymolecules. This would reduce possible residualinflammatory responses in the uterus associated withcarryover effects of subclinical endometritis or asreported in repeat breeder cows, reduce the potentialluteolytic peaks at the time that the conceptus is

5

suppressing PGF2a secretion in order to maintain the

corpus luteum for pregnancy maintenance andamplify localized immune-suppression responsesassociated with early pregnancy.

In a recent Florida study, Silvestre et al. (2008a, 2008band 2008c) randomly allocated cows (n = 1,582) intotwo experimental transition diets beginning atapproximately 30 days before the expected date ofparturition and continued until 30 dpp. After 30 dppcows within each transition diet were allocatedrandomly into the experimental breeding diets thatwere fed until 160 dpp. Experimental transition andbreeding diets differed only in the source ofsupplemental FA.

Transition diets consisted of CS of palm oil (PO;EnerGII) or CS of safflower oil (SO; Prequel 21) andbreeding diets consisted of CS of PO (EnerGII) or CSof fish oil (FO, StrataG). All CS of FAs weremanufactured by Virtus Nutrition (Corcoran, CA,USA) and supplemented at 1.5% of dry matter. Dietswere formulated to meet or exceed NRC (2001)nutrient requirements for net energy of lactation(NEL), crude protein (CP), fiber, mineral andvitamins and fed to obtain intakes of 200 and 400 g/dof CS of FAs, for pre- and postpartum cows,respectively. Diets were fed as a total mixed rationtwice daily targeting 5% orts.

Cows at 43 dpp began a Presynch protocol with twoinjections of PGF2a (25 mg, dinoprost tromethamine,i.m., Lutalyse®; Sterile Solution; Pfizer Animal Health,New York, NY) injected 14 days apart. The Ovsynchprotocol was initiated 14 days after the secondinjection of PGF2a of the Presynch with a GnRHinjection (100 µg; gonadorelin diacetate tetrahydrate,i.m., Cystorelin®, Merial Ltd., Athens, GA) followed 7days later by an injection of PGF2a and a finalinjection of GnRH 56 hours later. Timed artificialinsemination (TAI) for first service was performed 16hours after the second GnRH injection of theOvsynch protocol.

All cows received a controlled internal drug-releasingdevice (CIDR, EAZI-BREED; Pfizer Animal Health,New York, NY) containing 1.38 g of progesterone at18 days after the first TAI followed 7 days later byremoval of the CIDR device and an 100 µg injectionof GnRH. At 32 days after first TAI, cows wereexamined for pregnancy by per-rectumultrasonography to identify presence of an embryoand an embryonic heart beat. Non-pregnant cowswere injected with 25 mg of PGF2a and then injectedwith 100 µg of GnRH 56 hours later. A TAI wasperformed 16 hours after the last GnRH for thesecond service. Cows were examined for pregnancyby per-rectum ultrasonography at 32 days after

second service. All cows diagnosed pregnant afterfirst and second services were re-examined by per-rectum ultrasonography at 60 days after inseminationto determine pregnancy losses.

Pregnancy per AI, pregnancy losses, and cumulativeproportion of pregnant cows after two services wereanalyzed using pre-determined statistical contrasts totest the effects of the transition diets (PO-PO + PO-FOvs. SO-PO + SO-FO), breeding diets (PO-PO + SO-POvs. PO-FO + SO-FO) and the interaction of transitionand breeding diets (PO-PO + SO-FO vs. PO-FO + SO-PO) accordingly with the experimental feedingdesign described above (Silvestre, 2008a, 2008c).

Reproductive and Lactation ResponsesTransition, breeding and interaction of diets did notaffect pregnancy per AI at 32 and 60 days after TAIfor first service (Table 3). However, pregnancy lossfrom day 32 to day 60 after the first TAI was less (P <0.05) in FO compared to PO supplemented cowsduring the breeding period (Table 3). For secondservice, breeding diet altered (P < 0.05) the 32 dayestimates of pregnancy per AI and a tendency (P <0.10) for an interaction was detected betweentransition and breeding diets (Table 3). The increasein day 32 pregnancy per AI caused by FO was greaterin cows fed the SO transition diet, whereas there wasno increase in pregnancy per AI in cows fed the PObreeding diet regardless of transition diet (Table 3).Both breeding diet and a transition by breeding dietinteraction (P < 0.05) were detected for the 60 daypregnancy per AI response in which FO stimulatedpregnancy rate per AI but the response to FO wasgreater in cows fed the SO transition diet (Table 3).

Table 3. First and second services pregnancies per AIat 32 and 60 days after insemination and pregnancyloss for experimental diets

6

Milk weights were recorded once a month for allcows. The single measurement of milk production foreach month was considered as the average for themonth. Data from the first 5 months of lactation wereused. Average milk yield for combinations oftransition and breeding diets were PO-PO (41.1 ± 0.6Kg/day; n = 295), PO-FO (41.3 ± 0.7 Kg/day; n =280), SO-PO (41.7 ± 0.6 Kg/day; n= 302) and SO-FO(42.1 ± 0.7 Kg/day; n = 289). Average milk yield wasaffected (P = 0.02) by transition diets such that cowssupplemented with SO (41.9 ± 0.4 Kg/day; n = 591)during the transition period had a greater averagemilk yield for the 5 months postpartum comparedwith cow fed PO (41.2 ± 0.4 Kg/day; n = 575).Average milk yield was not affected by breeding dietor the interaction between transition and breedingdiets.

The integration of the disciplines of ruminantnutrition, reproductive physiology, immunology andclinical medicine has the potential to provide usefulalternatives to improve postpartum health andfertility in dairy cows in a scenario of increasing milkproduction. For example sequential feeding of dietsrich in linoleic acid followed by diets rich ineicosapentaenoic and docosahexaenoic fatty acidsduring the peri-parturient and breeding periods,respectively, impacted fatty acid composition oftissues, altered immune-responses and fertility(Silvestre et al. 2008a, 2008b and 2008c).

ConclusionsTremendous advances have been made for improvingmilk production, but have in turn, resulted in anoverall decline in reproductive efficiency for the dairyindustry. Problems associated with the cow includeinability to properly express estrus and alteredhormonal profiles resulting in low conception ratesand increased early embryonic death. Coordinatedsystems of reproductive management offer means toimprove herd reproductive performance and majoradvances have been made for synchronization ofovulation in both lactating dairy cows and dairyheifers. Such systems are predicated on a greaterunderstanding of the factors controlling follicledevelopment, ovulation and CL development.Systems of reproductive management need toconsider: efficient systems of presynchronization,induction of a new follicle wave in a high proportionof animals, optimization of the period of follicledominance, sustained presence of a CL during theperiod of follicle recruitment, effective induction ofCL regression, optimal timing of ovulation andtiming of insemination. The programs as describedrequire the producer, veterinarian and reproductivemanagement staff to understand the programs andmake the effort to obtain a high level of compliance.The platforms used for controlling first service and

resynchronized subsequent services in cows that donot conceive provide valuable platforms toimplement new technology such as the use of sexedsemen, embryo transfer and cow side chemicaldiagnosis of nonpregnant cows. Functional andefficient computer record programs are essential toimplement such reproductive management programs.The integration of the disciplines of ruminantnutrition, reproductive physiology, immunology andclinical medicine has the potential to provide usefulalternatives to improve postpartum health andfertility in dairy cows in a scenario of increasing milkproduction. We propose that sequential feeding ofdiets rich in LN followed by diets rich in EPA andDHA during the peri-parturient and breedingperiods, respectively can benefit overall cowperformance and fertility. Such feeding strategieswarrant economic analyses to evaluate cost-benefit.With the advent of new technologies to preciselymanipulate reproductive function in lactating dairycows, dairy producers are presented with a newopportunity. Coordination of management strategiesto maximize both milk production and reproductiveperformance may optimize the economical return ofdairy herds, and allow for the industry to takecomplete advantage of the genetic potential toimprove milk production through artificialinsemination.

ReferencesBartolome JA, Sozzi, A., McHale J, Melendez P, Arteche A CM, Silvestre FT, Kelbert D, Swift K, Archbald LF, ThatcherWW. (2005). Resynchronization of ovulation and timedinsemination in lactating dairy cows, II: assigning protocolsaccording to stages of the estrous cycle, or presence ofovarian cysts or anestrus. Theriogenology 63, 1628-1642.

Bleach ECL, Glencross RG, Knight P.G. (2004). Associationbetween ovarian follicle development and pregnancy ratesin dairy cows undergoing spontaneous oestrous cycle.Reproduction 127:621–629.

Brusveen DJ, Cunha AP, Silva CD, Cunha PM, Sterry RA,Silva EPB, Guenther JN, Wiltbank MC. (2008). Altering thetime of the second gonadotropin-releasing hormoneinjection and artificial insemination (AI) during Ovsynchaffects pregnancies per AI in lactating dairy cows. J. DairySci. 91, 1044-1052.

Cerri RLA, Rutigliano HM, Chebel RC, Bruno RGS, SantosJEP. (2009). Period of dominance of the ovulatory follicleduring synchronization programs influences embryoquality. Reproduction 137: 813–823.

Dewey ST, Mendonça LG, Lopes Jr G, Rivera FA, GuagniniF, Chebel RC and Bilby TR. (2009). Resynchronizationstrategies to improve fertility in lactating dairy cowsutilizing a presynchronization injection of GnRH orsupplemental progesterone: I. Pregnancy rates and ovarianresponses. J. Dairy Sci. 92: E-Suppl. 1 (Abstract): 267.[RTF bookmark start: }_Ref114736337

7

Diaz T, Schmitt EJ-P, De La Sota RL, Thatcher M-J, ThatcherWW. (1998). Human chorionic gonadotropin-inducedalterations in ovarian follicular dynamics during theestrous cycle of heifers. J. Animal Sci. 1998;76:1929-1936.[RTF bookmark end: }_Ref114736337

El-Zarkouny SZ, Cartmill JA, Hensley BA, Stevenson JS.(2004). Pregnancy in dairy cows after synchronizedovulation regimens with or without presynchronizationand progesterone. J. Dairy Sci. 87, 1024-1037.

Fricke PM, Caraviello DZ, Weigel KA, Welle ML. (2003).Fertility of dairy cows after resynchronization of ovulationat three intervals following first timed insemination. J.Dairy Sci. 86, 3941-3950.

Galv„o KN, SaFilho MF, Santos JEP. (2007). Reducing theinterval from presynchronization to initiation of timedartificial insemination improves fertility in dairy cows. J.Dairy Sci. 90, 4212-4218.

Lopez H, Caraviello DZ, Satter LD, Fricke PM, WiltbankMC. (2005). Relationship between level of milk productionand multiple ovulations in lactating dairy cows. J. DairySci. 88, 2783-2793.

Lopez H, Satter LD, Wiltbank MC. (2004). Relationshipbetween level of milk production and estrous behavior oflactating dairy cows. Anim. Reprod. Sci. 81, 209-223.

Lucy MC. (2001). Reproductive loss in high-producingdairy cattle: where will it end? J. Dairy Sci. 84, 1277-1293.

Moore K, Thatcher WW. (2006). Major advances associatedwith reproduction in dairy cattle. J. Dairy Sci. 89, 1254-1266.

Moreira F, Orlandi C, Risco CA, Mattos R, Lopes F,Thatcher WW. (2001). Effects of presynchronization andbovine somatotropin on pregnancy rates to a timedartificial insemination protocol in lactating dairy cows. J.Dairy Sci. 84, 1646-1659.

Norman HD, Wright JR, Hubbard SM, Kuhn MT, MillerRH. (2007). Genetic Selection for Reproduction: Current ReproductiveStatus of the National Herd; Application of Selection Indexes for Dairy Producers. In:Proc. Dairy Cattle Reproductive Conference, Eds. W.W.Thatcher and E.R. Jordan, Dairy Cattle ReproductiveCouncil, Hartland, WI, pp 69-78.

Palmquist DL. (2009). Omega-3 fatty acids in metabolism,health, and nutrition and for modified animal productfoods. The Professional Animal Scientist 25: 207-249.

Pursley JR, Kosorok MR, Wiltbank MC. (1997a).Reproductive management of lactating dairy cows usingsynchronization of ovulation. J. Dairy Sci. 80, 301-306.

Santos JEP, Narciso CD, Rivera F, Chebel RC, Thatcher WW.(2010). Effect of reducing the period of follicle dominance ina timed AI protocol on reproduction of dairy cows. J. DairySci. (In Press).

Santos JEP, Thatcher WW, Pool L, Overton MW. (2001).Effect of human chorionic gonadotropin on luteal functionand reproductive performance of high-producing lactatingHolstein dairy cows. J. Animal Sci.:79:2881-2894.

Savio JD, Keenan L, Boland M P, Roche JF. (1988). Pattern ofgrowth of dominant follicles during the oestrous cycle ofheifers. J. Reprod. Fertil. 83, 663-671.

Schmitt EJ-P, Barros CM, Fields PA, Fields MJ, Diaz T,Kluge JM, Thatcher WW. A cellular and endocrinecharacterization of the original and induced CL afteradministration of a gonadotropin-releasing hormoneagonist or human chorionic gonadotropin on day five ofthe estrous cycle. J Anim Sci 1996a;74:1915-1929.[RTFbookmark start: }_Ref112123962

[RTF bookmark end: }_Ref112123962Schmitt, E.J.-P., T. Diaz,C.M. Barros, R.L. de la Sota, M. Drost, E.W. Fredriksson,C.R. Staples, R. Thorner and W.W. Thatcher. 1996b.Differential response of the luteal phase and fertility incattle following ovulation of the first-wave follicle withhuman chorionic gonadotropin or an agonist ofgonadotropin-releasing hormone. J. Anim. Sci. 74:1074-1083.

Silva E, Sterry RA, Kolb D, Mathialagan N, McGrath MF,Ballam JM and Fricke PM. (2007). Accuracy of a pregnancy-associated glycoprotein ELISA to determine pregnancystatus of lactating dairy cows twenty-seven days aftertimed artificial insemination. J. Dairy Sci. 90, 4612-4622.

Silvestre F. T., T. S. M. Carvalho, N. Francisco, J. E. P.Santos, C. R. Staples, W.W.Thatcher. Effects of DifferentialSupplementation of Calcium Salts of Fatty Acids (CSFAs)on Dairy Cows. J. Dairy Sci., 91:(suppl. 1), p. 76 , 2008a.

Silvestre F.T., T.S.M. Carvalho, C. Crawford, J.E.P. Santos,C.R. Staples, W.W. Thatcher. 2008b. Effects of DifferentialSupplementation of Calcium Salts of Fatty Acids (CSFAs) toLactating Dairy Cows on Plasma Acute Phase Proteins andLeukocyte Responses: Phagocytic and Oxidative Burst,CD62L and CD18 Expression and Cytokine Production.Biol. Reprod., special issue, p.158.

Silvestre, F.T. 2008c. Nutraceutial and Hormonal Regulationof Immunity, Uterine Health, Fertility, and Milk Productionof Postpartum Dairy Cows. Doctorate Dissertation. Univ. ofFlorida, Gainesville.

Sterry RA, Welle ML and Fricke PM. (2006). Effect ofinterval from timed artificial insemination to initiation ofresynchronization of ovulation on fertility of lactating dairycows. J. Dairy Sci. 89, 2099-2109.

Stevenson JS, M. A. Portaluppi, D. E. Tenhouse, A. Lloyd,D. R. Eborn, S. Kacuba, and J. M. DeJarnette. 2007.Interventions After Artificial Insemination: ConceptionRates, Pregnancy Survival, and Ovarian Responses toGonadotropin-Releasing Hormone,Human Chorionic Gonadotropin, and Progesterone. J.Dairy Sci. 90:331–340.

8

Introduction Poor reproductive efficiency is a significant source ofeconomic loss affecting many dairies. Reproductiveinefficiency results in economic losses through avariety of ways. Cows that fail to become pregnantduring the breeding period are culled once milkproduction has declined below economically viablelevels, forcing the replacement of otherwise healthyanimals. Cattle that eventually become pregnant, butat a much later time than desired, spend adisproportionate amount of their lactation at lowerlevels of milk production, costing the dairy lostopportunity for addition marginal milk. Historically,dairy managers and consultants have used calvinginterval or days open as indices for evaluation ofreproductive performance and the optimal calvinginterval for most cows has been considered to be inthe range of 12 to 13 months, yielding a lactationlength of approximately 10.5 to 11 months. Thisbelief has been supported by other economic modelsexamining the effect of days open and reproductivesuccess on economic returns of dairies.1-3 However,often, these assumptions do not fully consider thetransition related culling risk, the potentialdifferences in lactation curve shape of today’smodern dairy cow, or the true cost associated withcows that fail to become pregnant and thus areremoved from the herd.

The use of calving interval or average days open arebiased estimates of reproductive performance sincethey only reveal information about the “successful”cows and fail to consider the cows that neverconceive, and thus, are removed from the herd asnon-pregnant cows. Average days open only givesthe interval from calving to conception for cows thathave successfully conceived. In most cases, daysopen gives no information regarding the status of thenon-pregnant animals other than potentially theircurrent days in lactation or a projected minimumdays open. Calving interval is even more limited inthat it only considers the cows that became pregnantand maintained that pregnancy throughout a fullgestation. Pregnancy rate (PR), defined as thehistorical rate at which eligible cows became

pregnant each 21-d cycle (# pregnant/ # of eligiblecow-cycles) and examined over a sequence of 21-dcycles, is the preferred parameter for evaluatingreproductive performance. To be considered aseligible or at risk for PR, a cow must be past thevoluntary waiting period (VWP), not alreadypregnant at the start of the 21-day period of interest,must have a known outcome at the end of the periodunder consideration, and must be present andeligible for pregnancy for at least half of the 21-dayperiod. A “do-not-breed” (DNB) is a code that isassigned to cows that are destined to be culled.These cows are no longer considered eligible forbreeding or pregnancy and are removed from thefuture reproductive statistics. PR is more sensitive todetecting recent changes in reproductive performanceand provides useful information since both pregnantand non pregnant cows that meet the eligibilitycriteria are considered in the calculation.4 Based ondatabase surveys as reported by Steve Stewart, BruceClark, Don Niles, Stephen LeBlanc and DavidGalligan (personal communications), PR in the U.Sand Canada appears to average between 14-16%. Yet,many dairy advisors consider a PR of 25-30% to bethe ultimate goal for optimum reproductivemanagement.

With the large difference between the average PR andthe goal for PR, there is significant room forimprovement. There are many ways of improvingherd reproductive efficiency and many non-breedingfactors that dramatically influence reproductiveoutcomes, but essentially it comes down toimproving insemination risk (IR), conception risk(CR), or preferably, both. Insemination risk is definedas the number of animals inseminated divided by thenumber of animals eligible (same eligibility definitionas discussed previously for PR). For IR, it does notmatter whether the animal was inseminated viaestrus detection or by using some form of timed AI.Conception risk is defined as the number of animalsthat were found pregnant divided by the totalnumber of cows (inseminations) either pregnant oropen; hence, to calculate conception risk, the outcomemust be known. The objective of this paper is to

9

Economic Returns of ImprovedReproductive Performance in Dairy Cattle

M. W. Overton DVM, MPVMUniversity of Georgia, College of Veterinary Medicine

Department of Population HealthRhodes Center - ADS

425 River RoadAthens, GA 30602-2771

moverton@uga.edu

explore the potential value generated as a result ofimproving PR via a variety of methods and toexamine the various drivers of economic returnsassociated with changes in PR, as well as illustratinghow much a dairy may be able to spend in order totry and achieve an improved PR.

Model Building and AssumptionsThe original simulation model was built using Excel“spreadsheets and @RISK® simulation software andhas been modified numerous times in order to refineit and to examine new factors. Distributionsdescribing CR and IR (almost exclusively from estrusdetection) were fit from data obtained fromapproximately 95 herds representing approximately150,000 cows (Niles, et al. and other California dairyherds) and are used to mimic the normal variationseen between and within dairies. Daily milk and 305day mature equivalent milk production estimateswere also obtained from a variety of dairies and usedto fit lactation persistency curves based on day inmilk (DIM). Milk price estimates, cull cow values,market cow values, labor estimates, and other keyinputs were derived from either published work oradapted from actual herd data. Culling risks over theentire lactation period were obtained from actualherd Dairy Comp 305 records and mathematicallyadjusted from 30-day to 21-day intervals to beconsistent with the breeding cycles.

All values of change in PR are obtained bycomparison with a baseline program. The baselinebreeding program is a simple estrus detection-basedreproductive program with CR and IR distributionsat each 21-day interval following a 50-day voluntarywaiting period. The potential breeding period is 1221-day cycles for a total of 252 days of breeding. Inother words, cows are eligible for breeding from 50days in milk until 302 days in milk. Simulated PR’sare obtained by multiplying randomly generatedsamples from the CR distribution and IR distribution.The user can manipulate the baseline PR by applyinga multiplier to the sampled CR, IR or both,throughout the program, resulting in the desired PRfor comparison.

There are 3 breeding programs for comparison. Thefirst is called an “improved baseline program” (IBP).This program is designed to mimic the changes thatmay be obtained as a consequence of improving CR,IR or both over the course of the breeding period. Nosynchronization protocols are included in thisparticular approach. This particular program wasdesigned to estimate the value that may be obtainedby simply doing a better job with a traditional estrusdetection-based program.

The second program that is used for comparison is a

total timed AI program (TAI) and is based upon aPresync-Ovsynch with day-32 Resynch. Briefly, thisapproach includes an injection of prostaglandin F2· at36+/- 3 days in milk, followed in 14 days with asecond injection. After an additional 14 days, cowsreceived an injection of GnRH to start the Ovsynchportion. In 7 days, another prostaglandin is given,followed in 56 hours with the final GnRH injectionand a timed insemination 12-16 hours later. Noestrus detection is used. All cows are given aninjection of GnRH at 32 days post-breeding. In 7days, cows are examined via palpation per rectumand non-pregnant animals are given a prostaglandininjection and then proceed to complete the Resynch(Ovsynch) portion of the TAI. Following thisschedule, all non-pregnant cows are re-inseminatedevery 42 days until the breeding period is concluded.

The final program for comparison is a combination ofestrus detection and TAI and is referred to as themodified Presynch program (MPS). Cows thatfollow this protocol receive a prostaglandin injectionat 36+/- 3 days in milk and again at 50+/- 3 days inmilk. Cows that are observed in estrus after thesecond injection are inseminated per normal farmroutine. Cows that are not observed within 14 daysstart the Ovsynch program as previously described.Afterwards, all inseminations for the remainder ofthe breeding period are performed using estrusdetection. Thus, the second breeding cycle iscomposed of two groups of cows - those that areinseminated via estrus detection and those that areinseminated by TAI, depending upon whether estruswas detected in the first 21 days following Presynchor not.

In both the TAI and the MPS programs, all cows areassumed to incur the cost of the injections, as per theschedule, but due to less than perfect on-farmcompliance, only 85-90% of cows initially enrolled areactually inseminated, depending on the compliancefactor input into the model. The CR for each of thesetwo programs is modeled as a function of the farm’sbaseline conception risk, the estimated proportion ofcows that are truly cycling, expected distributionwithin the estrous cycle at the start of the program,and published reports involving TAI.

5-11

The PR from traditional breeding is obtained bytaking the product of random samples from CR andIR for each cycle. All cycles are exactly 21 days long,all cows calve at the same time, and they arefollowed prospectively. There was no attempt tomodel the impact of abortion or seasonal effects onreproduction except as demonstrated by the impactfrom the original data set on CR and IR distributions.(It is assumed that CR results used in the modelalready reflect some of the expected embryonic

10

deaths since most herds are not palpated forpregnancy until approximately 40 days post-insemination and a large proportion of pregnancywastage occurs by 45-50 days.) Timed AI programsare assumed to have no effect on subsequentconception or estrus detection risk in non-pregnantcows and it is assumed that there are no differencesin reproductive efficiency for any of the programsbetween parities of lactating cows, i.e., the results areexpressed for the blended population on a per cowslot basis. The voluntary waiting period is 50 daysand as cows move from the first cycle to the second,the proportion of cows expected to be cyclingincreases (the model decreases the proportion that areanestrus by 33% of the original proportion). Cowsare palpated for pregnancy at approximately 39+/- 3days post-breeding. Milk production, price of milk,and other economic values remain the samethroughout the year. Milk production level may beutilized as a discrete variable to determine the impactat a certain 305ME milk production level, orstochastically (sampled from a distributions) todetermine the average impact (and expected range ofimpacts) over many dairies.

Reproductive performance for each of the 3alternative breeding approaches is then compared tothe original baseline program. Herd specific datathat may influence on-farm profitability, includingdry period length, calf death losses, culling riskacross time, milk production, milk price,pharmaceutical costs, labor costs, and feed costs areentered. The model’s inputs, herd-specific data, andpre-set distributions are linked to tables for eachreproductive intervention and are used to estimatethe average pregnancy rate over 252 days of potentialbreeding. The input table, herd-specific data, andpregnancy rate projections are linked to partialbudgets (modifications of original work by Wolf andDartt) to compare predicted economic returnsresulting from changes in daily milk yield as a resultof changes in reproductive performance.12 Cows thatare ultimately culled as non-pregnant, but that aremilked successfully until then, are removed from thedairy at 600 to 750 days in milk. Stochastic modelingwith @RISK® simulation software utilizes MonteCarlo sampling of the pre-set distributions and runs1000 iterations. Results are then displayed asprobability distributions, with a mean and 90%confidence interval.

Annual herd turnover or culling risk may bedramatically impacted by changes in reproductiveperformance. Herds that get more cows pregnanthave fewer cows that must be removed due to afailure to become pregnant. However, these sameherds are also producing more female calves, andassuming proportional mortality risk across time, will

have more replacement animals available to eithersell, expand the herd, or replace a less profitableanimal in the herd. If the latter option is chosen, theherd’s culling risk will increase. In the model, allcalves are sold as newborn calves and purchasedback as needed. When reproductive performanceimproves, there are fewer cows that are forciblyremoved due to reproductive failure. Consequently,the herd’s apparent culling risk decreases. However,in the model, I assumed that the dairy would save oninvoluntary culling by retaining cows equal innumber to one half of the increased number ofpregnancies accrued. The other half would allow thedairy to cull some poor producers from the herd. Asa consequence, the herd’s culling risk would changeas a consequence of the changes in reproductiveperformance.

The economic value of the change in PR is estimatedby use of simple partial budgeting approaches. Eachnew program is compared to the baseline program bytransferring the various outputs into its own partialbudget. The sources of revenue include predictedmilk per cow per day over a year (as determined bythe modeled herd’s estimated average days in milkand the herd’s lactation curve), the annualized valueof the calves produced, and the annualized value ofthe culled cows. Subtracted from the revenues are avariety of expenses that include any additionalreplacement costs, the marginal feed consumed bycows to produce the marginal milk, additional feedconsumed by additional non-lactating cows, theadditional costs for housing, labor, and medicalexpenses, as well as any additional costs due to thechange in reproductive management approach.Finally, the difference is adjusted for the time value ofmoney. Since money received in the future is worthless than money received today, future returns haveto be adjusted for when the returns actually occur.All of the revenues and expenses, and thus the netreturns, are reported as dollars gained (or lost) perlactating cow slot on the dairy per year.

Results and Conclusions

The predicted results of 1000 model iterationscomparing the benefits of improving PR byincreasing IR by 10% (through improved estrusdetection) over baseline are shown in figure 1. Thestarting average PR was 16% and the improvedprogram’s PR was approximately 18%.

11

Figure 1. Distribution of PR outcomes for improvedprogram as a consequence of improving inseminationrisk (in this case, estrus detection) by 10% ascompared to the baseline program.

Figure 2 displays the predicted economic value of thePR improvement (average of approximately 2 units ofPR change) over 1000 iterations. These results weretaken from the fully stochastic model with thefollowing input distributions for the baselineprogram (and their expected or average value): milkprice ($12), CR (30%), IR (57%), herd level of milkproduction (23,000 lbs), market cow value ($621),replacement heifer cost ($1700), heifer calf value($250) and bull calf value ($15). Overall, theimprovement in IR resulted in a net of approximately$9 per unit change in PR, or a total return ofapproximately $18 per cow slot per year.

Figure 2. Distribution of Predicted Returns per UnitChange in PR As a Consequence of ImprovingInsemination Risk by 10% (Mean = $18)

As mentioned previously, the model also allows forcomparison of different approaches to improvingreproductive efficiency. Each of these newapproaches is compared with the original baselineprogram to estimate the value of the change after alsoconsidering the cost of implementing the newprograms. The results are shown below in figure 3.Each program is expected to yield an improved PRbut the magnitude of the improvement and the valueof the change is different for each one.

First, the improved baseline shows a similar result asabove with the new PR of 17.5% which is predicted to

yield a value of about $18 per cow slot per year as aresult of the improved insemination risk.

The total TAI approach also yields an improved PR,although the apparent increase is minor relative tothe other approaches, but a word of caution is duehere. Total TAI, as modeled in this scenario, yields aPR of almost 19% when using a VWP of 70 days(when the breeding actually starts) but forcomparison sake, I maintained the same VWP as theother programs of 50 days. Hence, the lower thanexpected PR of only 16% is due in large part to thelack of breeding during the first potential cycle at 50-70 DIM. These non-breeding days are used topresynchronize cows, yielding an improved CR.However, it comes at the cost of a delay to firstservice. Despite the increased cost of this approach,there is still a positive return of about $15 ascompared to the baseline approach.

The final approach was the backdoor Ovsynchprotocol which included a Presynch series for allcows followed by a one-time use of Ovsynch only forcows that failed to be inseminated via estrusdetection in the first cycle. This program incurs alarger cost with a lower rate of return as compared tothe others, but is still an improvement compared tothe baseline. The expected value of this approachwould be greater had the program continued withadditional Ovsynch-based breedings in later cycles.However, this hybrid approach was not modeled inthis set of iterations.

Figure 3. Estimated results and associated values ofthree different approaches to improving reproductiveperformance as compared to the baseline program.

Figure 4 illustrates a very important concept toremember when evaluating the economic returns ofimproving reproductive performance – predictedreturns follow a curvilinear relationship. In otherwords, the average return associated with improvingPR varies depending upon the relative success of thestarting point. In this series of scenarios, I calculatedthe predicted returns of increasing PR starting at a10% baseline PR. The baseline PR of 10% wascompared to improved PR across a range of values,derived by changing the CR and IR. At 10% PR, thevalue of improving PR by 2 unit (ie. 10% to 12% PR)is predicted to be worth approximately $54 per cowslot per year when milk was valued at $12/ cwt.Conversely, going from 18 to 20% is worth

12

approximately $14 and from 26 to 28% is worth only$2.

Figure 4. Model Results of Value of Changes in PRover Ranges of PR

One of the benefits of using stochastic simulationmodels is the ability to perform sensitivity analysesof the major effect modifiers. Within thedistributional ranges used in the model, the followingvariables had the largest impact on the economicvalue associated with reproductive performancechange and each of the variables is listed indescending order of impact: 1) Insemination risk – Asinsemination risk increased in the baseline model, thevalue of improving PR decreased. In other words, ifthe starting reproductive performance was high,there was less to be gained from furtherimprovements. 2) Conception risk – As conceptionrisk increased in the baseline model, the value of eachincremental change decreased just as withinsemination risk. 3) Milk price – As milk priceincreased, the predicted value of the change inreproductive performance increased. 4) Feed cost –As feed cost increased, the value of change in PRdecreased due to the reduced profit marginassociated with the marginal milk produced. 5) Levelof milk production – As the herd level of milkproduction increased, the predicted value due toimproving reproductive performance increased. 6)Replacement cost – As the price for replacementheifers increased, the value realized by improvingreproductive performance increased. 7) Market cowprice – As the value of the market cow increased, thevalue realized by improving reproductiveperformance decreased.

The primary economic driver of improvingreproductive performance is the value of theadditional marginal milk produced as a consequenceof decreasing days in milk for the “herd”. Figure 5demonstrates the impact that milk price may have onthe economic returns. For this example, each of thefollowing inputs was entered as specific values andthe only one to vary was the price of milk: herd level

of milk production = 25,000 lbs, market cow value =$0.46/ lb, replacement heifer cost = $1600, TMR cost= $210/ ton, heifer calf = $250 and bull calf = $15.For this set of scenarios, a 50-day voluntary waitingperiod was used and other than additional semenand insemination fees associated with an increasedinsemination risk, no additional reproductivemanagement costs were assumed. As the value ofmilk increases, the value of the reproductive changeincreases within a range of PR change. For example,at $14 milk, increasing PR from 18% to 20% ispredicted to yield an economic return ofapproximately $24 per cow slot or roughly about$12/ unit change in PR/ per cow slot per year.

The concept of diminishing returns is nothing new.We see similar patterns in many biological systems.In the case of reproductive management, one mustkeep this issue in mind relative to makingrecommendations to clients. Herds that are alreadydoing a good job reproductively have less potentialeconomic value to be gained by improvingperformance even further. Likewise, if a herd’sperformance is already good with a baseline breedingprogram, one should carefully consider whetheradditional input costs will legitimately improve PRand return a profit to the dairy. In general, herdsshould work to improve basic semen handling andestrus detection prior to jumping on a TAI program.Other management issues such as compliance toprotocol are also critical to the success of anyprogram.

Most herds have much to gain by improvingreproductive performance. Improving PR shouldresult in higher milk production, more pregnantcows, more calves, and reduced reproductive-basedculling. Sensitivity analyses of model results revealthat insemination intensity, whether by estrusdetection, timed AI or a combination, has the largestimpact on reproductive performance. Efforts atimproving reproductive success should first focus onmaximizing the herd’s basic estrus detectionefficiency, due to its large impact on reproductivesuccess and because it is more easily improved ascompared to conception rate. Herds with very poorreductive efficiency have the most to gain by

13

improving PR, and within a given level of PR, theprice of milk has the greatest effect on the value ofthe economic change, followed by the herd’s level ofmilk production. Consequently, our emphasis inreproductive management should continue to beplaced on improving insemination risk while at leastmaintaining conception risk. Although almost anyherd can potentially benefit from synchronizationprograms, herds with poor reproductive performanceare expected to realize the greatest potential returnfrom improving reproductive performance, especiallythose herds with higher levels of milk production.

References:1. DeLorenzo MA, Spreen TH, Bryan GR, et al.Optimizing model: insemination, replacement,seasonal production, and cash flow. J Dairy Sci1992;75:885-896.

2. Hady PJ, Lloyd JW, Kaneene JB, et al. PartialBudget Model for Reproductive Programs of DairyFarm Businesses. J Dairy Sci 1994;77:482-491.

3. Meadows C, Rajala-Schultz PJ, Frazer GS. Aspreadsheet-based model demonstrating thenonuniform economic effects of varying reproductiveperformance in Ohio dairy herds. J Dairy Sci2005;88:1244-1254.

4. Galligan DT, Ferguson JD, Dijkhuizen AA, et al.Optimal Economic Goals in Reproduction:Underlying Concepts from Semen to Culling inProceedings of the National ReproductionSymposium 1994;55-64.

5. Bartolome JA, Archbald LF, Morresey P, et al.Comparison of synchronization of ovulation andinduction of estrus as therapeutic strategies forbovine ovarian cysts in the dairy cow. Theriogenology2000;53:815-825.

6. Cartmill JA, El Zarkouny SZ, Hensley BA, et al.Stage of cycle, incidence, and timing of ovulation,and pregnancy rates in dairy cattle after three timedbreeding protocols. J Dairy Sci 2001;84:1051-1059.

7. Keister ZO, Denise SK, Armstrong DV, et al.Pregnancy outcomes in two commercial dairy herdsfollowing hormonal scheduling programs.Theriogenology 1999;51:1587-1596.

8. Moreira F, Orlandi C, Risco CA, et al. Effects ofpresynchronization and bovine somatotropin onpregnancy rates to a timed artificial inseminationprotocol in lactating dairy cows. J Dairy Sci2001;84:1646-1659.

9. Pursley JR, Mee MO, Wiltbank MC.Synchronization of Ovulation in Dairy Cows UsingPGF2Alpha and GnRH. Theriogenology 1995;44:915-923.

10. Risco CA, Drost M, Archbald L, et al. TimedArtificial Insemination in Dairy Cattle - Parts I and II.The Compendium 1998;20:s280-s287 (issue 210)-and1284-1289 (issue 1211).

11. Stevenson JS, Kobayashi Y, Thompson KE.Reproductive performance of dairy cows in variousprogrammed breeding systems including OvSynchand combinations of gonadotropin-releasinghormone and prostaglandin F2 alpha. J Dairy Sci1999;82:506-515.

12. Wolf CA. Analyzing reproductive managementstrategies on dairy farms. Staff Paper 99-23,Department of Ag Econ, Michigan State University 1999.

14

What are Fatty Acids?Fatty acids are chains of carbons that end in an acidgroup, or carboxyl group as it is referred to inbiochemistry. An example of a common fatty acid isstearic acid with 18 carbons and no double bonds(Figure 1).

Fatty acids, such as stearic acid, are referred to assaturated because all the carbons are holding themaximum number of hydrogens possible, or the fattyacid is “saturated” with hydrogen. Stearic acid is lowin plant oils, but present in higher amounts in animalfats, particularly in fats obtained from ruminantspecies such as beef tallow.

Oleic acid and linoleic acid are examples ofunsaturated fatty acids containing one or more doublebonds (Figure 2). Oleic acid has a single double bondbetween carbons 9 and 10, and is referred to as amonounsaturated fatty acid. Linoleic acid is apolyunsaturated fatty acid containing two doublebonds between carbons 9 and 10, and betweencarbons 12 and 13. Oleic acid is the predominant fatty

acid in animal fats and some plant oils, such as canolaoil Linoleic acid is the predominant fatty acid in manyplant oils, including cottonseed oil, soybean oil, andcorn oil. Linolenic acid, with three double bonds, isthe primary fatty acid in most pasture species and inlinseed oil from flax.

Sources of Fatty Acids Grain and forage lipidsThe fatty acid content of most cereal seeds andforages typically ranges from 10 to 30 g/kg DM, withthe majority of the fatty acids classified asunsaturated (predominately oleic, linoleic, andlinolenic acids). Among the unsaturated fatty acids,linolenic acid is the predominant fatty acid in mostforage species followed by linoleic acid (Hatfield etal., 2007). In the cereal seeds, fatty acids arecomprised mainly of linoleic acid followed by oleic acid.

Fatty acid concentrations in some pasture can exceed50 g/kg DM, depending on plant species, stage ofmaturity, environment, etc. Fatty acid content ofannual ryegrass pasture that was clipped in the field,immediately immersed in liquid nitrogen, and thenfreeze dried contained as much as 68 g/kg DM totalfatty acids (Freeman-Pounders et al., 2009). CPM-Dairy lists 116 g/kg DM fatty acids in perennialryegrass pasture. Cattle grazing some species ofimmature pasture, in effect, may be consuming a highfat diet. Much lower concentrations are usually seenin hay and silage prepared from the same plantspecies. This is partially due to loss of plant leaveswhere chloroplast lipid is concentrated, but also dueto plant metabolism of stored energy sources. Plantenzymes can continue to function in dried foragecontaining as little as 5 to 10% moisture. Plantmaturity has a definite impact on both fatty acidcontent and fatty acid composition. Fatty acid content(g/kg DM) generally is highest in the spring and fallseasons and lowest in the summer months. Forexample, fresh perennial ryegrass contained 32 g/kgDM total fatty acids during primary growth in May,but only 12 g/kg DM at the beginning of secondregrowth (Bauchart et al., 1984). Linolenic acidfollows a similar seasonal pattern (Bauchart et al.,1984). As linolenic acid declines over the summermonths, percentages of palmitic and linoleic acidincreases.

15

Where Do All These Fatty Acids Come FromAnd What Do They Do to My Cow?

Tom JenkinsClemson Universitytjnkns@clemson.edu

Fat supplementsMost plant oils contain 100% ether extract with a highpercentage of fatty acids. The impurities extracted,such as water and pigments, are removed duringrefining leaving the commercial plant (soybean oil,canola oil, corn oil, etc) and animal (tallow, grease,etc) fats with mainly triglycerides consisting of 90-93% fatty acids. The remaining 7-10% is mainlyglycerol. Glycerol is readily utilized as an energysource, but only contains the energy ofcarbohydrates. Caution is advised when obtainingfats from unknown vendors to be sure thatconsiderable impurities do not still remain in theproduct that lower the fatty acid and energy content.Rather than guessing, it pays to have a sample of thefat analyzed for fatty acid content and profile. Theether extract values listed in NRC (2001) for dairycattle exceed 99% for all fat categories (vegetable oil,tallow, hydrolyzed tallow fatty acids, and partiallyhydrogenated tallow) except for calcium soaps. Etherextract for the vegetable oil, tallow, and partiallyhydrogenated tallow are assumed to contain 90%fatty acid and 10% glycerol. Ether extract for thehydrolyzed tallow fatty acids is assumed to contain100% fatty acids. Ether extract for calcium soaps islisted as 84.5% in NRC (2001) for dairy cattle, whichis assumed to be all fatty acid.

Fatty Acid Transformations in the RumenFeed consumed by ruminants first passes through thelargest of the four stomach compartments or rumen,which acts like a fermentation vat. Countlessnumbers of bacteria, protozoa, and fungi in therumen ferment the feed releasing end products thatare utilized by the host animal for maintenance andgrowth of body tissues. The microbial population inthe rumen also is responsible for extensivetransformation of dietary lipid. Lipid transformationsinclude lipolysis to release free fatty acids fromcomplex plant lipids, and biohydrogenation toconvert unsaturated fatty acids in plant matter tomore saturated lipid end products. Lipids enteringthe rumen are first transformed by microbial lipasesin a process called lipolysis. The microbial lipaseshydrolyze the ester linkages in complex lipidscausing release of fatty acids and glycerol. Theglycerol produced is fermented yielding mostlyvolatile fatty acids.The main types of lipids enteringthe rumen are triglycerides, phospholipids, andgalactolipids from forages and concentrates in thediet. Rapid hydrolysis of triglycerides occurs bymicrobial enzymes. Linseed oil incubated withruminal contents of sheep at 1.0 g/100 ml resulted ingreater than 75% of the total lipid recovered in theform of free fatty acids. Phospholipids andgalactolipids also undergo rapid and extensivebreakdown in the rumen as a result of the enzymeactivity of ruminal microorganisms. Some evidence

suggests hydrolysis of triglycerides and galactolipidsfrom pasture grass was due primarily to plantenzyme activity. Dawson et al. (1977) autoclaved

14C-

labelled grass to inactivate plant lipolytic enzymes.The grass was then administered intraruminally to asheep and the galactolipids were rapidly hydrolyzed.Additionally, in an in vitro trial, grass washomogenized with rumen fluid taken from sheep thathad been given autoclaved grass for 7 d and the grassgalactolipids were rapidly hydrolyzed. It wasassumed that the ruminal contents and grass weredevoid of plant lipases. In the absence of plant lipasesthe grass galactolipids were rapidly hydrolyzed.Grass was also homogenized with boiled ruminalfluid. In the absence of microbial lipases thegalactolipids were not metabolized. Therefore, it wasconcluded that lipases produced by ruminalmicroorganisms are mainly responsible for thebreakdown of ingested plant lipids (Dawson et al.,1977).

The biohydrogenation of linoleic acid in the rumen(Figure 3) begins with its conversion to CLA. In thisinitial step, the number of double bonds remains thesame but one of the double bonds is shifted to a newposition by microbial enzymes. Normally, the doublebonds in linoleic acid are separated by two singlebonds, but in CLA, the double bonds are onlyseparated by one single bond. Many types of CLAare produced in the rumen of dairy cows (Baumanand Lock, 2006), but a common CLA produced frombiohydrogenation of linoleic acid is cis-9, trans-11C18:2.

As biohydrogenation progresses, double bonds in theCLA intermediates are then hydrogenated further totrans fatty acids having only one double bond. Trans

16

double bonds only differ from cis double bonds in theplacement of the hydrogens. The hydrogens arelocated on opposite sides of the double bond for transfatty acids, but on the same side of the double bondfor cis fatty acids. Although the difference in structurebetween trans and cis fatty acids appears small, itcauses significant differences in their physical andmetabolic properties. A final hydrogenation step bythe ruminal microbes eliminates the last double bondyielding stearic acid as the final end product. As aresult of biohydrogenation, there is extensive loss ofunsaturated fatty acids from the mouth to theduodenum of the animal.

In cows on a typical forage diet, the major trans C18:1present in ruminal contents is trans-11 C18:1. Most ofthe remaining isomers have double bonds distributedequally among carbons 12 through 16 (Bickerstaffe etal., 1972). The exact pathways for the production ofthese positional isomers are not known. Linoleic andlinolenic acids are converted to several trans C18:1and C18:2 intermediates during biohydrogenation.

Protection of Ruminal Fermentation Biohydrogenation can be argued as an evolutionaryadaptation of the microbial population in the rumenas a self-protection device against the toxic effects ofunsaturated fatty acids. Elevating fatty acidconcentration in ruminal contents may cause anumber of changes in ruminal fermentationcharacteristics and microbial population distribution.Ruminal changes are the result of the antimicrobialnature of unsaturated fatty acids, where fatty acidsadsorb onto the cell membrane of selected microbialspecies, and then penetrate into the membranecausing disorganization of phospholipids andeventual cytological damage (Jenkins, 2002). Becausesome bacterial species are more susceptible thanothers, the result is a microbial shift in the rumen.The fatty acid-induced microbial shift can disruptfermentation of carbohydrate digestion causing adrop in the acetate to propionate ratio and possibly areduction in fiber digestion (Jenkins, 2002).

Two factors that affect the antibacterial activity oflipids are fatty acid structure and concentration. Freefatty acids generally disrupt fermentation more thantriglycerides and antibacterial activity of free fattyacids can be enhanced by increasing the number ofdouble bonds (Chalupa et al., 1984). Growth of somebacterial species is stimulated by low concentrationsof fatty acids, but inhibited at higher concentrations(Maczulak et al., 1981). In attempting to predictruminal fermentation changes caused by dietarylipid, it is often assumed that the fat load iscontributed only by the fat supplement and that freefatty acid concentration is low. Both assumptions canbe wrong. Fatty acids from the grain and forage can

significantly contribute to total rumen fat load, forexample when animals are consuming immaturepasture. Also, free fatty acid concentration may beelevated in some feed ingredients such as wholecottonseed stored in warm, humid conditions (Cookeet al., 2007), or in forages resulting from hydrolyticcleavage of esterified lipids during hay-making (Yangand Fujita, 1997).

Fatty Acid Outflow from the Rumen and AnimalPerformance Meeting Essential Fatty Acid DemandsOmega fatty acids belong to one of three families, thew-9, w-6, or w-3 family. Each family has a parentfatty acid that is converted to other biologically-activeacids within the same omega family (Figure 4). Theonly parent fatty acid that can be made by bodytissues is oleic acid. The w-6 and w-3 parentcompounds (linoleic and linolenic acids) cannot besynthesized by body tissues and, therefore, must besupplied in the diet. Thus, linoleic and linolenic acidsare regarded as essential because they are requiredfor normal tissue function but cannot be synthesizedby body tissues.

A typical total mixed ration of grains and foragesgenerally contains adequate essential fatty acids tomeet the needs of the animal. However, the majorityof the dietary essential fatty acids are destroyed bymicroorganisms through biohydrogenation.

Part of the interest in omega fatty acids in dairy cattleis to enhance their concentration in milk for value-added opportunities, and part is to enhance theirconcentration in body tissues of the cow to enhanceproduction and health. Omega fatty acids in milk areincreased to improve manufacturing properties andto increase fatty acid nutraceuticals known toenhance human health. Increasing omega fatty acidsin tissues of the cow has potential benefits onreproductive performance, immunity and diseaseresistance, and positive hormonal shifts.

In a few studies, feeding fat to lactating dairy cowshas improved reproductive performance implyingpossible benefits on lifetime production potential.Reported improvements of reproductive performancefrom added fat include higher conception rates

17

(Schneider et al., 1988; Sklan et al., 1989), increasedpregnancy rates (Schneider et al., 1988; Sklan et al.,1991), and reduced open days (Sklan et al., 1991).However, supplemental fat has had little or nobenefit on reproductive efficiency in other studies(Carroll et al., 1990).

The mechanism of how fat supplements alterreproductive performance is not clear. Fat mayfunction in one capacity by providing additionalenergy during early lactation to support improvedproductive functions, including reproduction.Negative energy balance delays ovulation and theinitiation of the first normal luteal phase (Butler et al.,1981). However, recent studies also suggest that themechanism involves an energy independent responseto fat.

Immune SystemCLA decreased the growth rate in chicks and ratsafter they were injected with endotoxin(lipopolysaccharide; LPS). This probably was causedby release of cytokines and the prevention of thecatabolic effects (Cook et al., 1993). Miller et al. (1994)examined endotoxin-induced growth suppression inmice fed with 0.5 % fish oil and CLA. The fish oil fed-group lost twice as much body weight after theinoculation with endotoxin than the CLA-fed groups.These researchers found that the CLA in theendotoxin injection inhibited anorexia (a decreasedsensation of appetite) and increased splenocyteblastogenesis, concluding that it might inhibitarachidonic acid synthesis, thus preventing thecatabolism of tissue by removing eicosanoidprecursors. In addition, Bontempo et al. (2004)examined the effects of CLA on the immunologicalvariables of lactating sows and piglets fed with a 0.5% CLA diet. They found that CLA-fed sows exhibitedincreased colostrum IgG and serum leptin, and IgGand lysozyme. Nursing piglets of CLA-fed sows alsoexhibited higher levels of IgG and lysozyme. As theseresults show, dietary CLA enhanced the effect ofimmunological variables in lactating sows andpiglets.

Effect on Body Weight and FatPark et al. (1997) found that CLA contributed to areduction in body fat mass and an increase in leanbody mass. Mice fed a 0.5 % CLA augumented dietexhibited 57-60 % lower body fat and 5-14 %increased lean body mass than the controls. They alsofound that the total carnitine palmitoyltransferaseactivity was enhanced with dietary CLAsupplementation. Moreover, in cultured 3T3-L1adipocytes, CLA treatment reduced the intracellularheparin-releasable lipoprotein lipase activity andtriacylglyceride and glycerol concentration. Inaddition, DeLany et al. (1999) suggested that CLA

played a key role in reducing body fat content andincreasing protein accumulation in mice. In thisstudy, the diets of mice were supplemented withCLA (0.0, 0.25, 0.50, 0.75, and 1.0 % by weight). In the0.50, 0.75, and 1.0 % CLA feeding groups, body fatwas significantly lower than in the control, however,body energy was not depressed by any CLA dose. Asthese results suggested, dietary CLA reduces fatdeposition and increases lipolysis in adipocytes,coupled with enhanced fatty acid oxidation.

In a human trial, Blankson et al. (2000) conducted adouble blind study with 60 overweight or obesevolunteers (body mass index 25-35 kg/m2). The CLAdoses given varied from 1.7, 3.4, 5.1, or 6.8 g/day for12 weeks. The reduction of body fat mass wassignificant for the 3.4, 5.1, and 6.8 g CLA groups. Nosignificant differences in lean body mass, body massindex, blood safety variables or blood lipids wereobserved in the groups. Long-term supplementationof CLA studied by Gaullier et al. (2007) reduced bodyfat mass and increased lean body mass. Theyconducted a double blind placebo-controlled studywith 118 healthy, overweight, and obese adults. TheCLA dose was 3.4 g/day. During the six-monthperiod of study, the CLA significantly decreased thebody fat mass (-3.4 %) located primary in the legs.

Two families of transcription factors may be involvedin the intracellular signaling mechanisms of CLAaccording to Tsuboyama-Kasaoka et al., (2000);peroxisome proliferator activated receptors (PPAR)and sterol regulatory element binding-protein(SREBP). However, the mechanisms by which CLAalters lipid metabolism in the human body are stillunclear. Initially, CLA, especially trans-10 cis-12 CLA,enters the cell membrane through unknown transportmechanisms before being shuttled into variousregulatory compartments. Brown and Mclntosh(2003) suggested that subsequently three mechanismsin adipose tissue depressed the triglyceride. The firstesterified CLA into triglyceride-rich oil droplets. Thismechanism did not have much effect on theregulation as a whole, even increasing triglyceridestores. The second mechanism esterified CLA into themembrane-bound phospholipids bilayer, where itchanged the fluidity of the membranes associatedwith a signal transduction cascade. The lastmechanism modified the activity of a currentlyunidentified transcription factor (TFX), resulting inless regulation of PPAR and the depression oflipoprotein lipase, an acyl-CoA-binding protein, anadipocyte fatty acid binding protein, a glucosetransporter, and leptin. In addition, CLA reduced theacitivity of steroyl-CoA desaturase and acetyl-CoAcarboxylase by altering the activity of TFX. Byinhibiting these factors, CLA attenuated insulin-stimulated glucose uptake, malonyl-CoA synthesis,

18

and oleate synthesis, collectively decreasing de novofatty acid synthesis. CLA also inhibited theexpression of SREBP, by enhancing SREBP transcriptdecay as well as by inhibiting the proteolyticcleavage, releasing the activated nuclear SREBPfragment.

Milk Fat DepressionThe discovery of major events in rumen lipidmetabolism occurred decades ago, with very littlenew information available on the details of itsbiochemistry and regulation until the discovery of theanticarcinogenic properties of cis-9, trans-11 CLA.This discovery made it apparent that even minutequantities of biohydrogenation intermediates in therumen could have dramatic effects on health andmetabolism of both the host animal and the humansconsuming animal-food products. Eventually it wasdiscovered that a second CLA, namely the trans-10,cis-12 isomer, was closely associated with milk fatdepression (MFD). This led to the biohydrogenationtheory of MFD that suggested feeding managementwas linked to an abnormal ruminal fermentationcausing accumulation of the trans-10, cis-12 isomer.Feed ingredients containing appreciableconcentrations of fat often cause MFD, an effect thatcan be explained by the biohydrogenation theory ofMFD. Predicting when fat sources will lead to MFD iscomplex and is a function of total unsaturated fattyacid supply to the rumen, how fatty acid supply willimpact the pathways of lipid biohydrogenation andits interaction with other feed ingredients. Animproved understanding of these events will providethe critical framework with which to bettertroubleshoot MFD.

The ‘biohydrogenation theory’ represents a unifyingconcept to explain the basis for diet-induced MFDwhere unusual intermediates of ruminal fatty acidbiohydrogenation accumulate in the rumen andeventually reduce milk fat synthesis in the mammarygland. Under certain dietary situations the rumenenvironment is altered and a portion ofbiohydrogenation occurs via a pathway that producestrans-10, cis-12 CLA and trans-10 18:1 (Figure 5).Bifidobacterium, Propionibacterium, Lactococcus,Streptococcus, and Lactobacillus isolates from otherhabitats have been reported to produce trans-10, cis-12-CLA. As these genera occur in the rumen,although generally at rather low numbers, they maycontribute to biohydrogenation and specifically totrans-10, cis-12-CLA formation in the rumen.Propionibacterium, Streptococcus, and Lactobacillus arealso more numerous in the rumen with concentratediets (Jenkins et al., 2008), which would again beconsistent with greater trans-10, cis-12 CLAproduction with concentrate diets. Therefore, dietarysituations causing MFD alter the pathways of rumen

biohydrogenation resulting in changes in the specifictrans-18:1 and CLA isomers available for uptake bythe mammary gland and incorporation into milk fat.

As shown in Figure 5, this ‘trans-10 shift’ inbiohydrogenation pathways, and the associatedincrease in the trans-10 18:1 content of milk fat, isindicative of the complex changes in ruminalbiohydrogenation pathways characteristic of MFD.Although trans-10 18:1 does not directly inhibitmammary synthesis of milk fat (Lock et al., 2007), it isrelatively easy to analyze compared to trans 10, cis-12CLA and other CLA isomers. Therefore, in general,this fatty acid can serve as a marker for the type ofalterations in rumen biohydrogenation thatcharacterize diet-induced MFD.

ReferencesBauchart, D., R. Verite, and B. Remond. 1984. Long-chainfatty acid digestion in lactating cows fed fresh grass fromspring to autumn. Can. J. Anim. Sci. 64:330-331.

Bauman, D. E. and A. L. Lock. 2006. Concepts in lipiddigestion and metabolism in dairy cows. Proc. Tri-StateDairy Nutr. Conf. pp. 1-14. Available at:http://tristatedairy.osu.edu/

Blankson, H., J. A. Stakkestad, H. Fagertun, E. Thom, J.Wadstein, and O. Gudmundsen. 2000. Conjugated linoleicacid reduces body fat mass in overweight and obesehumans. J. Nutr. 130:2943-2948.

Bontempo, V., D. Sciannimanico, G. Pastorelli, R. Rossi, F.Rosi, and C. Corino. 2004. Dietary conjugated linoleic acidpositively affects immunologic variables in lactating sowsand piglets. J. Nutr. 134:817-824.

Brown, J. M., and M. K. Mclntosh. 2003. Conjugated linoleicacid in humans: regulation of adiposity and insulinsensitivity. J. Nutr. 133:3041-3046.

Butler, W. R., R. W. Everett and C. E. Coppock. 1981. Therelationships between energy balance, milk production andovulation in postpartum Holstein cows. J. Anim. Sci. 53:742.

Carroll, D. J., M. J. Jerred, R. R. Grummer, D. K. Combs, R.A. Pierson and E. R. Hauser. 1990. Effects of fatsupplementation and immature alfalfa to concentrate ratioon plasma progesterone, energy balance, and reproductivetraits of dairy cattle. J. Dairy Sci. 73:2855.

19

Chalupa, W., B. Rickabaugh, D. S. Kronfeld, and D. Sklan.1984. Rumen fermentation in vitro as influenced by longchain fatty J. Dairy Sci. 67:1439-1444.

Cook, M. E., C. C. Miller, Y. Park, and M. Pariza. 1993.Immune modulation by altered nutrient metabolism:nutritional control of immune-induced growth depression.Poult. Sci. 72:1301-1305.

Cooke, K. M., J. K. Bernard, C. D. Wildman, J. W. West, andA. H. Parks. 2007. Performance and ruminal fermentation ofdairy cows fed whole cottonseed with elevatedconcentrations of free fatty acids in the oil. J. Dairy Sci.90:2329-2334.

Dawson, R. M. C., N. Hemington, and G. P. Hazlewood.1977. On the role of higher plant and microbial lipases in theruminal hydrolysis of grass lipids. Br. J. Nutr. 38:225-232.

DeLany, J. P., F. Blohm, A. A. Truett, J. A. Scimeca, and D. B.West. 1999. Conjugated linoleic acid rapidly reduces bodyfat content in mice without affecting energy intake. Am. J.Physiol. 276:R1171-1179.

Gaullier, J. M., J. Halse, H. O. Høivik, K. Høye, C.Syvertsen, M. Nurminiemi, C. Hassfeld, A. Einerhand, M.O’shea, and O. Gudmundsen. 2007. Six monthssupplementation with conjugated linoleic acid inducesregional-specific fat mass decreases in overweight andobese. Brit. J. Nutr. 97:550-560.

Hatfied, R., H. G. Jung, G. Broderick, and T. C.Jenkins.2007. Nutritional chemistry of forages. In Forages, Volume 2.The Science of Grassland Agriculture, Sixth Edition. R. F.Barnes (Ed.), Blackwell Publishing, Iowa State Press, Ames.

Jenkins, T. C. 2002. Lipid transformations by the rumenmicrobial ecosystem and their impact on fermentativecapacity. pp 103-117 in Gastrointestinal Microbiology inAnimals, S. A. Martin (Ed.), Research Signpost, Kerala,India.

Jenkins, T. C., and W. C. Bridges, Jr. 2007. Protection of fattyacids against ruminal biohydrogenation in cattle. Eur. J.Lipid Sci. Technol. 109:778-789.

Jenkins, T. C., R. J. Wallace, P. J. Moate, and E. E. Mosley.2008. Board-invited review: Recent advances inbiohydrogenation of unsaturated fatty acids within therumen microbial ecosystem. J. Anim. Sci. 86:397-412.

Kellens, M. J., H. L. Goderis, and P. P. Tobback. 1986.Biohydrogenation of unsaturated fatty acids by a mixedculture of rumen microorganisms. Biotechnol. Bioeng.28:1268-1276.

Lock, A. L., C. Tyburczy, D. A. Dwyer, K. J. Harvatine, F.Destaillats, Z. Mouloungui, L. Candy, and D. E. Bauman.2007. Trans-10 octadecenoic acid does not reduce milk fatsynthesis in dairy cows. J. Nutr. 137:71-76.

Maczulak, A. E., B. A. Dehority, and D. L. Palmquist. 1981.Effects of long chain fatty acids on growth of bacteria. Appl.Environ. Microbiol. 42:856-861.

Miller, C. C., Y. Park, M. W. Pariza, and M. E. Cook. 1994.Feeding conjugated linoleic acid to animals partiallyovercomes catabolic responses due to endotoxin injection.Biochem. Ciophys. Res. Commun. 198:1107-1112.

Park, Y., K. J. Albright, W. Liu, J. M. Storkson, M. E. Cook,M. W. Pariza. 1997. Effect of conjugated linoleic acid onbody composition in mice. Lipids. 32:853-858.

Freeman-Pounders, S. J., D. W. Hancock, J. A. Bertrand, T.C. Jenkins, and B. W. Pinkerton. 2009. The fatty acid profileof rye and annual ryegrass pasture changes during theirgrowth cycle. Forage and Grazinglands 30 January, 2009.

Schneider, P., D. Sklan, W. Chalupa, and D. S. Kronfeld.1988. Feeding calcium salts of fatty acids to lactating cows.J. Dairy Sci. 71: 2143-2150.

Sklan, D., E. Bogin, Y. Avidar and S. Gur-Arie. 1989.Feeding calcium soaps of fatty acids to lactating cows:effect on production, body condition and blood lipids. J.Dairy Res. 56:675-682.

Sklan, D., U. Moallem and Y. Folman. 1991. Effect offeeding calcium soaps of fatty acids on production andreproduction responses in high producing lactating cows. J.Dairy Sci. 74:510-517.

Tsuboyama-Kasaoka, N., M. Takahashi, K. Tanemura, H. J.Kim, T. Tange, H. Okuyama, M. Kasai, S. Ikemoto, and O.Ezaki. 2000. Conjugated linoleic acid supplementationreduces adipose tissue by apoptosis and developslipodystrophy in mice. Diabetes. 49:1534-1542.

Yang, U. M., and H. Fujita. 1997. Changes in grass lipidfractions and fatty acid composition attributed to haymaking. Grassl. Sci. 42:289-293.

20

21

The Compatibility Between DairyProductivity and Carbon Footprint

Jude CapperWashington State University

22

23

24

25

26

When reviewing the 2009 dairy industry andeconomics, no one could imagine the steep drop inmilk prices at the farm gate (over 40 percent), thequickness of the drop in milk prices (less than onemonth), and the length of time (10 months belowbreakeven milk prices). Another change wasMidwest states had higher milk increases varyingfrom four to six percent in 2009 on the same numberof cows while many other states reported less milkwith fewer cows. What may have happened inIllinois and the Midwest allows us to look back tolook ahead and prepare for the next milk pricechallenge which started in February, 2010. Dairymanagers will need to plan for variable shifts in milkprices, feed prices, and profit margins.

Making Correct and Incorrect ManagementDecisionsThirty two dairy nutritionists, nine veterinarians, andten educators responded to a field survey to the listthe three best or correct decisions dairy managersmade in 2009 and the three incorrect changes made in2009 in ranked order. The top ranked item wasassigned three points, the second ranked item wasassigned two points, and third ranked decision wasassigned one point. Table 1 summarizes positive orcorrect decisions by each group. The survey pointsout the role of forage quality, level, and type (cornsilage specifically) and keep focused on correctdecision with $12 or $20 per one hundred pounds ofmilk. Other interesting correct points includedmaintaining high morale and positive attitude withfamily members and hired labor, feed contracting,amino acid balancing reduced protein purchases,grouping cows, and bringing heifers back to the farmto reduce costs. Table 2 summarizes negative orincorrect dairy manager decisions by each group inthe survey. The main concern was reducing orremoving feed intake, nutrients, minerals, vitamins,and/or additives. Other interesting points were notentering the CWT program, lame and broken cows,major expansions in 2007 and 2008, and not usingprofessionals (AI technicians, calf and heifer growers,hoof trimmer, and/or veterinarians).

Providing Economic FlexibilityIllinois dairy managers can have several advantagescompared to other dairy managers facing the 2009low milk prices with high feed prices.

• Illinois dairy producers had ample supplies offorages and corn produced on their farms whichdid not have to be purchased in 2009. Thisadvantage reflects the agronomic skills of Illinoisdairy producers, but they did not capture highermarket prices and income if they sold feed. Thisstrategy avoided out-of-pocket costs whichbankers encouraged/demanded of dairymanagers.

• Illinois producers did not expand and/or paiddown debt. Bank and interest payment could beminimized. Stable land prices allowed credit tobe extended compared to dairy cow equity thatdeclined 25 to 50 percent.

• Illinois dairy farms (average herd size of 106cows) use family labor as a resource. Dairy farmfamilies did not draw $50,000 (Minnesotaguideline for a dairy farm family with twochildren) in the short term.

• Because the average Illinois herd size is fewerthan 150 cows, dairy farm managers couldqualify for the MILC program providing $1 to $2per cwt month added income. A rBST paymentfor not using this technology resulted in forty tosixty cents per cwt added income. One Illinoiscooperative provided one dollar advancedpatronage per cwt payment for several months toassist financially stressed dairy farms.

Making Correct DecisionsAn important decision was not to make shortdecisions to save a nickel while leading to a longterm loss of a dollar (“staying the course”). Examplesof potential decisions and choices are outlined below.

• Reducing or removing minerals and vitamins cansave six cents (heifers) and twenty cents (lactatingcows) a day. Because minerals do notimmediately reduce milk yield, dairy managersreasoned this may be a prudent move. However,when mineral deficiencies occur six months later(reduce immunity, slower growth, and decliningfertility), it resulted in large negative economicimpacts which may be difficult to pinpoint andrecover later in lactation or growth phases.

27

Feeding Economics For 2010 Michael Hutjens

University of Illinois232 Animal Sciences Lab

1207 West Gregory Drive, Urbana, ILhutjensm@illinois.edu

• Holstein heifers must gain over 1.7 pounds perday if they are expected to calve at 23 to 24months of age, weigh 1250 pounds after calving,and produce lactations yields above herdaverage. The cost of delayed calving is $2 perday (reflects only added feed costs).

• An increase in somatic cell count due to reducedimmunity and health (removal of organic traceminerals, less vitamin E, and/or energy shortagefor example) will lead to a loss of 2 to 2 1/2pounds per cow per day due to a change in onelinear somatic cell count score.

• An increase in days open will cost $2 per day(each day over 120 days open) to $8 per day (eachday over 180 days open) based on Wisconsin datawhich could be related to negative energybalance due to removal of fat or effective feedadditives.

• Dropping an accelerated calf feeding programcan reduce milk yield in the first lactation by 1100pounds due it impact on mammary glanddevelopment. This decision is a long terminvestment of $30 to $50 added feed costs notrecovered for nearly two years in higher milkyield based on IL and NY data.

• Feed additives must be purchased (an out-of-pocket cost) which can lead to removingadditives than return 3 to 10 times the cost of thefeed additive (for example a buffer returns 30cents in added milk production for a six centinvestment). The feed additives listed areranked: 1st choice – monensin (an ionophore);2nd choice – yeast-based products; 3rd choice –silage inoculants; 4th choice – organic traceminerals; 5th choice – rumen buffers; and 6th

choice – biotin.

• Shifting from a one group TMR to multiple TMRsmay be an alternative to lower feed costs.Feeding a ration higher in forages to lowerproducing cows can save 40 to 75 cents or moreper day. Consider low producing cows mayconsume 4 to 6 pounds less dry matter which canreduce the estimated savings. High producingcows may need more nutrients to replace lostbody weight in late lactation. Heifers may needadded nutrients to grow reaching their matureweight. Another economic consideration is if theone group TMR contains expensive nutrientsources (such as inert fat, amino acids, addedfat/oil, or high quality RUP protein sources).Recent research from Michigan State Universitysuggest metabolic reasons for grouping cows(high group cows requiring more glucose, more

dry matter intake, has lower insulin sensitivity,and higher levels of natural BST compared to lowproducing cows).

Monitoring Feed Changes From Cow ResponsesWhen dairy managers make changes, lactating cowswill respond (cows “talk” to you). Monitor thefollowing cow measurements to determine if yourchange led to lost income or health.

• MUN (target 8 to 14 mg /dl to avoid nitrogenlose while maintaining milk protein levels)

• Milk protein and milk fat test (meet or exceedbreed averages)

• Management level milk or 150 day milk (shouldincrease or maintain herd values)

• Fecal scores (range from 2.5 to 3.5)

• Changes in feed benchmarks

•• Herd feed efficiency from 1.5 to 1.7 pounds of3.5% milk per pound of dry matter with eachchange in 0.1 point worth 25 to 35 cents percow per day.

•• Feed cost per pound of dry matter at 9 to 10 centsper pound of dry matter reflects the cost of feedingredients selected when building andbalancing the ration.

•• Feed cost per cwt ($5 to $6 per cwt) reflects thecost per pound of dry matter, amount of drymatter offered including weigh backs, and milkyield. Milk yield is the key factor.

•• Income over feed costs represents margin (dollarsavailable) for fix, variable, labor, and return tomanagement. Milk price is a key factor in thisvalue.

Feeding Strategies That Worked• Forage quality is a key solution. Consider

increasing corn silage levels in rations as feedcost per cow per day may drop 15 to 30 cents.Evaluate the use of low lignin forages andforages high in NDFD (neutral detergent fiberdigestibility).

• Use of computer modeling programs allows forfine-tuning rations. Lower levels of protein basedon amino acid balancing and rumen microbialestimation can be reduce feed costs whileoptimizing production.

• Determine if starch levels and utilization areoptimal. Lower levels of starch (20 to 22 percent)can maintain milk production with high quality

28

forage, rumen fermentable fiber, adding sugar,and/or feeding an ionophore. Plant or kernelprocessing of corn silage and processing corngrain can increase starch availability in the rumenand reduce fecal losses of starch. If fecal starch isover 5 to 7 percent, examine sources andprocessing reducing starch utilization.

• By-product feeds can be an economical nutrientsource. Distillers grain and wet brewers graincan reduce protein costs while corn gluten feed,soy hulls, and wheat midds can maintain energylevels while reducing feed costs (Table 3).

• Review shrink losses. Managing and monitoringweigh backs can increase profitability. Oneguideline is to target 1 to 2 percent weigh backper cow per day. Bunk management may allowfeeding to an empty bunk reducing feed refusalssaving 1 to 3 pounds of dry matter per cow perday (9 to 27 cents a day).

Table 1. Summary of field responses to correct dairymanagement decisions made with low milk prices in2009.

Decision Nutritionists Veterinarians Educator Total PointsForage program aspects 42 4 19 65Staying the course 36 4 16 56Ration balancing/nutrients 29 8 12 49Strategic culling 25 6 0 31Milk components and quality 14 5 4 23Financial adjustments 11 0 3 14Use of by-product feeds 10 0 0 10Labor management 5 4 0 9Use of rBST 2 6 0 8Contracting milk 0 4 0 4

Table 2 Summary of field responses to incorrect dairymanagement decisions made with low milk prices in2009.

Decision Nutritionists Veterinarians Educator Total PointsRemoving feed 41 14 11 66Pulling min, vit, and additives29 5 9 43Not staying the course 16 3 1 20Low forage quality 7 8 4 19Avoiding financial support 7 2 9 18Reduce hoof care 12 2 1 15Poor cow comfort 10 3 0 13Reduced rBST use 3 4 4 10Overfeeding of distillers grain 3 0 6 9Reducing health 4 3 0 7Incorrect culling decisions 2 0 4 6Not using records 3 0 3 6

Table 3. Breakeven prices for selected by-productfeeds using Feed Val 3 and Sesame withrecommended levels in lactating cow rations. Feedprices used to calculate breakeven prices withFeedVal3 were soybean meal at $350 a ton, shelledcorn at $3.50 a bushel, tallow at 30 cents a pound,dicalcium phosphate at $25 per cwt, and limestone at$10 per cwt. Sesame calculations were based on 30reference feeds on April 22, 2010.

By-product Breakeven price Level Feed Val 3 Sesame (% ration DM)

———- ($ per ton) ———Soy hulls 109 85 10 Cottonseed, fuzzy 230 236 10Corn gluten feed 140 165 10 to 25Brewers grain (30% DM) 66 na 15 to 20Corn hominy 140 185 10 to 20Corn distillers grain 252 207 10 (> 10% oil)

20 (< 10% oil)

29

30

4-State Dairy Nutrition &Management Conference

31

32

Coordination of Reproductive and NutritionalManagement of Lactating Dairy Cows

Bill ThatcherUniversity of Florida

33

34

35

36

37

38

Demystifying the EnvironmentalSustainability of Food Production

Jude CapperWashington State University

39

40

41

42

IntroductionThe transition period, which extends fromapproximately 3 weeks prior to calving untilapproximately 3 weeks post-calving, is a high-risktime in a cow’s life and proper management of thisperiod is critical to the success of any dairy. Duringthis time, cows experience many physiological andmetabolic changes and must successfully adapt to thechanging demands. There is a large increase innutrient requirements that cannot be met throughreliance on dry matter intake and thus, cows mustmobilize body tissue to meet the energy and proteindemands. During late gestation, the fetus is growingrapidly and the cow begins producing colostrum. Asa consequence, there is a large increase in the amountof glucose and amino acids that she needs to producein order to meet the demands for energy and growthof the fetus and for the production of colostrum.Despite these increasing needs, feed intake declinesduring the last 7-14 days prior to calving. Cowsexperience large changes in hormone levels includingincreases in estradiol, growth hormone, cortisol,adrenaline, endorphins, and oxytocin and decreases inprogesterone. There is also a large increase in thedemand for calcium, first for colostrum and then forlactation. With the onset of lactation followingparturition, glucose and amino acid demands increaseby approximately 3-fold as compared to the alreadyhigh demands of the previously gravid uterus.

In order the meet the energy needs of this transitionperiod, cattle shift the ways in which their bodies useglucose (essentially “sparing” glucose for themammary gland and fetus at the sacrifice of otherbody tissues such as muscle) via changes in insulinsensitivity and increases in growth hormone levels.These other tissues derive their energy frommobilized fatty acids. If a successful transition andadaptation to the changing demands is made, cowswill experience mild increases in the levels of non-esterified fatty acids during the last 10 days ofgestation that carry over into early lactation. Cowsthat successfully transition into lactation will notexperience appreciable hyperketonemia prior tocalving, although the levels of ‚-hydroxybutyrate willmoderately increase in early lactation but generallyremain less than 1,000 Ìmol/L. However, if cows fail

to successfully manage the demands of the transitionperiod, excessive mobilization of fatty acids fromtheir body stores will occur leading to a fatty liver,poor immune response, poor glucose production,hyperketonemia above 1,400 Ìmol/L, increased riskof disease, increased risk of premature culling, anddecreased reproductive performance.

Key components of successful transition include: 1)the implementation of herd management approachesthat focus on prevention of periparturient problems,optimization of feed intake, and the removal ofstressors, 2) real time monitoring of key processesthat impact the risk of periparturient diseaseproblems, and 3) finally, the monitoring of success orfailure in key outcomes of interest. Each of thesecomponents will be discussed in part in theremainder of the paper. When proper preventativemanagement is combined with real-time monitoring,the result should be an improved transition programand increased lactation and reproductive success.

Management KeysGrouping, Housing and Pen MovementThe goal of proper grouping is to reduce the social,environmental, and metabolic stressors on apopulation of cows by minimizing the number of penchanges a cow is forced to make while also workingto fit the management needs of the dairy. Strive toavoid unnecessary pen changes, as each pen move islikely to result in a drop in DMI and elevated cortisollevels – both of which may negatively impactimmune function and overall health and productivity.When pen moves are necessary, decrease the impactof pen changes by moving animals once weekly andmove in groups of 10 or more animals, if possible.Avoid moving cows into new pens during the last 10d prior to calving. Ideally, cows should spend at least14 d in the close-up pen.

• Due to the inevitable variation around calvingdates, strive to have at least 90 % of cows spend atleast 10 d in close-up pens by modifying the movedates for cows going from the far-dry to the close-up pens. Change the move dates during summerheat stress and for cows carrying twins as each ofthese conditions usually result in a gestationlength that is 5-7 d shorter than expected.

43

The Use of Records to Evaluate andImprove Transition Cow Performance

M. W. Overton DVM, MPVM, and I. J. Smith, DVMUniversity of Georgia, College of Veterinary Medicine

Department of Population HealthRhodes Center - ADS

425 River Road, Athens, GA 30602-2771moverton@uga.edu

• Separate heifers and older cows, if possible, sinceheifers have been shown to have longer restingtimes and higher DMI when separated frommature cows.

•• Some researchers feel that heifers need higherlevels of protein during the close-up period ( > 15 % CP or 1100 - 1200 g of metabolizableprotein) as compared to mature dry cows.

•• Feeding dietary cation-anion difference(DCAD) diets to springing heifers is not usuallyrequired, since they are not as susceptible toclinical hypocalcemia and are less affected bysubclinical hypocalcemia than mature cows; butsome herds report improved performance withDCAD diets for heifers.

• Maintain the stocking density at less than 100 %,based on both feed bunk space and resting area.

•• Provide ~ 30 in of bunk space per animal or, inpens with lock-ups spaced at 24 in, populatethe pen at 80 - 85 % of the number of lock-ups.To avoid confusion, instead of relying on acount of lock-ups, strive to always provide 30to 36 in of feed bunk access per cow in theclose-up and fresh cow pens.

•• Maintain a clean, dry environment withadequate areas for animals to rest. Mud andheat stress increase metabolic needs, butdecrease feed intake. Wet, mucky conditionsalso increase the risk of mastitis that may notappear until later in the fresh pen. Cowscalving in wet conditions may experiencehigher risks of metritis. If using maternity pens,these areas should be bedded with clean, drymaterial and changed frequently. Thefrequency of rebedding will depend on avariety of issues such as stocking density,bedding type, weather conditions, etc. Strivingto maintain a clean, dry area results in cowsmaintaining good hygiene scores.

• Following calving, cows should be housed in acolostrum pen, instead of a hospital pen, iffeasible, until milk is free of dry cow antibioticresidues and legal for sale. If this additional pen isnot possible, strive to understock the hospital pen,both in terms of feed bunk space and resting area.

• Minimize distance walked in these tired and sorefresh cows by placing the pre- and post-freshpens close to the parlor, if possible. Ideally, theclose-up pens should be located close enough toallow frequent observation, but not in the midstof noisy, high traffic areas that might stress thecows and interfere with feeding or calving.

Nutrition and Feed DeliveryThe primary feeding management goals during theperiparturient period is to minimize the inevitabledrop in DMI that occurs prior to calving, meet theenergy and amino acid demands without overfeedingenergy, and to maximize the rise in intakepostpartum. Feed intake, energy balance, and themagnitude of change during the periparturientperiod are associated with changes in immunefunction, risk of developing retained placenta andmetritis, and postpartum feed intake.

• Energy and protein requirements during the lastweek of gestation are estimated to beapproximately 15 Mcals NEL and 1100 g ofmetabolizable protein/d, respectively. It isbeyond the scope of this paper to adequatelydescribe the various strategies and guidelines forbalancing rations, but there are a few basicsworth mentioning:

•• Ensure an adequate level of fiber intake byfeeding 7 to 7.5 lb of forage ADF. Make surecows are actually consuming the rationprovided by using a Penn State ParticleSeparator to evaluate both the fresh feed andthe refusals.

•• Increase metabolizable protein toapproximately 1100 g/d (corresponds to apositive balance of 400 to 450 g ofmetabolizable protein in some ration balancingprograms)

•• Be careful with fermentable carbohydrate levels– keep total NFC to less than 30 to 32 % andstarch at approximately 14 - 18 %.

• If using DCAD diets for close-up cows, selectforages, grains, and grain by-products that arelow in potassium to minimize the amount ofanionic salts needed.

• Feed additional vitamin E to close-up and freshcows. Vitamin E has been shown to improveimmune function and decrease the risk ofretained placenta, metritis, and mastitis in freshcows. Specific levels to feed depend upon type ofdiet and feed ingredients but many consultantsrecommend levels of 1800 to 3000 IU/d in thesehigh risk cows.

• Energy and protein requirements during earlylactation change dramatically as milk productionincreases. After the prescribed withdrawal time,move cows from the colostrum pen to a fresh cowpen for ~ 10 to 21 d. Duration of time in freshpen is dependent upon preferred feedingstrategy, ability to feed a special fresh cow ration,

44

and calving pressure. Once again, it is beyondthe scope of this paper to adequately describe thevarious strategies and guidelines for balancingrations, but there are a few basics depending onthe management/ feeding option chosen:

•• Option 1 – short duration in fresh pen (10 to 14d) with more aggressive protein feedingfollowed by move to normal high cow ration at10 to 14 d in milk.

• Ensure an adequate level of fiber intake byfeeding approximately 7 lb of forage ADFwith total NDF levels at approximately 32 %.

• Increase metabolizable protein balance to apositive 500 to 600 g.

• Maintain correct blend of carbohydrates todrive propionate production, but keep totalNFC at 35 to 38 %. (Note, some programswill report a higher level of NFC on the samediet as compared to other ration balancingprograms. Check on the suggestedrequirements for the program you are using,but in general, most feed a slightly lowerlevel of NFC to these postpartum cows andthen increase the level as they move along inlactation.)

•• Option 2 – move cows onto regular high cowration.

• Ensure an adequate level of fiber intake byfeeding 7 to 7.5 lb of forage ADF with totalNDF levels at approximately 30 to 33 %.

• Shoot for metabolizable protein balance ofpositive 250 to 400 g through first 100 d inmilk (DIM).

• Feed a balanced carbohydrate blend ofapproximately 23-25 % starch, 4.5 to 5.5 %sugars, and 9.5 to 11 % soluble fiber.

• (Note: Ration balancing programs mayestimate and report specific rationcomponents differently. The aforementionedcomments are meant as general guidelines,but may not be directly comparable acrossdifferent programs.)

•• In both scenarios, the goal is to ensure anadequate level of fiber intake to maintainrumen health while still providing the propermix of fermentable substrate and nitrogenoussources (protein) to increase microbial numbersand propionate, the driver behind glucose/

lactose production and subsequently, milkproduction.

• Fat cows (≥ 4.0 BCS) are at increased risk ofketosis and often benefit from oral drenching.Consider 8 to 10 oz propylene glycoldrench/cow/d at calving and again in 24 hr.

• General feeding principles:

•• Ensure uniform feed intake by all animals.

•• Monitor particle size using a particle separator.

•• Maintain a moisture content of the rationbetween 50 - 60% to help reduce sorting andincrease palatability (may need to add water tosome rations).

•• Monitor manure for fiber length, grain particles,gas bubbles and consistency across cows withina pen.

•• Pre-batch mix/ chop hays to control length toapproximately 2-3 in (i.e., less than the width ofa cow’s muzzle) in order to reduce sorting.

•• Use high quality, highly palatable hays free ofmold and mycotoxins.

•• Use high quality, highly palatable silages free ofclostridial or butyric acid fermentationproblems and mycotoxins. Do not feed silagefrom top and sides of the silo to transitionanimals. In general, limit silages to no morethan ~ 40 to 50 % of forage needs in pre-freshcows if possible.

•• Clean out feed bunks daily for both close-upand fresh cows to minimize risk of feed intakedepression from moldy or heated feeds.

Facilities and Cow ComfortGood cow comfort to promote more lying time

and to minimize additional metabolic needsassociated with excessive standing and or walking iscritical, especially in fresh cows since these animalsare at an increased risk of lameness/ laminitis due tothe influence of periparturient hormonal changes thatmay negatively impact foot and leg tissues and dueto pen, ration, and feed intake changes.

•• Cows need sufficient space for resting in aclean, dry area. This need can be accomplishedusing well-designed free stalls, dry lots, beddedpacks or in other ways.

•• Space requirements:~ 100 sq ft/ cow in bedded packs;

45

~ 500 to 600 sq ft/ cow of loafing area and 50-75 sq ft shade area/ cow in open corrals; or

•• A minimum of 1 properly bedded andmaintained freestall/cow, if using freestallhousing, is important.

•• Heat stress abatement is critical in both pre-fresh and fresh cows. Provide soaker lines onlock-ups during heat stress conditions thatcycle once every 15 min from 70 to 79 °F, onceevery 10 min from 80 to 88 °F, and once every 5min above 88 °F with 0.33 gal ofwater/cow/cycle.

•• Water is a critical nutrient and should not beoverlooked. Strive to provide a minimum oftwo locations per pen and a minimum of 3linear in. per cow.

•• Acclimate heifers to lock-ups/stanchions andconcrete feeding aprons, if possible, prior toentering the close-up pen.

Monitoring—Real Time and Other General ItemsMonitoring is the regular observation and recordingof activities, events and yields that occur for thepurposes of observing and evaluating the degree ofchange, intended or unintended, positive or negative,within a system. It should include a systematicapproach to data collection, evaluation, and provisionof feedback about the changes detected. Theobjectives of monitoring include: 1) to recognize“normal” performance, 2) to test the impact ofintentional change in some area of management orperformance, 3) to discover unintended drifts ordeclines in procedures or performance, and 4) todetermine potential causes of abnormal performance.However, before getting into specific monitors, reportsor interpretation, there are some general concepts,concerns and terminology that must be considered.

Goals are target levels of performance toward whichproducers are trying to achieve and are typicallyrelated to profitability. For instance, a farm mighthave a goal of higher milk production, betterreproductive performance, or lower somatic cellcounts. Metrics are any type of measurement or setof measurements that quantify results and are used togauge some quantifiable component of dairyperformance, i.e., “Is the herd meeting its goals?”.Metrics that are monitored in dairy production aretypically numbers that represent some type ofprocess and are always important in achieving a goal,but are not synonymous with the goal themselves.Goals are great to establish for herds, but it is rarely agood idea to use the goal itself as a monitor. Anexample might be the average age-at-freshening of

replacement heifers. If the average age has been 27months, it might be a good goal to lower this age bya few months. Age-at-freshening is an appropriategoal, but a horrible monitor since it is the result ofmany processes that are involved in achievement ofthe goal such as appropriate feeding, housing,vaccination, breeding, etc.

The process of monitoring involves the routine andsystematic collection and evaluation of information(monitoring parameters) from a dairy in an attemptto detect change in the process. In order to do this, itis critical to monitor as close to the process(es) aspossible, as opposed to simply measuring theoutcome. Close-up urine pH, stocking density andfeed intake are often some of the best predictors offuture fresh cow problems and can be monitored on adaily basis. These specific “real-time” monitors willbe discussed below as well as other general itemsthat can be used to evaluate transition performance.

• Monitoring feed intake is one of the simplestmonitors of change in performance (andpredictors of future performance), but yet is mostoften overlooked.

•• Feed intake should be weighed daily, both theamount of fresh feed delivered and the amountleftover, as both a monitor and predictor offresh cow performance.

• Target a 5 % refusal (or more) on a daily basisand ensure that the ration is not easilysortable by grinding hays to 2 – 3 in. andadding water if necessary.

• Based on a typical 21 to 24/d average forcows in the close-up pen, strive to achieve aDMI of at least 26 lb for mature Holsteinsand at least 23 lb for Holstein heifers whenthese animals are housed in separate pens.

• In fresh pens that range from 2 – 21 DIM,strive to achieve at least 35 lbs of DMI forfirst lactation Holsteins and at least 43 lbs ofDMI for mature Holsteins. In mixed parityfresh pens, DMI should be at least 38 lb forHolsteins.

• If using DCAD diets for close-up cows, urinepH’s should be closely monitored.

•• Monitor urine pH once weekly from 10 to 15 cowswhile feeding a DCAD diet or more frequently iffeed ingredients change. In general, cows must beon the new diet for at least 48 hrs in order toaccurately assess the DCAD balance using urinepH. The goal is to have all cows at a pH of 6.0 to6.9. Many people monitor the average pH, but the

46

average can be very misleading, especially insituations where cows are sorting the ration andsome animals have a high pH while others are toolow. Overacidification (urine pH < 5.8) may resultin depressed DMI and perhaps compromisedimmune function; while inadequate acidification(urine pH > 7.2) can lead to severe, non-responsivedowner animals following calving. Eitherscenario can also result in an increase in retainedplacentas.

• All lactating cows are expected to lose someweight post-calving. Normal weight loss duringthe first 30 DIM should be < 0.75 BCS or ~90 lb (1BCS ~ 120 lb of fat and protein). If possible,monitor BCS for close-up and just fresh cows andthen again at approximately 2 months oflactation.

•• First service conception risk may be reduced by50 % when BCS decreases by more than 1.0 BCSduring the first 60 DIM and the risk of aprolonged anovulatory condition (failure tocycle) increases in animals whose BCS fallsbelow 2.75 or who lose excessive conditionduring the early postparturient period.

• Use some form of a fresh cow monitoring andtreatment program custom designed with yourveterinarian to fit your farm’s needs.

•• No one program fits all herds, but most herdsbenefit from some sort of evaluation program toassess appetite, attitude, and appearance ofevery cow in the fresh pen every day.Depending on the amount of labor available, aswell as the quality of the labor, some herdsneed a rigorous fresh cow monitoring programto prevent cows from falling through thecracks. If some form of a 10-d monitoringprogram is utilized, careful attention should bepaid to ensure that fresh cows are not locked upfor more than 30 to 45 min/d.

•• Other herds that have very high qualityherdsmen and fewer fresh cow issues mayactually perform better with a promptedassessment approach instead of individuallyexamining every fresh cow every day for thefirst 10 d of lactation.

• Many herd owners and consultants like tomonitor fresh cow culling risk (sold and died areoften calculated separately) during the first 30and 60 days in lactation and to use this as ametric for evaluating transition cowmanagement. However, this approach is fraughtwith issues and in most cases, probably shouldnot be used. First, most herds do not calve

enough cows to get an accurate assessment of thetrue point estimate of culling risk. Second,culling risk in early lactation should not becompared between herds due to the impact ofother management issues or differentphilosophies regarding the culling of animals inearly lactation. For example, one herd may havesevere reproductive challenges and must keep asmany animals as possible simply to keep herdnumbers up. Another herd may have goodreproductive performance, an abundance of freshheifers, and a greater ability to cull poor-doers.This better managed herd may even sell animalsto another dairy for milking replacements, yet the“apparent culling risk” would be much higherthan the first herd. Also, some herds tend to playgames to make this number look good by waitinguntil the next 30 d window to cull poor doinganimals. Thus, the use of early lactation culling isconfounded by potentially unknown herdmanagement issues, highly subject to sample sizeconstraints, and really has very little utilitywithin the area of transition monitoring.

• Instead of using culling evaluations, herds shouldstrive to develop better disease treatment andmonitoring protocols. If a subset of animals isaffected severely enough to require culling, thereare also likely negative effects on the remainingpopulation of survivors that will adverselyimpact production and reproduction. Having asystem in place to monitor changes in diseaserisk (i.e., metritis, mastitis, and displacedabomasum) or risk factors for disease, such asmilk fever or retained placenta, allows for moretimely and appropriate intervention. Recordmajor, consistently defined fresh cow events suchas milk fever, DA, RP, mastitis, metritis, andlameness in addition to freshenings.

•• Some events such as ketosis may be toosubjective or prone to detection biases and areusually not as valuable to record. However, ifrecorded, monthly ketosis incidence can beused to evaluate employee performance.

•• Retained placenta risk, calculated on a weeklyor monthly basis, can be a very good monitor ofboth preparturient feed intake as well as apredictor of future metritis risk. Typically, cowsare considered retained if the placenta is stillpresent 24 hrs after calving.

•• Monthly risk of displaced abomasum (DA)(number of DA divided by number of freshcows at risk) can also be helpful to indicatetransition problems, but this metric suffers frommore lag than RP risk.

47

•• In general, the following fresh cow event risksare achievable goals for most operations:

• Milk fever – less than 3-5 % of mature cowcalvings,

• Displaced abomasum – less than 3-5 % of allcalvings, and

• Retained placenta – less than 8 % of allcalvings.

• Monitor total days dry and days in the close-up pen.

•• Very short dry periods (less than 30 days) mayhave negative impacts on the subsequentlactation performance. Equally important arethe number of excessively long dry periods dueto the cost associated with keeping non-productive cows on the dairy. Excessively longdry periods often reflect problems such aspregnancy loss and rebreeding that results inpregnant cows that are dried prematurelyrelative to gestational age due to low milkproduction, technical error either withconception date estimation or data entry intothe record system, or management decisions tomove pregnant cows into the dry period (ratherthan culling them) prior to the normal daterange due to decreased milk production.Excessively short dry periods are often theresult of errors with conception date estimationor data entry into the record system, shortenedgestation length due to abortion or prematuredelivery, or management mistakes (failed tomove the cow at the correct time). In general,with weekly pregnancy evaluations in AI herdsand weekly moves to the dry pen, a herdshould be able to have about 85% of the drylengths within 14 days +/- of their stated goal.In natural service herds or herds that movecows less often, the variation will besignificantly greater.

•• Most herds strive to achieve about 21 d in aclose-up pen in order to modify the ration froma nutritional perspective, manipulate dietarycation anion differences to managehypocalcemia, to decrease stocking density andto allow for closer observations. However, fewherds actually monitor this item. Longer thannecessary time spent in close-up is costly andoccupies space that other close-up cows mayuse. Days in close-up of less than 10 maypredispose cows to increased risk ofperiparturient issues. Strive to achieve at least10 days in close-up for at least 90% of all cows.

•• The evaluation of peak milk by parity group isan approach that has been practiced for manyyears, but the correlation to overall lactationperformance is actually pretty low. In addition,this metric suffers from the consequences of lag,momentum and the difficulties with accuratecalculations of an animal’s true peak.Therefore, peak milk is a very poor monitor oftransition management and its use should bediscouraged.

• Early lactation milk production, first test milk orweek 4 milk production estimates are bettermonitors of transition performance than waitingfor peak milk.

•• First test milk is the earliest production datathat can be used to evaluate early lactationperformance and the impact of transitionprograms. The lag for this approach is 1 to 3mo shorter than relying on peak milk andallows for the inclusion of cows that may beculled prior to reaching true peak milk.However, this approach is subject to the impactof DIM at the first test. To correct for thisconfounding factor, in large herds first test milkcan be limited to only evaluating animals thatexperience first test between 20 and 30 DIM (orsome comparable range).

•• A useful approach that has gained in popularityis the use of wk 4 milk. In DC305, an estimateof milk production during the fourth week canbe calculated using item type 122 (weeklyaverage milk on week “X” where “X” equals 4).This estimate will include data from more cowsthan only evaluating first test for cows thattested between 20 and 30 DIM and can be usedto illustrate the impact of seasonal changes inearly lactation performance, as well as showingthe impact of management changes.

•• In herds with daily milk meters, changes inmilk production can also be a good monitor,but results should be interpreted with caution.In general, cows should increase in milk flowby ~ 10 %/d for the first 14 d and heifersshould increase in milk flow by ~ 6 to 8 %/dfor the first 14 d.

• One quick assessment of how parity groups areperforming relative to each other is to comparep305me production for parity =1, parity =2 andparity > 2. Interpretation of the results mustconsider the potential that one or more groups isperforming poorly, or conversely, that one ormore groups is performing better than expectedrelative to the remainder of the herd. In most

48

herds, the first lactation group’s p305me milkestimate will be 2 to 5% lower than older cows.This result is often due to a lower cullingpressure for production being applied to thesefirst calf animals. The third and greater lactationgroup, while representing the oldest genetics,should have a p305me that is at least as good asthe second lactation animals or higher since thesecows have had multiple lactations of cullingpressure. If the performance of the first lactationgroup is vastly inferior to expectations, potentialareas for investigation include frame size atcalving, stocking density (especially in mixedparity groups), heifer mastitis challenges, anddystocia challenges unique to the heifers.Common reasons that the first lactation groupmight be outperforming the other two groupsmay be related to the purchase of higher geneticmerit heifers, more aggressive culling of heifersdue to an increase in supply related to the use ofsexed semen or due to disease issues in maturecows such as mastitis, metabolic challengesaround calving, or lameness. In expandingherds, herds that suffer higher risks for lamenessor mastitis, or herds that struggle withreproductive performance, the p305me of theolder cows may in fact be 5 to 15% less than thesecond lactation cows.

• Milk components can also be used at the herdlevel to indicate potential transition issues. Freshcows that mobilize excessive body fat will oftendemonstrate higher than normal levels ofbutterfat. On an individual cow basis, the use ofeither first test fat percentage or fat:protein ratiois not very sensitive for identifying cows atincreased risk of subclinical or clinical ketosis.However, at the herd level, examining thefat:protein ratio at first test can provide valuableinformation.

•• Calculate fat:protein ratio for cows with DIM atfirst test of 10 to 40. If 40 % or more of thispopulation has a fat:protein ratio > 1.4, furtherinvestigation is warranted.

•• Another approach is to look at first test fatpercentage alone. In this case, if > 10 % havean excessively high first test fat percent, furtherinvestigation may be warranted. Cut-pointsused by the authors for quick screening are: 5.0for Holsteins and 6.0 for Jerseys.

SummaryTransition performance is critical to the success ofany dairy. Key components of successful transitioninclude the implementation of herd managementguidelines that focus on prevention of periparturient

problems, real time monitoring of key processes thatimpact the prepartum and the postpartum periods,and evaluating the results of the program through theexamination of key outcomes. The points covered inthis paper are not an exhaustive list of all possibletransition management issues or of all the possibleapproaches to monitoring transition performance.Each herd may have specific approaches that workwell for it and consultants all have their preferredapproaches for evaluating performance. High qualityrecords and their appropriate use are vital to theevaluation of how well cows are transitioning intolactation, but one must always remember there is nosubstitute for walking the herd and observing thecow and her environment. The combination of directobservation of housing, cow comfort, nutrition, andgeneral cow health and condition and a carefulapproach to proper evaluation of records should leadto improved performance in the transition period andbeyond.

LITERATURE USEDBell, A.W. 1995. Regulation of organic nutrient metabolismduring transition from late pregnancy to early lactation, J.Anim. Sci. 73:2804-2819.

Bell, A. W., W. S. Burhans, and T. R. Overton. 2000. Proteinnutrition in late pregnancy, maternal protein reserves andlactation performance in dairy cows. Proc. Nutri. Soc.59:119-126.

Butler, W.R., and R.D. Smith. 1989. Interrelationshipsbetween energy balance and postpartum reproductivefunction in dairy cattle. J. Dairy Sci. 72:767-783.

Comin, A., D. Gerin, A. Cappa, V. Marchi, R. Renaville, M.Motta, U. Fazzini, and A. Prandi. 2002. The effect of anacute energy deficit on the hormone profile of dominantfollicles in dairy cows. Theriogenology 58:899-910.

Contreras, L.L., C.M. Ryan, and T.R. Overton. 2004. Effectsof dry cow grouping strategy and prepartum bodycondition score on performance and health of transitiondairy cows. J. Dairy Sci. 87:517-523.

Drackley, J.K. 1999. Biology of dairy cows during thetransition period: the final frontier? J. Dairy Sci. 82:2259-2273.

Drackley, J.K., T.R. Overton, and G.N. Douglas. 2001.Adaptations of gulcose and long-chain fatty acidmetabolism in liver of dairy cows during the periparturientperiod. J. Dairy Sci. 84:E100-E112E.

Duffield, T.F., D.F. Kelton, K.E. Leslie, K.D. Lissemore, andJ.H. Lumsden. 1997. Use of test day milk fat and milkprotein to detect subclinical ketosis in dairy cattle inOntario. Can. Vet. Jour.-Revue Veterinaire Canadienne38:713-718.

49

Duffield, T. 2000. Subclinical ketosis in lactating dairycattle. In: Vet. Clin. .N. Am.: Food Anim. Prac., p 231-253.

Grant, R., and J.L. Albright. Dry matter intake influencedby cow grouping, behavior. Feedstuffs, Dec 8, p. 12-16.1997.

Grummer, R.R. 1993. Etiology of lipid-related metabolicdisorders in periparturient dairy cows. J. Dairy Sci. 76:3882-3896.

Grummer, R.R. 1995. Impact of changes in organic nutrientmetabolism on feeding the transition dairy cow. J. Anim.Sci. 73:2820-2833.

Hayirli, A., R.R. Grummer, E.V. Nordheim, and P.M.Crump. 2002. Animal and dietary factors affecting feedintake during the prefresh transition period in Holsteins. J.Dairy Sci 85:3430-3443.

Ingvartsen, K.L., and J.B. Andersen. 2000. Integration ofmetabolism and intake regulation: a review focusing onperiparturient animals. J. Dairy Sci. 83:1573-1597.

Moreira, F., C. Risco, M.F.A. Pires, J.D. Ambrose, M. Drost, M.DeLorenzo, and W.W. Thatcher. 2000. Effect of bodycondition on reproductive efficiency of lactating dairy cowsreceiving a timed insemination. Theriogenology 53:1305-1319.

Rabelo, E., R.L. Rezende, S.J. Bertics, and R.R. Grummer.2003. Effects of transition diets varying in dietary energydensity on lactation performance and ruminal parametersof dairy cows. J. Dairy Sci. 86:916-925.

Reynolds, C.K., P.C. Aikman, B. Lupoli, D. J. Humphries,and D. E. Beever. 2003. Splanchnic metabolism of dairycows during the transition from late gestation throughearly lactation. J. Dairy Sci. 86:1201-1217.

Santos, J.E., E.J. DePeters, P.W. Jardon, and J.T. Huber. 2001.Effect of prepartum dietary protein level on performance ofprimigravid and multiparous Holstein dairy cows. J. DairySci. 84:213-224.

Santos, J.E., S.O. Juchem, K.N. Galvao, and R.L. Cerri. 2003.Transition cow management to reduce metabolic diseasesand improve reproductive management. Proc. WesternCanadian Dairy Seminar, March 11-14, University ofAlberta, Edmonton, Canada.

Stokes, S.R., and J.P. Goff. 2001. Evaluation of calciumpropionate and propylene glycol administered into theesophagus at calving. Prof. Anim. Sci. 17:115-122.

Thatcher, W.W., F. Moreira, J. Santos, and C.R. Staples. 2003.Factors influencing reproductive effciency. In: Proc. FifthWestern Dairy Conf., p. 107-115.

Vandehaar, M.J., G. Yousif, B.K. Sharma, T.H. Herdt, R.S.Emery, M.S. Allen, and J.S. Liesman. 1999. Effect of energyand protein density of prepartum diets on fat and proteinmetabolism of dairy cattle in the periparturient period. J.Dairy Sci. 82:1282-1295.

50

51

Comparison of Immune Function,Uterine Health and More in Holstein and

Crossbred Transition CowsRicardo Chebel

University of Minnesota

52

53

54

55

56

57

58

Dairy managers watch manure changes as a guidewhen making feed changes and evaluating rations.Fresh, undisturbed piles of feces or droppings mayprovide valuable clues and should be part of yourtool box when evaluating the nutritional status of thedairy herd. Four aspects of manure evaluation can beconsidered to be part of your tool box.

Washing manure samplesWashing manure through a screen (6 to 8 squares tothe inch) allows the dairy manager and nutritionist toquickly find or “see” if feed processing and digestionis optimal. Take a cup of fresh manure and wash itwith a stream of warm water (cold water takeslonger) through the screen removing the digestedmaterial. It typically takes about 30 seconds if yourscreen has sides allowing for more water pressure.Look for the following remaining feed particles.Finding pieces of barley or corn grain with whitestarch remaining indicates that some feed value waslost. If the seed and starch pieces are hard, additionalgrinding or processing may be needed to expose thestarch to rumen microbial fermentation or lower gutenzymatic digestion. Corn kernels from corn silagereflect that the seed was too hard for digestion andchewing by the cow. Mature and dry corn silage cancause this observation as grain is hard. Some cornsilage varieties can be selected for softer kernelsallowing for more digestion. Whole cottonseeds orsoybean splits (half of a soybean seed) that appear inthe washed manure reflect a loss of feed nutrients.The cottonseeds are not caught in the rumen mat anddo not allow for rechewing. If roasted soybean seedsare hard, they must be processed finer. Wisconsinworkers suggest breaking soybeans into fourths oreighths. Forage particles over 1/2 inch long mayreflect a lack of long forage particles to maintain therumen mat and adequate cud chewing. A higher rateof passage reduces the time needed in the rumen todigest the fiber properly. The Cargill ManureSeparator (NASCO Digestion Analyzer) iscommercially available through NASCO (price is$195 plus shipping and handling). Users can decideto use the top screen only or two to three screensdepending on time and personal bias and experience.

Scoring manureMichigan workers developed a scoring system to

evaluate fresh manure. Consistency is dependent onwater and fiber content of the manure, type of feed,and passage rate. A scale of 1 to 5 is listed below witha score 3 optimal.

• Score 1. This manure is very liquid with theconsistency of pea soup. The manure may actually“arc” from the cow. Excess protein or starch, toomuch mineral, or lack of fiber can lead to this score.Excess urea in the hindgut can create an osmoticgradient drawing water in the manure. Cow withdiarrhea will be in this category.

• Score 2. This manure appears runny and does notform a distinct pile. It will measure less than oninch in height and splatters when it hits the groundor concrete. Cows on lush pasture may have thismanure score. Low fiber or a lack of functionalfiber can also lead to this manure score.

• Score 3. This is the optimal score! The manure hasa porridge-like appearance, will stack up 1 1/2 to 2inches, have several concentric rings, a smalldepression or dimple in the middle, make aplopping sound with it hits concrete floors, and itwill stick to the toe of your shoe.

• Score 4. The manure is thicker and stacks up over 2inches. Dry cows and older heifers may have thistype of manure (this may reflect that low qualityforages are fed and/or a shortage of protein).Adding more grain or protein can lower thismanure score or improve forage quality.

• Score 5. This manure appears as firm fecal balls.Feeding a straw-based diet or dehydration couldcontribute to this score. Cows with a digestiveblockage may exhibit this score.

Manure scores 1 and 5 are not desirable and mayreflect a health problem besides dietary limitations.Score under score 2 and over score 4 manure scoresmay reflect a need to rebalance the ration. As cowsprogress through their lactation, manure score mayalso shift as outlined below.

• Early lactation cows (2 1/2 to 3) • Late lactation cows (3 to 3 1/2)

59

Manureology 101Michael F. Hutjens

University of Illinois, Urbana232 Animal Sciences Lab1207 West Gregory Drive

Urbana, Illinois 61801hutjensm@illinois.edu

• Far off dry cows (3 to 4) • Close up dry cows (3 to 3 1/2)

Increasing the amount of degradable, soluble, or totalprotein, deceasing the amount or physical form of thefiber; increasing starch level, decreasing grain particlesize (such as fine grinding or steam flaking), andconsuming excess minerals (especially potassium andsodium) can cause manure scores to decline.

A University of Illinois study investigatedrelationships between dairy fecal scores and physicalfiber property based on manure score, fiber particlesize, and fecal dry matter content. Fecal sampleswere collected with 17 pooled fecal samples from 42dairy cows based on their fecal score (1 to 5). Aftercollecting fresh samples over three weeks, thesamples were labeled, mixed, washed, and dried.The amount collected was 500 g of manure persample. For samples less than 500 g, an adjustmentwas calculated to correct to 500 g. Each sample wascollected based on its manure score and given a letterassigned (A-F). Samples were washed using warmwater with a Cargill Manure Separator containingthree stainless steel screens (3/16, 3/32, and 1/16inch hole openings). The fibrous fraction on eachscreen was oven dried for two days at 45 degreescentigrade. Each sample was weighed and recorded.Individual samples and fecal score summary werelisted in table 1.

Total dry matter in samples increased as manurescore increased. The percentage of dry matter on thetop screen (the largest particle size) increased asmanure score increased (Table 2) while the percent ofdry matter on the bottom and middle screensdecreased. The number of whole fuzzy cottonseedsfound in the feces samples increased as fecal scoresincreased. During week two of manure collection,the ration contained 50 percent less fuzzy cottonseed(2.5 pounds compared to 5 pounds). This decreasewas reflected in the number of whole fuzzycottonseeds found in the fecal samples in week two.

Manure colorThe color of manure is influenced by feed, amount ofbile, and passage rate. Manure from cows on pastureis dark green while hay-based rations are brown.Manure from high grain-based diets is more gray-like. Slower rates of passage cause the color to darkenand become more ball-shaped with a shine on thesurface due to mucus coating. Score 1 may be morepale due to more water and less bile content.Hemorrhage in the small intestine causes black andtar-like manure while bleeding in the rectum resultsin red to brown discoloration or streaks of red.

Fecal starch evaluationAs corn prices have increase, the need to optimize thestarch digestibility in the dairy cow continues toimportant. Kernel or plant processing corn silage,grinding corn grain (900 to 1100 microns), invitrorumen starch fermentation values, level of prolamin(type of protein related to vitreousness), and the NRCenergy values based on the rumen model programillustrate the important of total tract starchdigestibility. University of Pennsylvania published aformula to predict total tract starch digestibility usingfecal starch and fecal lignin along with ration starchand lignin. Lignin was used as a marker to estimatestarch utilization. This approach could be useful toevaluate starch utilization on farms. The Pennsylvaniadata concluded that for each increase in fecal starch,the potential loss in milk yield was 0.7 pound per daywith a range of 4 to 10 percent starch in group or herdvalues. Cumberland Valley Lab analyzed 1420 fecalsamples with starch content ranging from 0.20 to 38.9percent with 62 percent containing less than fivepercent starch. Rock River Lab reported 52 samplesaveraged 7.9 percent starch with an apparent total tractdigestibility of 84.8 percent.

An Illinois field study using nineteen Holstein herdsin southwestern Illinois evaluated the fecal starchdigestion using the Pennsylvania equation. Themanure samples used in this project were taken fromundisturbed, fresh pies in the cow lot. On average,four to five pies were sampled, mixed together, andplaced into the quart sized containers supplied byRock River Lab. They were refrigerated until allsamples were collected and shipped by UPS to thelab using cold packs to prevent the samples frombursting out of the containers in transit. Rock RiverLabs conducted feed and fecal starch and NDFanalysis. Results were statistically analyzed usingSAS software to evaluate feed and fecal results andstatistically determine which parameters weresignificant in predicting a prediction model for starchdigestibility.

Table 2 summarizes data collected at each farmillustrating variation from farm to farm. Table 3

60

summarizes the average, standard deviation, andrange associated with each variable evaluated. Milkyield was converted to 3.5% fat-corrected milk usingplant milk fat test. Feed values were calculated usingrations balancing software and forages tested results.The equation from University of Pennsylvania usedto estimate starch digestibility is listed below thatcalculated starch total tract digestibility values inTable 2.

Percent starch apparent digestibility = 1 – ((%lignin in feed x % starch in feces) / (% lignin infeces x % starch in feed))

When entering all variables in Table 4, fecal starchand fecal NDFD were the two variable that werecorrelated with a P < 0.01 to calculated starchdigestibility. Statistical trends (P > 0.05) wereobserved for feed NDF levels and fecal dry mattercontent. Based on the statistical evaluation, thefollowing Illinois prediction equation was developed:

Percent starch apparent digestibility = 0.9373 –(0.0261 x fecal starch) + (0.0091 x fecal lignin).

The R-squared value for the equation was 73indicating 73 percent of the variation in starchdigestibility can be explained by the equation andvariable used with P < 0.0001. The equation must beused with care as the values are based on 19 Holsteinherds, the manure samples procedure, and analyticallab procedures. Additional studies are needed toconfirm and/or refine the equation. Dairy managersand consultants may want to add fecal starch andfecal lignin analysis to monitor starch utilization bytheir dairy herd.

The cost of fecal starch analysis is $15 to $20 persample. The recommendation is to pool fecalsamples from 10 to 15 cows and submit a mixedsample requesting fecal starch. Fecal starch can beanother tool to evaluate total track starch utilization.

Selected ReferencesDeOndarza, M.B. and R. Ward. 2010. Starch in manurecan’t make milk. Hoard’s Dairyman Magazine. Feb 25issue. p. 139.

Lidy, D, J. S. Osorio, M.F. Hutjens, and D.W. Meyer. 2009.Evaluating total tract starch digestibility. IL Dairy Report.pp. 27-29.

Jones, J and M.F. Hutjens. 2010. Relationship of fecalscores and fecal fiber levels. IL Dairy Report. pp. 25-26

Skidmore, A.L., A. Brand, and C.J. Sniffin. 1996.Monitoring milk production: Defining preset targets andexecution. Herd Health and Production Management.Wageningen Pers, Wageningen, Netherlands. pp. 233-262.

61

Troubleshooting Silage Yeast,Mold and VFA Problems

Bill Mahanna, Ph.D., Dipl. ACANNutritional Sciences Manager - Pioneer, A DuPont Business

bill.mahanna@pioneer.com; 515.229.3409

62

63

64

65

66

67

68

69

70

71

72

73

Improving Feeding ConsistencyThrough TMR Audits

Tom Oelberg, Ph.D.Diamond V

toelberg@diamondv.com

74

75

76

77

78

79

80

81

82

83

IntroductionThe first trial reported in the Journal of Dairy Scienceevaluating the nutritive value of high moisture corn(HMC) for lactating dairy cows was published byZogg et al., (1961). The use of HMC on commercialdairy farms has grown, with approximately 65 % ofWisconsin dairy producers now utilizing HMC(Holmes, 2010). Despite wide spread use, HMC is anenigmatic feed because HMC per se is not ahomogeneous feed. A specific HMC corn fed to alactating dairy cow can be a highly variable feedstuff.Corns of varying endosperm type can be ensiledbetween 20%-40 % moisture, with or withoutinoculants, at ambient temperatures of 10-70oF,ensiled whole or ground, treated with or withoutorganic acids, contain cob or husk, be fermented 1 to365 days or more, stored in bags, bunkers and oxygenlimiting silos and still be classified as HMC.

Variance associated with HMC production practiceshas been hypothesized or shown to create variance infermentation characteristics, chemical composition,starch digestibility and milk yield in lactating dairycows. The effects of chemical alteration of HMC onanimal performance is challenging to quantifybecause most if not all HMC studies in the literaturedid not measure detailed chemical compositions ofthe HMC fed. As a result, general review articles(Firkins et al., 2001; Huntington, 1997, Owens et al.,1986) pertaining to starch digestibility in ruminantshave focused on animal responses in trials wherechemically undefined HMC was fed. Differences inruminal, post-ruminal or total tract starchdigestibilities between various grain sources andHMC can be generally categorized, but animalresponses are challenging to directly link to HMCchemistry. Absent from the literature, are definingchemical mechanisms associated with fermentation,which explain altered starch digestion of HMC inruminants. In short, altered starch digestion inlactating dairy cows fed HMC is presently binomiallyclassified (i.e. dry vs HMC) but mechanismsexplaining chemical alterations in HMC as comparedto dry corn and variance of these alterations within amultitude of HMC production practices are poorlydefined.

This paper will focus on the chemistry of HMCduring fermentation and attempt to provide inferenceregarding why HMC starch digestibility in ruminantsis altered as compared to other grain sources such asdry corn. A greater understanding of HMC

chemistry may yield a better understanding of animalperformance variance associated with feeding HMCof various origins.

High Moisture Corn-Starch DigestibilityReviews (Firkins et al., 2001; Huntington, 1997,Owens et al., 1986) pertaining to factors andlimitations of starch digestibility in ruminants havebeen previously published and will not be re-reviewed in this proceedings paper. From thesereviews and trials on feeding HMC the followinggeneral concepts of HMC starch digestibility inlactating dairy cows can be defined (refer to Table 1).

Figure 1. The effect of storage period (240 d) onhydrophobic prolamin-zein proteins in theendosperm of high moisture corn (Hoffman et al.,2010a).

1) The NEL value of HMC is estimated to be 5-10 %greater than dry corn of similar origin and particlesize (Tyrrell and Varga, 1987; Wilkerson et al.,1997). Greater NEL values for HMC are primarilydue to increased total tract starch digestion ofHMC as compared to dry corn.

84

The Chemistry of High Moisture CornP.C. Hoffman, R.D. Shaver and N.M. Esser

Department of Dairy ScienceUniversity of Wisconsin-Madison

2) Ensiling of corn alters the site of starch digestion.Ruminal starch digestibility of HMC starch iscommonly 20-30 percentage units higher than drycorn (Firkins et al., 2001; Owens, 2005)

3) The rate of ruminal starch digestion is faster forHMC as compared to dry corn (Sniffen et al., 1992).

4) Increased ruminal starch digestion and increasedstarch digestion rates may decrease ruminal NDFdigestion (Firkins et al., 2001, Knowlton et al., 1998,Oba and Allen, 2003).

5) Feeding high levels of HMC with high rumenfermentability may depress DMI, rumen pH ormilk fat test (Owens et al., 1986, Bradford andAllen, 2007, Firkins et al., 2001). Depressions inDMI are thought to be modulated by a glucose-insulin response effect (Bradford and Allen, 2007).

Starch Digestibility – From a Corn Seed PerspectiveCorn per se is not a feed, it is a seed, and someunderstanding of corn seed anatomy and physiologyare required to better understand chemical factorsthat potentially influence starch digestibility inruminants. The corn seed is comprised of three basicmorphological parts, pericarp, germ, and endosperm.The endosperm represents approximately 75-80percent of the corn kernel by weight and is themorphological structure which contains starch. Theendosperm contains primarily starch and protein butdoes contain small amounts of fat as phospholipidsand ash. The endosperm of corn is virtually devoidof fiber (ADF or NDF). Specifically, corn endospermcontains < 4% NDF, as compared to the germ whichcontains 17% NDF, and the pericarp with 33% NDF(Van Kempen et.al., 2003). Corn endosperm containsstorage proteins (albumins, globulins, glutelins andthe abundant prolamins (zein protein) which arehydrophobic. The endosperm’s biological function isto serve as the primary nutrient source for theembryo until photosynthesis is initiated uponseedling emergence (Buchanan, et al., 2000; Mohr andSchopfer, 1995).

The basic morphological parts of the corn seed arenot equally digestible in ruminants. The pericarp isthe primary morphological structure protecting boththe embryo and endosperm. In native form, thepericarp of corn is poorly digested by rumen bacteriawith minimal post ruminal digestion potential. Cornpericarp is relatively resistant to rumen bacteriaattachment (Huntington, 1997) and whole corn seedswith the pericarp intact are largely indigestible in thesmall and large intestines of ruminants (Owens et al.,1986).

Digestion of starch, contained in the endosperm, byruminants is enigmatic because starch isolated from

cereal grains, regardless of source is rapidly attackedby rumen microbes and fermented rapidly (Hibberdet al., 1983). Starch in corn endosperm is, however,not in isolated form. Starch in a corn seed isprotected by hydrophobic (repels water) proteinscalled prolamins (zein). The combination of starch,prolamins and other proteins (albumins, globulins,glutelins) in corn endosperm is often referred to asthe starch-protein matrix. The starch-protein matrixbinds starch granules together and the degree ofbinding alters the grinding efficiency of corn (Foxand Manley, 2009) and the ability of, and surface areafor, rumen bacterial attachment (Huntington, 1997).

In corn, prolamin proteins named zein are theprimary protein in the starch protein matrix, andcomprise 50-60 % of the total protein in whole corn(Hamaker et al., 1995). Prolamin-zein, defines a classof hydrophobic proteins synthesized on the roughendoplasmic reticulum of the amyloplast (starchproducing organelle) envelope consisting of four zeinsub-classess (α,β,γ,δ) (Buchanan, et al., 2000). Becauseprolamin-zein proteins are synthesized on the roughendoplasmic reticulum within the amyloplastwithout the presence of transit genes (Buchanan etal., 2000), prolamin-zein proteins are not intrinsicwithin the starch granule but are primarily surfacelocalized on the exterior of starch granules (Mu-Forster and Wasserman, 1998). As prolamin-zeinproteins enlarge and distend with advancingmaturity β- and γ- zeins cross-link and α- δ-zeinspenetrate their network and occupy a more centralposition encapsulating starch into a starch-hydrophobic protein matrix (Buchanan et al., 2000;Mu-Forster and Wasserman, 1998).

Differences in the starch-protein matrix can be visiblyseen in dissected kernels of yellow dent corn. Thevisual appearance of all or portions of the starch-protein matrix in corn endosperm have historicallybeen given visually descriptive classifications.Starch-protein matrices appearing white arecommonly given the names floury, opaque or softendosperm. Starch-protein matrices appearingyellow, shiny or glassy are classified as, horny,translucent or vitreous (Kempten, 1921).

The Starch-Protein Matrix and High Moisture CornThe starch-protein matrix in corn has been previouslydefined as a physio-chemical impediment to starchdigestion in ruminants (Owens et al., 1986), but therole of the starch- protein matrix in the digestion ofHMC starch in ruminants is not well defined.Because prolamin-zein increases with advancingmaturity (Murphy and Dalby, 1971), lower prolamin-zein contents in HMC at ensiling could be expected.This argument is somewhat illogical because Murphyand Dalby (1971) observed that maximum prolamin-

85

zein accretion occurred near black layer formation (±30 % moisture), which is similar to typical ensilingmoisture contents of HMC. In addition, HMC anddry corn are often harvested (combined) at verysimilar moisture contents with only post-harvesthandling and storage of the corn being differentthereafter. Specifically, corn is commonly combined at25%-30 % moisture and mechanically dried thereafteryielding dry corn.

A more plausible explanation for greater and morerapid starch digestion of HMC starch is thatfermentation acids or proteolysis degrade prolamin-zein proteins during the ensiling process. Bacterialproteolysis is an intrinsic mechanism in corn-grainfermentation which induces degradation of cornproteins (Baron et al., 1986). Philippeau andMichalet-Doreau (1998) observed that ensiling grainsincreased ruminal starch degradability andhypothesized that ensiling increases accessibility ofstarch granules to rumen microorganisms, becausehydrophobic prolamin-zein proteins encapsulatingstarch granules were partially degraded byproteolysis. Likewise, Jurjanz and Monteils (2005)observed the effective ruminal degradability of starchto be lower in corn kernels before (70.2%) than after(92.3%) ensiling. The ensiling process improvedstarch degradation by significantly altering therapidly-degradable starch fraction (80.7% versus65.6%) and the starch degradation rate (12.4 vs 8.0%/h). Combined, these data (Baron et al., 1986;Philippeau and Michalet-Doreau, 1998; Jurjanz andMonteils, 2005) result in a very plausible hypothesisas to why higher ruminal and total tract starchdigestibility is observed for HMC as compared to drycorn (Firkins, et al., 2001).

In a recent study, (Hoffman et al., 2010a) wemonitored the fate of the starch-protein matrix inHMC across a long storage period (240 days). Tworandom HMC(s), containing 25.7% and 29.3 %moisture were ground, ensiled and stored for 0, 15,30, 60, 120 and 240 d. At 0 and 240 d, the α, γ, δ and βzein regions of the starch-protein matrix wereprofiled using high performance liquidchromatography. The effect of fermentation (storagetime) on the starch-protein matrix of HMC after 240 dof storage is presented in Figure 1. Fermentation (0vs 240 d) reduced all α, β and δ prolamin-zeinsubunits of the starch-protein matrix from 10%-40 %.The degradation of the γ prolamin-zein subunits ofthe starch-protein matrix of HMC was more extensivewith a 60 % reduction. Because γ prolamin-zeins aresurface localized and primarily responsible for cross-linking starch granules together, the degradation of γzeins in HMC would suggest that clusters of starchgranules should disassociate (fall apart) as a result offermentation since the cross links holding starch

granules together are being degraded. This wasconfirmed by electron microscopy (photos notshown) of HMC starch granules at 0 and 240 d..Upon fermentation and storage for 240 d, thedisassociation of starch-granule clusters in HMCcould be readily seen using electron microscopy.Fermentation resulted in a greater number ofindividual starch granules (and surface area) forpotential attack by rumen bacteria. Electronmicrographs also revealed no alteration in individualstarch granules in HMC prior to fermentation or after240 d of storage. Inferences from this investigation(Hoffman et al., 2010a) also suggested the proteins inthe starch-protein matrix were more likely altered bybacterial proteolysis and may not have been simplysolubilized by fermentation acids.

In second study (Hoffman et al., 2010b), thedigestibility of HMC fermented and stored for 0, 15,30, 60, 120 and 240 d was evaluated using an in vitrogas production system. Gas production and rate (kd)of gas production by rumen bacteria during the first12 h of incubation increased with increasing storagetime, which indirectly validates the observations ofgreater ruminal starch digestion of HMC ascompared to unfermented corn. Increases in 12 h gasproduction and rate (kd) of gas production increasedchronically over the entire HMC storage periodssuggesting that the increase in HMC (DM) digestionis not an acute event. Similar results were reportedby Benton et al. (2005) who evaluated in situ DMdegradation of two HMC(s) and two reconstitutedHMC(s) of varying moisture content; a chronicincrease in DM degradation across a 300(+) dayensiling period was observed. The observations ofBenton et al. (2005) and Hoffman et al. (2010b) arepresented in Figure 2. The data are similar and when

86

combined suggest DM that the digestion potential ofHMC increases chronically as storage time increases.

Figure 2. Changes in high moisture corn DMdegradation across long ensiling periods.A= Benton et al., 2005 (n = 24% moisture HMC,x = 28% moisture reconstituted corn, s= 30%moisture HMC, •• = 35% moisture reconstituted corn).B = Hoffman et al., 2010b (•• = 29.3% moisture HMC,n = 25.7% moisture HMC). In situ Dacron bags andin vitro gas production were used as evaluationtechniques by Benton et al., (2005) and Hoffman etal., (2010b) respectively.

High Moisture Corn Fermentation is Poor and SlowIn our recent research (Hoffman et al., 2010a) weevaluated the nutrient composition (CP, prolamin,starch, ADF and NDF), fermentation (pH, lactate andacetate) and protein degradation markers (buffer-soluble CP and NH3-N) of HMC at 0, 15, 30, 60, 120and 240 d of storage. The data provided a holisticview of nutri-chemical transformations in HMC bystorage time. The CP, origin prolamin, starch, ADFand NDF contents of HMC are relatively static, butpH, lactate, acetate, buffer-soluble CP and NH3-Ncontents chronically changed with advancing storagetime. The chronic changes in HMC NH3-N contentby storage time are presented in Figure 3. Ammonia(NH3-N) in HMC did not stop accumulating even at240 d. Ammonia is an important marker infermented feeds, because NH3-N is intrinsic todeamination of amino acids which is the terminalphase of proteolysis (protein breakdown). The datain Figure 3 suggest that proteolysis in HMC did notabate even after 240 d of storage. These data presentan indication that fermentation of HMC is very slowand chemical alterations are occurring over anextended storage period.

Figure 3. The effect of storage time of on NH3-N offour high moisture corns (Hoffman et al., 2010a)

It is logical that HMC ferments slower than legumeor corn silage for a number of reasons. NormallyHMC, prior to ensiling, does not contain high levelsof sugars or water soluble carbohydrates forconversion to volatile fatty acids. The levels of mono-disaccharides and water soluble carbohydrates oflegumes, whole-plant corn and corn grain prior toensiling (Dairy One Laboratories, Ithica, NY) arepresented in Figure 4. Fresh corn containssignificantly less mono-disaccharides or water solublecarbohydrates than legumes or whole-plant corn.Because the level of fermentable substrate in freshcorn is lower than fresh legumes or whole-plant corn,the production of volatile fatty acids in HMC isreduced when compared to legume or corn silage(Figure 5).

Figure 4. Typical contents of mono-disaccharides andwater soluble carbohydrates (CHO) in legumes, cornsilage and high moisture corn prior to ensiling (DairyOne Laboratories, Ithaca NY.

Figure 5. Typical pH, lactate and acetate contents oflegume silage, corn silage and high moisturecorn (Dairy One Laboratories, Ithaca, NY).

High moisture corn is also ensiled at DM contentsnear 70.0%. High DM contents increase the osmoticpotential in silage (or HMC), which decreases thegrowth rate of lactic acid producing silage bacteria(Pitt et al., 1985). As a result, silage or HMC withhigher DM content ferment slower than silage or

87

HMC with a lower DM content. Slower growth ratesof silage bacteria induced by ensiling at high DMcontents can be further exacerbated by ensiling at lowtemperatures (Pitt et al., 1985). The effect of silagemass temperature on growth of lactic acid producingbacteria is presented in Figure 6. High moisture cornis commonly ensiled when ambient temperatures are< 50oF, which does not facilitate rapid bacterialgrowth. The combination of limited substrate forfermentation, high DM content, and ensiling at coolertemperatures suggest HMC fermentations aredestined to be protracted. Protracted fermentationswould mean a protracted proteolytic breakdown ofthe starch-protein matrix in the endosperm. In ourrecent work (Hoffman et a., 2010ab), we observed thiseffect; protracted fermentations and proteinalterations in HMC which resulted in chronicincreases over time in storage for 12 h in vitro gasproduction and rates of gas production.

Figure 6. Effect of ensiling temperature on silagebacteria growth rate (Calculated from Pitt et al., 2005)

Conclusions• The starch protein matrix in HMC is

significantly altered by the fermentationprocess, especially γ zein proteins which crosslink starch granules together.

• Fermentation induced degradation of γ zeinproteins in HMC appears to yield a generaldisassociation of starch granule clustersyielding more individual starch granules and(or) surface area for potential bacterial attack.

• The degradation of the starch protein matrix inHMC appears to be chronic and slow.

• Fermentation and storage time chronicallyincreases the DM digestion potential of HMC.

• Traditional feed chemistry nutrients in HMC(ADF, NDF, CP and starch) are static across thestorage period and do not appear well suitedfor determining biochemical factors thatinfluence starch digestibility of HMC inruminants.

• High moisture corn is not a static feedstuff witha fixed or book value nutrient composition.Nutrient availabilities in HMC chronicallychange and changes are likely dependent onphysical processing, the strength of the starch-protein matrix at ensiling, fermentationconditions at ensiling (DM and temperature),and the length of the storage period.

REFERENCESBaron, V.S., K.R. Stevenson, and J.G. Buchanan-Smith.1986. Proteolysis and fermentation of corn-grain ensiled atseveral moisture levels and under several simulated storagemethods. Can. J. Anim. Sci. 66:451-461.

Bradford, B.J., and M.S. Allen. 2007. Depression in feedintake by a highly fermentable diet is related to plasmainsulin concentration and insulin response to glucoseinfusion. J. Dairy Sci. 92:3838-3845.

Benton, J.R., T. Klopfenstein, and G.E. Erickson. 2005.Effects of corn moisture and length of ensiling on drymatter digestibility and rumen degradable protein.Nebraska Beef Cattle Reports: 31-33.

Buchanan, B.B., W. Gruissem, and R.L. Jones. 2000.Biochemistry and Molecular Biology of Plants. Am. Soc. ofPlant Physiol., Rockville, MD.

Fox, G. and M. Manley. 2009. Hardness methods fortesting maize kernels. J. Agric. Food Chem. 57:5647-5657.

Hamaker, B.R., A.A. Mohamed, J.E. Habben, C.P. Huang,and B.A. Larkins, 1995. Efficient procedure for extractingmaize and sorghum kernel proteins reveals higherprolamin contents than the conventional method. CerealChem. 72(6):583-588.

Hibberd, C.A., D.G. Wagner, R.L. Hintz, and D.D. Griffin.1983. Effect of sorghum grain variety and processingmethod on the site and extent of starch digestion in steers.Oklahoma Agr. Exp. Sta. MP-114:28.

Hoffman, P.C., N.M. Esser, R.D. Shaver, W. Coblentz, M.P.Scott, A.L. Bodnar, R. Schmidt and B. Charely. 2010a.Influence of inoculation and storage time on alteration ofthe starch-protein matrix in high moisture corn. J. DairySci. 93(Suppl. 1):in press.

Hoffman, P.C., N.M. Esser, R.D. Shaver, W. Coblentz, M.P.Scott, A.L. Bodnar, R. Schmidt and B. Charely. 2010b.Influence of inoculation and storage time on in vitro gasproduction of high moisture corn. J. Dairy Sci. 93(Suppl.1):in press.

Holmes, B. 2010. A field survey of high moisture corn useon Wisconsin dairy farms. University of Wisconsin-Extension (Unpublished survey: personal communication).

88

Huntington, G.B. 1997. Starch utilization by ruminants:from basics to the bunk. J. Anim. Sci. 75:852-867.

Jurjanz, S., and V. Montels. 2005. Ruminal degradability ofcorn forages depending on the processing methodemployed. Anim. Res. 3:15-23.

Kempten J.H. 1921. Waxy endosperm in coix and sorghum.J. Heredity. 12:396-400.

Knowlton, K. F., B. P. Blenn, and R. A. Erdman. 1998.Performance, ruminal fermentation, and site of starchdigestion in early lactation cows fed corn grain harvestedand processed differently. J. Dairy Sci. 81:1972-1984.

Mohr, D., and P. Schopfer. 1995. Plant Physiology.Springer-Verlag, Berlin, Germany.

Mu-Forster, Chen, and Bruce P. Wasserman. 1998. Surfacelocalization of zein storage proteins in starch granules frimmaize endosperm: Proteolytic removal by thermolysin andin vitro cross-linking of granule-associated polypeptides.Plant Physiology. 116:1563-1571.

Murphy, J.J., and A. Dalby. 1971. Changes in the proteinfractions of developing normal and opaque-2 maizeendosperm. Cereal Chem. 48:336-349.

Oba, M., and M.S. Allen. 2003. Effects of corn grainconservation method on ruminal digestion kinetics forlactating dairy cows at two dietary starch concentrations. J. Dairy Sci. 86:184-194.

Owens, F.N., R.A. Zinn and Y.K. Kim. 1986. Limits tostarch digestion in the ruminant small intestine. J. Anim.Sci. 63:1634-1648.

Owens, F.N. 2005. Corn grain processing and digestion.University of Minnesota-Extension,http://www.ddgs.umn.edu.

Philippeau, C., and B. Michalet-Doreau. 1998. Influence ofgenotype and ensiling of corn grain on in situ degradationof starch in the rumen. J. Dairy Sci. 81:2178-2184.

Pitt, R.E., R.E. Muck, and R.Y. Leibensperger. 1985. Aquantitative model of the ensilage process of lactate silages.Grass and Forage Sci. 40:279-303.

Sniffen, C.J., J.D. O’Connor, P.J. Van Soest, D.G. Fox and J.B.Russell. 1992. A net carbohydrate and protein system forevaluating cattle diets: II. Carbohydrate and proteinavailability. J. Anim. Sci. 70:3562-3577.

Tyrrell, H.F., and G.A. Varga. 1987. Energy value forlactation of rations containing ground whole ear maize ormaize meal both conserved dry or ensiled at high moisture.Eur. Assoc. Anim. Prod. 32:308-309.

Van Kempen T.A., E. van Heugten, A.J. Moeser, 2003.Dehulled, degermed corn as a preferred feed ingredient forpigs. 2003-North Carolina Annual Swine Report, NorthCarolina State University, Raleigh, N.C.

Wilkerson, V.A., B.P. Glenn, and K.R. McLeod. 1997.Energy and nitrogen balance in lactating dairy cows feddiets containing dry or high moisture corn in either rolledor ground form. J. Dairy Sci. 80:777-783.

Zogg, C.A., R.E. Brown, K.E. Harshbarger, and K.A.Kendall. 1961. Nutritive value of high moisture corn whenfed with various silages to lactating dairy cows. J. DairySci., 44:483-489.

89

n Take Home Messages

n Reduced starch diets may be acceptable forlactating dairy cows when using digestible orsoluble fiber to partially replace starch.

n Type of endosperm, particle size, maturity andmoisture content, and conservation andprocessing methods, influence the digestibilityof starch from corn grain and corn silage bydairy cows.

n The inclusion of exogenous enzymes withamylolytic activity in reduced-starch diets fordairy cows may play a role in the future toincrease feed conversions.

n IntroductionThe optimum starch content of diets fed to lactatingcows is not well defined, but 24% to 26% starch (DMbasis) has been suggested (Staples, 2007). Kaiser andShaver (2006) and Bucholtz (2006), from surveys ofhigh producing (>13,650 kg RHA) dairy farms inWisconsin (n = 9) and Michigan (n = 18), respectively,reported starch concentrations of diets fed to lactatingcow groups ranging from 25% to 30% (DM basis).With today’s higher grain prices, however, there isincreased interest in feeding diets that are lower instarch content than what has been the norm. Thepurpose of this paper is to evaluate the potential forusing digestible or soluble neutral detergent fiber(NDF) from byproduct feeds to partially replacestarch from corn grain in diets fed to lactating dairycows. Potential modifying effects of starchdigestibility on lactation performance by dairy cowsfed reduced starch diets will also be examined.

n Partial replacement of dietary starch withdigestible or soluble NDF

Beet pulpVoelker and Allen (2003) fed mid-lactation cows dietscontaining 35, 31, 27 and 18% starch (DM basis);high-moisture corn was replaced by 6, 12 and 24%pelleted beet pulp (DM basis) to formulate diets withdecreasing starch content. Effects of decreasingdietary starch content were linear (P < 0.05) for dry

matter intake (DMI) and quadratic (P < 0.07 and 0.03,respectively) for FCM and fat yields. Relative to theaverage for the 27 and 31% starch diets, feeding the18% starch diet reduced DMI, FCM yield and fatyield by 9%, 4% and 5%, respectively; true protein(TP) content and yield were numerically reduced by4% and 5%, respectively.

Citrus pulpBroderick et al. (2002) fed mid lactation cows dietscontaining 31 or 20% starch (DM basis); dry crackedcorn was replaced by 19% dried citrus pulp (DMbasis) to formulate the low-starch diet. Feeding thelow starch diet reduced DMI (P < 0.02), milk yield (P< 0.02), fat yield (P < 0.03), TP content (P < 0.01) andyield (P < 0.01) by 8%, 11%, 14%, 4% and 20%,respectively.

Soy hullsFor the set of trial diets which contained 50% foragecomprised of 50:50 corn silage: alfalfa silageformulated for 30%, 26% and 22% starch (DM basis)by partially replacing dry ground shelled corn withsoyhulls, Weiss et al. (2009) observed in mid-lactationcows across decreasing dietary starch concentrations:DMI = 24.0, 24.5 and 25.0 kg/d; milk yield = 37.9,38.3 and 37.6 kg/d; energy-corrected milk yield =41.7, 40.2 and 41.2 kg/d. Stone (1996) reported nodifferences between 25%- and 16%-starch diets fed toearly lactation cows with high-moisture corn beingreplaced by 19% soyhulls (DM basis) to formulate thelow-starch diet.

Ipharraguerre et. al (2002) fed mid-lactation cowsdiets containing 28, 23, 17, 13 and 7% starch (DMbasis); dry ground corn was replaced by 10, 20, 30and 40% pelleted soyhulls (DM basis) to formulatediets with decreasing starch content. Decreasingdietary starch content decreased linearly DMI (P <0.06) by 7% and increased linearly fat content (P <0.004) and fat yield (P < 0.001) by 8% and 10%,respectively. Yield of TP tended (P < 0.09) to bereduced by 5% for the lowest-starch diet relative tothe 28%-starch diet. There were no differencesbetween the 17%- and 23%-starch diets. Comparingthe average of the 7%- and 13%-starch diets to theaverage of the 17%-, 23%- and 28%-starch diets,

90

Improving Starch Digestibility in Dairy Cows:Opportunities with Reduced-Starch Diets

R.D. ShaverDepartment of Dairy Science280 Animal Sciences Building

1675 Observatory Drive, Madison, WI 53706University of Wisconsin

Email: rdshaver@wisc.edu

feeding the low starch diets numerically reducedDMI, milk yield and TP yield by 6%, 3% and 3%,respectively; milk fat content and yield were eachnumerically increased by 8%.

Corn gluten feedStaples (2007), from a review of 14 trials withlactating dairy cows where corn gluten feed partiallyreplaced grains, protein meals or forages with dietarystarch concentrations ranging across the trials from15% to 40% (DM basis), concluded that 21%-starchdiets may be acceptable.

High-fiber byproduct mixturesRanathunga et al. (2010) fed mid-lactation cows dietscontaining 29, 26, 23, and 20% starch (DM basis); dryground corn was partially replaced by a mixture ofdistillers dried grains (DDGS) and soyhulls(approximately 2:1 DDGS: soy hulls) to formulatediets with decreasing starch content. Decreasingdietary starch content decreased (P < 0.01) linearlyDMI, but actual and energy-corrected milk yieldswere unaffected by treatment. Thus, decreasingdietary starch content increased (P < 0.06) linearlyenergy-corrected milk feed conversion from 1.47 to1.61 kg/kg DMI. It should be noted that dietarycrude fat concentrations increased from 4.4 to 5.5%(DM basis) from the added DDGS as dietary starchcontent was decreased from 29 to 20%, which mayhave influenced the DMI and feed conversionresponse observed in this study.

Batajoo and Shaver (1994) fed mid-lactation cowsdiets containing 30, 26, 21, and 15% starch (DMbasis); dry ground corn was partially replaced by 0-10% wheat midds, 3-20% brewers dried grains and 0-9% soyhulls (DM basis) to formulate diets withdecreasing starch content. Decreasing dietary starchcontent decreased (P < 0.05) linearly DMI, TP contentand TP yield by 7%, 4% and 6%, respectively, andincreased (P < 0.05) linearly fat content by 3%.Adverse effects of low starch diets on DMI, TPcontent and TP yield were more apparent for the15%-starch diet than the 21% starch diet.

SummaryResults from these relatively short-term dairy cattlefeeding trials suggest that reduced-starch dietsformulated by partially replacing corn grain in dietswith high-fiber, low-starch byproduct feedstuffs maybe feasible, but longer-term lactation trials and trialswith higher producing cows are warranted. Further,the cost of using digestible or soluble NDF frombyproduct feeds to partially replace starch from corngrain needs to be evaluated for the various high-fiberbyproduct sources on a local basis relative to cornand protein supplement prices.

n Starch digestibilityTotal tract digestibility of starch by dairy cows isvariable ranging from 70% to 100% (Firkins et al.,2001). Various factors, particle size (fine vs. coarsegrind), grain processing (steam flaked vs. dry rolled),storage method (dry vs. high-moisture corn),moisture content of high-moisture corn, type of cornendosperm, and corn silage maturity and processing,influence the digestibility of starch by dairy cows(Firkins et al., 2001; Johnson et al., 1999; Nocek andTamminga, 1991).

Kernel vitreousness, the ratio of vitreous to flouryendosperm, has been used to assess the type of cornendosperm (Ngonyamo-Majee et al., 2008a, b).Increased kernel vitreousness reduced ruminal in situcorn starch degradation (Correa et al., 2002;Ngonyamo-Majee et al., 2008b). Kernel vitreousnesswas lower and ruminal in situ starch degradationwas greater for dry corn with floury or opaqueendosperm than with normal dent endosperm(Ngonyamo-Majee et al., 2008a, b). Taylor and Allen(2005) reported greater ruminal and total tract starchdigestibilities in ruminally and duodenallycannulated lactating dairy cows for floury (3%vitreousness) vs. normal dent (67% vitreousness)endosperm dry corn.

Highly vitreous corn types contain higherconcentrations of prolamin proteins than floury oropaque corn types (Hamaker et. al., 1995; Larson andHoffman, 2008). Starch granules in the cornendosperm are surrounded by hydrophobic prolaminproteins which are slowly degraded (McAllister et al.,1993). Lopes et al. (2009) conducted an experiment toevaluate the effect of type of corn endosperm onnutrient digestibility in lactating dairy cows usingnear-isogenic variants of a normal dent endospermhybrid carrying floury-2 or opaque-2 alleles. Thepercentage vitreous endosperm was zero for flouryand opaque endosperm corns and 64% for thevitreous corn. Prolamin protein content of floury andopaque endosperm corns was 30% of the contentfound in vitreous corn. Starch disappearance after 8-hr ruminal in situ incubation was 32%-units onaverage greater, respectively, for floury and opaqueendosperm corns than vitreous corn. Total-tractstarch digestibility was 6.3%-units, on average,greater for cows fed diets containing floury andopaque endosperm corns than vitreous corn.

The impact of the digestibility of corn grain starch onlactation performance by dairy cows was reviewedby Firkins et al. (2001). Based on regressions from thedata of (Firkins et al., 2001), increasing starchdigestibility increased milk and protein yields (R2 =0.89; P < 0.01) and reduced milk fat percentage (R2 =0.58; P < 0.05) but not yield. When in concurrence

91

with the feeding of low-starch diets, however,increasing starch digestibility may be less likely toresult in reduced milk fat percentage. But, research islimited on the impact of increasing starch digestibilityin reduced-starch diets on lactation performance bydairy cows.

n Reduced starch diets and improving starchdigestibility

Gencoglu et al. (2010) conducted a lactation trial todetermine lactation performance responses in high-producing dairy cows to a reduced-starch versus anormal-starch diet and to the addition of exogenousamylase to the reduced-starch diet. Some exogenousenzymes are resistant to ruminal degradation(Hristov et al., 1998), and thus may offer potential forimproving diet digestibility and animal performance.Klingerman et al. (2009) reported that exogenousamylase addition to a normal-starch diet (26% of DM)increased milk yield by dairy cows; positive in vitroand in vivo digestibility responses to exogenousamylase were also observed.

In the trial of Gencoglu et al. (2010), 36 multiparousHolstein cows (51 ± 22 DIM at trial initiation) wererandomly assigned to 1 of 3 treatments in acompletely randomized design; a 3-wk covariateadjustment period with cows fed the normal-starchdiet followed by a 12-wk treatment period with cowsfed their assigned treatment diets. The normal-starchTMR did not contain exogenous amylase (NS-). Thereduced-starch diets, formulated by partiallyreplacing corn grain with soy hulls, were fed without(RS-) and with (RS+) exogenous amylase addition tothe TMR. Starch concentrations averaged 27.1%,21.8% and 20.7% (DM basis) for the NS-, RS- and RS+diets, respectively.

Dry matter intake for cows fed RS- was 2.4 and 3.2kg/d greater than for cows fed NS- and RS+,respectively. Milk yield averaged 50.4 kg/d and wasunaffected by treatment. Fat-corrected milk yield was2.9 kg/d greater for cows fed RS- than for cows fedNS-. Body weight and condition score measurementswere unaffected by treatment. Fat-, solids-, andenergy-corrected milk feed conversions (kg / kgDMI) were 12% to 13% greater for cows fed RS+ thanfor cows fed RS-. Dry matter and nutrientdigestibilities were lowest for cows fed NS- andgreatest for cows fed RS+, and were greater for cowsfed RS+ than for cows fed RS- with the exception ofstarch digestibility which was similar.

Greater conversion of feed to milk for dairy cows fedreduced-starch diets with inclusion of exogenousamylase may offer potential for improving economicperformance depending on diet and additive costs.

Additional studies have recently been conducted atThe Ohio State University (Weiss pers. comm.,OARDC, Wooster, OH) and UW-Madison (Ferrarettoand Shaver) on the effects of reduced-starch diets andexogenous amylase addition to reduced-starch dietswith formulation of the reduced-starch diets bypartially replacing dry shelled corn with corn silageor a whole cottonseed/wheat middlings mixture,respectively.

n ConclusionsLactation performance was reduced for 18% and 20%starch diets (DM basis) formulated using beet pulpand citrus pulp, respectively, to partially replace corngrain. However, lactation performance was notreduced for diets as low as 16% to 17% starch (DMbasis) formulated using soy hulls to partially replacecorn grain. Diets containing 21% starch (DM basis)were acceptable when high-fiber, moderate proteinbyproduct feeds were used to partially replace corngrain and protein supplement. The starch in low-starch diets should be highly digestible. Variousfactors, including type of endosperm, particle size,maturity and moisture content, and conservation andprocessing methods, influence the digestibility ofstarch from corn grain and corn silage by dairy cows.The inclusion of exogenous enzymes with amylolyticactivity in reduced-starch diets for dairy cows mayplay a role in the future.

n ReferencesBatajoo, K. K., and R. D. Shaver. 1994. Impact of nonfibercarbohydrate on intake, digestion, and milk production bydairy cows. J. Dairy Sci. 77:1580:1588.

Broderick, G. A., D. R. Mertens, and R. Simons. 2002.Efficacy of carbohydrate sources for milk production bycows fed diets based on alfalfa silage. J. Dairy Sci. 85:1767-1776.

Bucholtz, H. 2006. Feeding practices of high-producingherds; What can we learn? Proc. Western Canadian DairySeminar. Red Deer, Alberta, Canada. 18:157-177.Correa, C. E. S., R. D. Shaver, M. N. Pereira, J. G. Lauer, andK. Kohn. 2002. Relationship between corn vitreousness andruminal in situ starch degradability. J. Dairy Sci. 85:3008-3012.

Firkins, J. L., M. L. Eastridge, N. R. St-Pierre, and S. M.Noftsger. 2001. Effects of grain variability and processingon starch utilization by lactating dairy cattle. J. Anim. Sci.79(E. Suppl.): E218-E238.

Gencoglu, H., R. D. Shaver, W. Steinberg, J. Ensink, L. F.Ferraretto, S. J. Bertics, J. C. Lopes, and M. S. Akins. 2010.Effect of feeding a reduced-starch diet with or withoutamylase addition on lactation performance by dairy cows.J. Dairy Sci. 93: 723-732.

Hamaker, B. R., A. A. Mohamed, J. E. Habben, C. P. Huang,and B. A. Larkins, 1995. Efficient procedure for extractingmaize and sorghum kernel proteins reveals higherprolamin contents than the conventional method. CerealChem. 72(6):583-588.

92

Hristov, A. N., T. A. McAllister, and K. J. Cheng. 1998.Stability of exogenous polysaccharide-degrading enzymesin the rumen. Anim. Feed Sci. Technol. 76:161–168.

Ipharraguerre, I. R., R. R. Ipharraguerre, and J. H. Clark.2002. Performance of lactating dairy cows fed varyingamounts of soyhulls as a replacement for corn grain. J.Dairy Sci. 85:2905-2912.

Johnson, L., J. H. Harrison, C. Hunt, K. Shinners, C. G.Doggett, and D. Sapienza. 1999. Nutritive value of cornsilage as affected by maturity and mechanical processing: Acontemporary review. J. Dairy Sci. 82:2813-2825.

Kaiser, R., and R. Shaver. 2006. Benchmarking highproducing herds. Proc. Western Canadian Dairy Seminar.Red Deer, Alberta, Canada. 18:179-190.

Klingerman, C. M., W. Hu, E. E. McDonell, M. C.DerBedrosian, and L. Kung, Jr. 2009. An evaluation ofexogenous enzymes with amylolytic activity for dairycows. J. Dairy Sci. 92:1050-1059.

Larson, J., and P. C. Hoffman. 2008. Technical Note: Amethod to quantify prolamin proteins in corn that arenegatively related to starch digestibility in ruminants. J.Dairy Sci. 91:4834-4839.

Lopes, J. C., R. D. Shaver, P. C. Hoffman, M. S. Akins, S. J.Bertics, H. Gencoglu, and J. G. Coors. 2009. Type of cornendosperm influences nutrient digestibility in lactatingdairy cows. J. Dairy Sci. 92:4541–4548.

McAllistar, T. A., R. C. Phillippe, L. M. Rode, and K. J.Cheng. 1993. Effect of the protein matrix on the digestionof cereal grains by ruminal microorganisms. J. Anim. Sci.71:205-212.

Nocek, J. E., and S. Tamminga. 1991. Site of digestion ofstarch in the gastrointestinal tract of dairy cows and itseffects on milk yield and composition. J. Dairy Sci. 74:3598-3629.

Ngonyamo-Majee, D., R. D. Shaver, J. G. Coors, D.Sapienza, C. E. S. Correa, J. G. Lauer and P. Berzaghi. 2008a.Relationships between kernel vitreousness and dry matterdegradability for diverse corn germplasm. I. Developmentof near-infrared refelctance spectroscopy calibrations.Anim. Feed Sci. Technol. 142:247-258.

Ngonyamo-Majee, D., R. D. Shaver, J. G. Coors, D. Sapienzaand J. G. Lauer. 2008b. Relationships between kernelvitreousness and dry matter degradability for diverse corngermplasm. II. Ruminal and post-ruminal degradabilities.Anim. Feed Sci. Technol. 142:259-274.

Rananthunga, S. D., K. F. Kalscheur, A. R. Hippen, and D. J.Schingoethe. 2010. Replacement of starch from corn withnonforage fiber from distillers grains and soyhulls in dietsof lactating dairy cows. J. Dairy Sci. 93: 1086-1097.

Staples, C. R. 2007. Feeding dairy cows when corn pricesare high. Proc. 44th Florida Dairy Production Conference.Gainesville, FL.

Stone, W. C. 1996. Applied topics in dairy cattle nutrition:Soy hulls as either forage or concentrate replacement. Ph.D.Thesis. Cornell Univ., Ithaca, NY.

Taylor, C. C., and M. S. Allen. 2005. Corn grain endospermtype and brown midrib 3 corn silage: Site of digestion andruminal digestion kinetics in lactating cows. J. Dairy Sci.88:1413-1424.

Voelker, J. A., and M. S. Allen. 2003. Pelleted beet pulpsubstituted for high-moisture corn: 1. Effects on feed intake,chewing behavior, and milk production of lactating dairycows. J. Dairy Sci. 86:3542-3552.

Weiss, W. P., N. R. St-Pierre, and L. B. Willett. 2009. Varyingtype of forage, concentration of metabolizable protein, andsource of carbohydrate affects nutrient digestibility andproduction by dairy cows. J. Dairy Sci. 92: 5595-5606.

93

Most consumers today have no direct relationship tolivestock producers. Many have a close relationshipwith their pets and love animals… so they want toknow how animals are cared for on the farm. There isa need to reassure them that producers care for theiranimals.

There have been various recent examples ofundercover footage of dairy animal abuse appearingin the news, such as ABC Nightline, and videos, e.g.,one from PETA depicting poor welfare conditions at aPennsylvania dairy farm. These are extreme cases,and definitely not the norm. Consumers can getinfluenced by this negative propaganda about thedairy industry.

The industry is taking a proactive approach inrelation to dairy welfare and in October 2009, theNational Milk Producers Federation and DairyManagement Inc. announced their new NationalDairy FARM (Farmers Assuring ResponsibleManagement) Dairy Well-Being Program. Goals ofthis program include demonstrating to retailers andconsumers that dairy producers are using bestpractices in animal care and providing uniformityand consistency for these practices across the U.S.Uniformity is one of the advantages of a nationalprogram.

The program includes three stages: 1) education andself-assessment, 2) evaluation, and 3) third-partyverification. Educational workshops will be offeredin Minnesota later this year with the goal ofinforming dairy producers, nutritionists,veterinarians, and other dairy professionals about theFARM program and some of the areas that will beevaluated on the farm. The workshops will helpproducers and their advisors conduct a self-assessment of their dairy. Educational informationwill also be available at the FARM website. For thesecond stage, each farm will be evaluated once everythree years by a second party evaluator, who couldbe the herd veterinarian or milk coop field personnelor other professionals familiar with the dairy. Astatistical sample of all dairy farms on the programwill be selected every year, starting in late 2011 or2012, to have third-party verification by arepresentative who is not involved with the dairy. Allthe information collected from each farm remainsconfidential and only overall summaries will beavailable publicly.

Areas assessed in the FARM program includestandard operating procedures, training and recordkeeping, calf care, animal health, nutrition,environment and facilities, handling, movement andtransportation, special needs animals, and dairy beef.The recommended best practices or guidelines aresummarized in the Quick Reference User Guide, andmore detail is provided in the animal care manual,both available at the FARM website:www.nationaldairyfarm.com.

Most producers are already addressing the areas tobe evaluated in the program. For example, one of thechecklist items is ‘calves receive colostrum or colostrumreplacement soon after birth’. This is already beingdone because all producers want healthy, productivecalves. Another item is ‘the dairy has aVeterinarian/Client/Patient relationship’. I don’t know ofmany dairies in Minnesota not working with aveterinarian and not having a health plan for theiranimals. ‘Rations should provide the required nutrientsfor maintenance, growth, and lactation’. Again, that isgood for the cow and for the business. ‘Freestallbedding is refreshed (remove soiled sand or other beddingmaterial) and fresh bedding is added on a routine basis’.Hopefully that is also standard protocol in all ourdairies. ‘Adequate lighting is in place to allow inspectionof animals and to provide safe working conditions’. Withvery few exceptions, all dairy barns and parlors arewell lit. The list goes on.

When producers do the self-assessment or have theevaluation by the second party, there might be somepractices that are not being done on the dairy, maybesome standard protocols need to be developed, orbetter care provided to special needs animals, ormaybe more training for the workers on animalhandling. This provides an opportunity to furtherimprove animal care.

Some of the numbers suggested in the guide foroutcome-based measurements (such as locomotion,hock lesion and hygiene scores) are only guidelinesand not standards. For example, research has shownthat the prevalence of lameness in freestall Minnesotaand Wisconsin dairy herds averaged approximately25% (Espejo et al., 2006; Cook et al., 2003) not 10% asit is recommended in the FARM guide. The samegoes for hock lesions, that averaged for variousstudies we did in the Midwest at 67% for freestallswith mattresses, 47% for freestalls with deep beddedmanure solids, 30% for freestalls with sand, and 11%for compost bedded pack barns. The FARM

94

FARM Dairy Well-Being ProgramMarcia I. Endres

University of Minnesota

recommendation is less than 10%. Producers don’thave to fret about these suggested numbers forlocomotion and hock lesion prevalence. They areguidelines that might be re-evaluated in a few years,and maybe long term goals, not requirements.

FARM is not an audit program or certificationprogram or a marketing tool. It is an evaluationopportunity and an organized and consistentapproach to ‘document’ across the nation thatproducers provide good care for their animals, soconsumers and retailers can have their reassurancewhen purchasing dairy products.

If we all work together to evaluate and improveanimal care everyone wins – the cow, the producer,and the consumer (who wants to be assured goodcare is the standard on farms). It is not easy to makea national program work, but we recommend thatproducers participate on the FARM program, so itwill work and be of benefit to the dairy industry.

References:Cook, N. B. 2003. Prevalence of lameness amongdairy cattle in Wisconsin as a function of housingtype and stall surface. J. Am. Vet. Med. Assoc.223:1324-1328.

Espejo, L.A., M.I. Endres, and J. A. Salfer. 2006.Prevalence of lameness in high-producing Holsteincows housed in freestall barns in Minnesota. J. DairySci. 89:3052-3058.

95

Take Home Messages• It is unclear how new milk replacer antibiotic

regulations will affect calf growth efficiency andhealth.

• Numerous bio-active feed additives are availablethat may improve calf gut health and result inimprovements in efficiency of growth and calfhealth.

• Future calf research should focus on determiningwhich combination of these bio-active feedadditives offer the best health and growthbenefits for milk replacer fed dairy calves

IntroductionDespite many years of research and improvements incalf nutrition too many producers struggle with calfhealth. According to the 2007 USDA-NAHMSsurvey, mortality rates in unweaned heifers were 7.8percent. Of this nearly eight percent mortalities,scours (56.5%) and respiratory illness (22.5%) werethe most frequently cited causes. Implementing newstrategies that show benefits in human and otherlivestock neonates may be useful in developingnutritional strategies to improve dairy calf health.The aim of this proceedings paper is to describe newdietary modifications that may improve calfperformance and health.

During the nursery phase, dairy calves aresusceptible to many pathogens. Traditionallyantibiotics were added to milk replacer to lower calfmortality, reduce the incidence of scours, andimprove feed efficiency. Calf feeders andnutritionists have expressed concern over new FDAregulations changing the continuous use of a 2:1 ratioof neomycin sulfate:oxytetracycline (NT) medicatedmilk replacers. Previous NT approved use inmedicated milk replacers was for concentrations of200-400 g/ton neomycin and 100-200 g/tonoxytetrocycline. Within this system of antibiotic use,calves were fed the 2:1 ration of NT therapythroughout the milk replacer feeding period for thetreatment of bacterial enteritis (scours) on acontinuous basis. As of April 1, 2010, 2:1 NT milkreplacers were no longer allowed to bemanufactured.

Under the newly approved regulation, there will betwo weight based options for the medication of milkreplacer feeding programs. The first option iscontinuous feeding of a dose of 1:1 ratio of NT at afeeding rate of 0.05 to 0.10 mg /lb of bodyweight.The lower dose concentration will be 8-16 g/ton ofeach antibiotic versus the previously approved 100-200 g/ton neomycin and 200-400 g/tonoxytetracycline. The FDA indication for this low rateof feeding protocol is labeled for increased rate ofweight gain and improved feed efficiency. Thesecond option under the new milk replacermedication standards permits manufactures tomarket products for the treatment of clinical bacterialenteritis (scours) caused by E. Coli and/or bacterialpneumonia caused by P. multocida. Administered onthe basis of calf weight, this treatment will deliverfive to ten times more antibiotic therapy than theprevious 2:1 NT program. This higher concentrationantibiotic program is labeled to be fed continuouslyfor 7 to 14 days. During this therapeutic treatmentperiod, medication will be added to the non-medicated milk replacer so that 1:1 NT treatment (10mg/lb of body weight) will be consumed daily.Assuming a 100 lb calf consuming 1 to 1.25 lb of milkreplacer powder daily, this equates to 16 to 20 g ofNT per ton of milk replacer. Producers will need toeither handle two separate milk replacers (low andhigh antibiotic) or use an add-pack to add NT 1:1 forcalves needing treatment. It will be increasinglyimportant for producers, nutritionist andveterinarians to work together to ensure that calvesare being treated correctly.

Impact of new antibiotic regulations on animal performanceAntibiotics in milk replacers were clearly effective inimproving performance and health of calves (Morrillet al., 1977; Quigley et al., 1997; Heinrichs et al., 2003;Berge et al., 2005). Situations with poor sanitation orwhere environmental stressors and poor nutritionplace extra burdens on calves likely benefited themost from medicated milk replacer programs (Bergeet al., 2005). Concerns from producers andnutritionists have been expressed regarding lag timebetween identification of clinical symptoms, additionof NT to milk replacer, and effective treatment ofbacterial scours. The new regulations will have theleast impact on dairy producers that place a premium

96

Dairy calf liquid feeding strategies to copewith new antibiotic use regulations

Noah B. LitherlandUniversity of Minnesota

Department of Animal ScienceSt. Paul, MN

on sanitation, bio-security, bedding quality, and feeda quality nutrition program. Calves may be moresusceptible to disease during different seasons of theyear depending on air quality and thermal stressabatement strategies.

One important take home message is that antibioticsdo not offer protection from rotavirus, coronavirus,coccidia or cryptosporidia which are the most prevalentcauses of dairy calf scours. These viruses andparasites are not bacteria and therefore are notsusceptible to antibiotics. Results from bacterial scourscases submitted to the University of MinnesotaVeterinary Diagnostic Laboratory are summarized inTable 1. Results from these clinical cases indicate that74% (450/606) tested positive for at least onepathogen. The most common pathogen cultured wascryptosporidium followed by rotavirus. Calf feeding andmanagement strategies should be designed to reducerisk factors associated with all major pathogens.

Table 1. University of Minnesota Veterinary Diagnostic lab2006 case summary for fecal cultures from dairy calves withscours (Source: Dr. Jeremy Schefers).

Feed additives and feeding strategies toimprove efficiency of growth and healthMany feed additives for milk replacer and calf starteras well as management strategies have beenemployed to improve calf performance and health. Itis plausible that combinations of feed additives mayprovide an additive response to promote calf healthand growth. There is a need to identify affordableand effective combinations of these compounds anddetermine their effectiveness within a diversenutrition and management scenarios. Table 2contains a partial description of some commerciallyavailable milk replacer additives, the pathogens theymay have an effect on, purported benefits, and somereferences using these products in controlled researchstudies. Drackley (2008) suggested that theeffectiveness of additives may be enhanced if testedin calves fed more biologically normal amounts ofmilk or milk replacer. Applications of feed additivetechnology for milk fed dairy calves will likelybecome more important as group feeding usingautomated calf feeders becomes more common.Automated calf feeders have the capability of

detecting early signs of poor calf health and mayincrease the sensitivity of detecting calf-hood disease.Additionally automated calf feeding systems can beequipped with dosing equipment to deliver specifictreatments to calves on an individual basis. Thisoption may become a powerful tool to individuallytreat calves and prevent reduce the impact of diseaseoutbreaks. Controlling enteric disease challenges ingroup housed calves will likely continue to becomean important consideration for calf welfare.

Altering the fatty acidcomposition of milk replacerMilk fat in milk replacer typically comes from lard,tallow, or white grease. While more affordable, thefatty acid profile of these sources of fat and milk fathave some dissimilarities. Milk replacer is higher inC16:0, C18:0, and C18:1 and lower in C4:0, C18:2, andC18:3. Several of the fatty acids that are in lowerquantities in milk replacer compared to milk fat haveproperties related to health, antimicrobial properties,and growth. Butyric acid (C4:0) or butyrate is animportant short chain fatty acid (SCFA) fordevelopment of the rumen and health anddevelopment of the lower gut. Butyrate is a naturallyoccurring organic acid that is present in cow’s milk ata concentration of 0.15-0.20 g/L and is normallyreleased from milk triglycerides in the abomasum asa result of the action of preintestinal lipases (Bugaut,1987). Muscato et al. (2002) found that newborndairy calves given daily doses of autocalved rumenfluid gained more weight and had a reducedincidence of scours compared with controls.Butyrate, along with many other components, mighthave been responsible for these benefits.

97

SCFA’s are produced by microbes in the rumen andin the large intestine and appear to have a role ingrowth, digestibility, feed efficiency, cell proliferationand differentiation, and function of the GI tract. Thepresence of SCFA in the intestinal lumen is importantfor; structural and functional development (includingtight junction assembly and maintenance), nutrientabsorption, and osmolarity regulation. In the lowergut, butyrate may help in modifying immune andinflammatory responses and influence intestinalmicro-flora. Human research indicates that butyrateenhances the intestinal barrier by facilitating tightjunction assembly (Peng et al., 2009). Hill et al. (2007)supplemented 1% sodium butyrate (4.4 g/calf/d) inmilk replacer and observed a significant increase inbody weight gain and a reduction in abnormal fecalscores. Researchers in France recently fed 0.3% of thediet as crystalline sodium-butyrate and observedimprovements in starter intake, increased reticuo-rumen development, and improved fecal consistency(Gorka et al., 2009). When compared withflavomycin (antibiotic) calves supplemented with 3 gof sodium-butyrate weighed more at 145 days andhad lower feed to gain from day 60 to 124 and day 13to 145 (Guilloteau et al., 2009).

Supplementing milk replacer with long-chain fattyacids is an option to deliver these fatty acids insimilar proportions to that contained in milk fat.Determining the source, fatty acid profile, andamount of these supplemental fatty acids may bechallenging. Work conducted to evaluate calfperformance when vegetable oils are included in milkreplacer has demonstrated variable calf response tofatty acid composition of supplemental fat. Grauletet al. (2000) reported similar gains for calved fedtallow or coconut oil. Jenkins et al. (1985) observedequivalent performance for tallow and coconut oilsbut markedly poorer results for corn oil. Huuskonenet al. (2005) demonstrated similar rates of gain forcalves fed tallow or a combination of palm, coconut,and rapeseed oil compared with tallow. Canola andrapeseed oil contain considerable amount of linolenicacid (C18:3) Jenkins and Kramer, (1986) indicatedthat supplementing linoleic and linolenic acid, didnot alter calf performance, however, the authorsconcluded that these fatty acids may play animportant role in stressed calves. Similarly, Hill et al(2007) determined that formulating the calf milkreplacer to increase the concentration of SCFA (C4:0),medium-chain (C8:0, C10, C12:0, and C14:0) andessential fatty acids (C18:3) above what is found inmilk replacer containing animal fat reduced thenumber of days with abnormal fecal scores andimproved ADG in calves. More recently, Hill et al.(2009) determined that supplementing C18:3 (linoleicacid) as a calcium salt of flax oil to starter in clavesless than 3 months old resulted in increased ADG and

feed efficiency. Recent advances in the area offunctional foods and neutraceuticals have resulted inthe generation of a number of human food products.Perhaps these fatty acids have a place in milkreplacer.

LactoferrinLactoferrin is a bioactive glycoprotein iron bindingcompound normally present in colostrum and milk(Masson and Heremans, 1971). Bovine colostrumcontains about 2 mg/mL lactoferrin and milkcontains a much lower concentration of 20 to 200Ìg/ml (Masson and Heremans, 1971). Lactoferrin hasbacteriostatic activities against E. Coli (Teraguchi etal., 1994) and rotavirus (Superti et al., 1997), whichmay help reduce colonization in the GI tract of calves.Since lactoferrin is present in the mammary gland asa potential antimicrobial protein, Robblee et al. (2003)hypothesized that it may serve a dual role inprotecting the mammary gland and the gut of theneonatal calf. Roblee et al. (2003) noted someimprovements in average daily gains, fecal scores,and reduced morbidity in preweaned calves withsupplementation of 3 g/d lactoferrin. Addinglactoferrin (1 g/d) to milk replacer did not alter fecalscores or improvement performance in conventionalor accelerated milk replacer programs (Cowles et al.,2006).

PrebioticsPrebiotics are defined as “a nondigestible foodingredient that beneficially affects the host byselectively stimulating the growth and/or activity ofone or a limited number of bacteria.” Gibson andRoberfroid, 1995. Published research (Heinrichs etal., 2003; Quigley et al., 2002; Donovan, 2002) haveshown an inconsistent impact of prebiotics on healthand performance of calves. The impact of prebioticson immune function has not yet been clearlyestablished. Effects of these products might be bestpositioned after treatment of calves followingantibiotic treatment for 7 to 14 days with 10 mg/lb ofbody weight dose of 1:1 NT. These prebiotics mayprovide an opportunity for re-growth of normalintestinal flora following antibiotic treatment.

ProbioticsProbiotic is a general term defined as a “livemicrobial feed supplement which beneficially affectsthe host animal by improving its intestinal balance.”According to Yoon and Stern (1995), this term refersto microbial cultures, enzyme preparations andculture extracts. Most probiotic research has beenconducted using direct fed microbials (DFM) whichare “a source of live naturally occurringmicroorganisms” (Krehbiel et al., 2003). The mode ofaction of DFM in dairy calves is not clear; however,performance and health benefits are most likely

98

observed when DFM are fed to stressed calves(Lesmeister et al., 2004; Seymour et al., 1995; Galvaoet al., 2005; Magalhãs et al., 2008). Probiotics likelychange the micro-ecology of the gut throughcompetitive inhibition. Research evaluating theimpact of DFM on immune function in calves islimited. Timmerman et al. (2005) demonstrated thatstressed calves had higher average daily gain andfeed efficiency.

Essential OilsEssential oils are “blends of secondary metabolitesobtained from the plant volatile fraction by steamdistillation.” (Calsmaiglia, 2007). The main mode ofaction of essential oils is as antimicrobials with theirmode of action through effects on the cellmembranes. Essential oils with antimicrobial activityinclude garlic, dill, paprika, cassia, juniper, tea tree,oregani, anise, rosemary, clove, thyme and ginger.Alicin, a component of garlic, is of particular interestas it inhibits bacterial growth by binding to theenzyme alcohol dehydrogenase and also hadantioxidant effects. The majority of researchconducted with essential oils has been conducted invitro with limited published research available incalves. Published research (Hill et al., 2007, Bampidiset al., 2006 and Olson et al., 1998) does not stronglysupport the use of essential oils as alternatives toantibiotics, but does show some interesting potentialbenefits.

Fructooligosaccharides (FOS)FOS belongs to a family of oligosaccharidesconsisting of several ‚-(1-2) or ‚-(1-6) linked fructoseresidues. FOS acts as a selective substrate that maystimulate the growth of bifidobacteria resulting incompetition for pathogens. FOS may modify theenvironment of the gastrointestinal tract byincreasing fermentable fiber, resulting in productionof short-chain fatty acids. May et al. (2004)demonstrated that FOS prevented gut colonization ofClostridium difficile. Additionally, Webb et al. (1992)measured greater weight gains by adding FOS tomilk replacer.

Challenges with interpreting health dataInterpreting the effects of dietary supplements on calfhealth can be difficult. Quigley (2002) the attributesof well designed experiments evaluating alternativesto antibiotics including; negative and positivecontrols, sufficient number of animals, an indicationof passive immune status, an indication of theimmunological challenge on the animal during thetest, measure of environmental effects, measurementsthat can detect treatment differences, a completedescription of methods, and proper interpretation ofthe data. Designing, conducting, and interpretingexperiments with alterations in health as the outcome

of interest are challenging. Most university researchherds are inadequately sized to achieve anappropriate statistical power to detect differences intreatments for most health variables.

SummarySignificant changes in FDA regulations regarding theuse of antibiotics in milk replacer offers anopportunity to reexamine milk fed calf nutrition.Our goal should be to continue to discover feedingand management strategies to optimize the efficiencyof calf growth while continuing to improve healthand welfare. Discovering new feed additives or feedadditive combinations will offer more tools toaccomplish this goal. Research should continue totest additives in university trials to understand modeof action and also in on-farm studies to determineanimal response with greater calf numbers andsubsequent economic impact.

ReferencesBampidis, V. A., V. Christodoulou, P. Florou-Paneri, and E.Christaki. 2006. Effect of dried oregano leaves versusneomycin in treating newborn calves with colibacillosis. J.Vet Med A Physiol Clin Med. 53:154-156.

Berge, A. C. B., T. E. Besser, D. A. Moore, and W. M. Sischo.2009. Evaluation of the effects of oral colostrumsupplementation during the first fourteen days on health andperformance of preweaned calves. J. Dairy Sci 92:286-295.

Berge, A. C., P. Lindeque, D. A. Moore, and W. M. Sischo.2005. A clinical trial evaluating prophylactic andtherapeutic antibiotic use on health and performance ofpreweaned calves. J. Dairy Sci. 88:2166-2177.

Bielmann, V., T. J. DeVries, S. J. LeBlanc, K. Lissemore, andK. E. Leslie. 2009. Evaluation of supplemental driedbovine colostrum in milk replacer fed dairy calves. J. DairySci. Vol 92, E-Suppl. 1. 127.

Bugaut, M. 1987. Occurrence, absorption and metabomismof short chain fatty acids in the digestive tract of mammals.Comp. Biochem Physio B. 86:439-492.

Calsmaiglia, S., M. Busquet, P. W. Cardozo, L. Castillejos, A.Ferret. 2007. Invited review: Essential oils as modifiers ofruminal microbial fermentation. J. Dairy Sci. 90:2580-2595.

Cowles, K. E., R. A. White, N. L. Whitehouse, and P. S.Erickson. 2006. Growth characteristics of calves fed anintensified milk replacer regimen with additionallactoferrin. J. Dairy Sci. 89:4835-4845.

Donovan, D. C., S. T. Franklin, C. C. L. Chase, and A. R.Hippen. 2002. Growth and health of Holstein calves fedmilk replacers supplemented with antibiotic orenteroguard. 2002. J. Dairy Sci. 85:947-950.

Drackley, J. K. 2008. Calf nutrition from birth to breeding.Vet. Clin. Food Anim. 24:55-86.

Galvão, N. K., J. E. P. Santos, A. Coscioini, M. Villaseñor, W.M. Sischo, A. C. B. Berge. 2005. Effect of feeding live yeastproducts to calves with failure of passive transger onperformance and patterns of antibiotic resistance in fecalEscherichia coli. 2005. Reprod. Nutr. Dev. 45:427-440.

99

Gorka, P. Z. M. Kowalski, P. Pietrazak, A. Kotunia, R.Kiljanczyk, J. Flaga, J. J. Holst, P. Guilloteau, and R.Zabielski. 2009. Journal of Physiology and Pharmacology.60:47-53.

Graulet, B., D. Gruffat-Mounty, D. Durand, and D.Bauchart. 2000. Effects of milk diets containing beef tallowor coconut oil on the fatty acid metabolism of liver slicesfrom preruminant claves. Br. J. Nutr. 84:309-318.

Guilloteau, P., R. Zabielski, J. C. David, J. W. Blum, J. A.Morisset, M. Biernat, J. Wolinski, D. Laubitz, and Y. Hamon.2009. Sodium-butyrate as a growth promoter in milkreplacer formula for young calves. J. Dairy Sci. 92:1038-

Heinrichs, A. J., C. M. Jones, B. S. Heinrichs. 2003. Effectsof mannan oligosaccharides or antibiotics in neonatal dietson health and growth of dairy calves. J. Dairy Sci. 86:4064-4069.

Hill, T. M., H. G. Bataeman III, J. M. Aldrich, and R. L.Schlotterbeck. 2009. Effects of changing the essential andfunctional fatty acid intake of dairy calves. J. Dairy Sci92:670-676.

Hill, T. M., J. M. Aldrich, R. L. Schlotterbeck, and H. G.Bateman, II. 2007. Effects of changing the fat and fatty acidcomposition of milk replacers fed to neonatal calves. TheProfessional Animal Scientist. 23:135-143.

Huuskonen, A., H. Khalili, J. Kiljala, E. Joki-Tokola, and J.Nousiainen. 2005. Effects of vegetable fats versus lard inmilk replacers on feed intake, digestibility, and growth inFinnish Ayrshire bulls calves. J. Dairy Sci. 88:3575-3581.

Jenkins, K. J. 1988. Factors affecting poor performance andscours in preruminant claves fed corn oil. J. Dairy Sci.71:3013-3020.

Jenkins, K. J. and J. K. G. Kramer. 1986. Influence of lowlinoleic and linolenic acids in milk replacer on calfperformance and lipid in blood plasma, heart, and liver. J.Dairy Sci. 69:1374-1386.

Jenkins, K. J., J. K. G. Kramer, and D. B. Emmons. 1986.Effect of lipids in milk replacer on calf performance andlipids in blood plasma, liver, and perirenal fat. J. Dairy Sci.69:447-459.

Jenkins, K. J., J. K. G. Kramer, F. D. Sauer, and D. B.Emmons. 1985. Influences of triglycerides and free fattyacids in milk replacers on calf performance, blood plasma,and adipose lipids. J. Dairy Sci. 68:669-680.

Jenny, B. F., H. J. Vandlijk, and J. A. Collins. 1991.Performance and fecal flora of calves fed a Bacillus subtilisconcentrate. J. Dairy Sci. 74:1968-1973.

Krehbiel, C. R. S. R. Rust, G. Zhang and S. E. Gilliland.2003. Bacterial direct-fed microbials in ruminant diets:Performance response and mode of action. J. Anim. Sci.81:E120-132.

Lesmeister, K. E., A. J. Heinrichs, M. T. Gabler. 2004.Effects of supplemental yeast (Saccharomyces cerevisiae)culture on rumen development, growth characteristics, andblood parameters in neonatal dairy calves. J. Dairy Sci.87:1832-1839.

Mason, P. L., and J. F. Heremans. 1971. Lactoferrin in milkfrom different species. Comp. Biochem. Physop. 39B:119-129.

Magãlhas, V.J., F. Susca, F.S. Lima, A. F. Branco, I. Yoon, andJ. E. Santos. 2008. Effect of feeding yeast culture onperformance, health, and immunocompetence of dairycalves. J. Dairy Sci. 91:1497-1509.

May, T., R. I. Mackie, G. C. Fahey, J. C. Cremin, and K. A.Garleb. 1994. Effect of fiber source on short-chain fattyacid production on growth and toxin production by Cl.Difficile. Scand. J. Gastroentestinol. 29:916-922.

Morrill, J L., A. D. Dayton, R. Mickelson. 1997. Culturedmilk and antibiotics for young calves. J Dairy Sci. 60:1105-1109.

Muscato, T. V., L. O., Tedeschi, and J. B. Russell. 2002. Theeffect of ruminal fluid preparations on the growth andhealth of newborn, milk-fed dairy calves.

Olson, E. J., W. B. Epperson. D. H. Zeman. 1998. Effects ofan allicin-based product on cryptosporidiosis in neonatalcalves. J. Am Vet Med Assoc. 212:987-989.

Quigley, J. D., T. A. Wolfe, and T. H. Elsasser. 2006. Effectsof additional milk replacer feeding on calf health, growth,and selected blood metabolites in calves. J. Dairy Sci.89:207-216.

Quigley, J. 2002. Calf note #89 Evaluating the use ofantibiotic alternatives. (http://www.calfnotes.com) Pages1-5.

Quigley, J. D. III and M. D. Drew. 2000. Effects of oralantibiotics or bovine plasma on survival, health and growthin dairy calves challenged with Escherichia coli. Food andAgricultural Immunology. 12:311-318.

Quigley, J. D. III, J. J. Drewery, L. M. Murray, and S. J. Ivey.1997. Body weight gain, feed efficiency, and fecal scores ofdairy calves in response to galactosyl-lactose or antibioticsin milk replacer. J. Dairy Sci. 80:1751-1754.

Peng, L. Z. R. Li, R. S. Green, I. R. Holzman, and J. Ling.2009. Butyrate enhances the intestinal barrier by facilitatingtight junction assembly via activation of AMP-activatedprotein kinase in Caco-2 cell monolayers. J. Nutr. 139:1619-1625.

Robblee, E. D., P. S. Erickson, N. L. Whitehouse, A. M.McLaughlin, C. G. Schwab, J. J. Rejman, and R. E. Rompala.2003. Supplemental lactoferrin improves health andgrowth of Holstein calves during the preweaning phase. J.Dairy Sci 86:1458-1464.

Seymour, W. M., J. E. Nocek, J. Siciliano-Jones. 1995.Effects of a colostrum substitute and of dietary brewer’syeast on the health and performance of dairy calves. J.Dairy Sci. 78:412-420.

Superti, F., M. G. Ammendolia, P. Valenti, and L. Seganti.1997. Antirotaviral activity of milk proteins: lactoferrinprevents rotavirus infection in the enterocyte-like cell lineHT-29. Med. Microbiol. Immunol. 186:83-91.

Teraguchi, S., K. Ozawa, S. Yasuda, K. Shin, Y. Fukuwatari,and S. Shimamura. 1994. The bacteriostatic effects of orallyadministered bovine lactoferrin on intestinalEnterobcteriacae of SPF mice fed bovine milk. Biosci.Biotech. Biochem. 58:482-487.

Timmerman, H. M., L. Mulder, H. Everts, D. C. van Espen,E. van der Wal, G. Klaassen, S. M. G. Rouwers, R.Hartemink, F. M. Rombouts, and A. C. Beynen. 2005.

100

Health and growth of veal calves fed milk replacer with orwithout probiotics. J. Dairy Sci. 88:2154-2165.

Webb, P. R., D. W. Kellogg,M. W. McGahee, and Z. B.Johnson. 1992. Addition of fructooligosaccharides (FOS)and sodium diacetate (SD) plus decoquinated (D) to milkreplacer and starter grain fed to Holstein calves. J. DairySci. 75:293. (Abstr.).

Weinberg, E. D. 2001. Human lactoferrin: a noveltherapeutic with broad spectrum potential. J. Pharm.Pharmacol. 53:1303-1310.

Yoon, I. K. and M. D. Stern. Effects of Saccharomycescerevisiae and Aspergillus oryzae cultures on ruminalfermentation in dairy cows. 1995. J. dairy Sci. 79:411-417.

101

Take Home Messages• Culling and transporting decisions are an

important part of dairy farming. • Occasionally, an animal that is ambulatory on the

farm may not be suitable for transport to a packingor processing facility.

• Consider the “Top 10 Considerations for Cullingand Transporting Dairy Animals to a Packing orProcessing Facility” to make appropriate decisionson the suitability of an animal to be shipped.

• All production animals eventually become marketanimals.

Within the food production system, dairy producerswear several “hats.” The largest and most obvious“hat” is the production of raw milk shipped from thedairy operation. The quality of the raw milkproduced will not improve once it has been harvestedfrom the cows. Every effort should be made topresent the highest quality, most wholesome productto the milk processor. A less obvious “hat” that dairyproducers wear is the generation of calves and cowsfor the beef market. Cull cows and bull calves canrepresent between 10-15 percent of the gross farmincome. With proper management and timelymarketing, the value of market cows and bull calvescan be increased. This paper will focus on theconsiderations dairy producers must make whenculling and transporting cattle from their operations.

The National Milk Producers Federation has publisheda document outlining the “Top 10 Considerations forCulling and Transporting Dairy Animals to a Packingor Processing Facility.” Leaders in the dairy industryhave been working on a dairy beef quality assuranceprogram for years. The Humane Society of the UnitedStates release of the Heartland Packing Plant videoshowing inhumane treatment of dairy cattlepropagated the release of this document.

1. Do not move non-ambulatory animals to marketunder any circumstances. (Only allow ambulatoryanimals to be shipped to market).

2. Make the decision to treat, to cull, or to euthanizeanimals promptly. Sick and injured animalsshould be segregated from the herd.

3. Delay transport of an animal that appears to beexhausted or dehydrated until the animal isrested and re-hydrated.

4. Milk all cows that are still lactating just prior totransporting to a packing or processing facility.

5. Use a transportation company that isknowledgeable about your animal careexpectations and provides for the safety andcomfort of the animals during transport.

6. Do not transport animals to a packing orprocessing facility until all proper treatmentwithdrawal times have been followed.

7. Do not transport animals with a poor bodycondition, generally a Body Condition Score of less than 2 (1-5 scale).

8. Do not transport animals that require mechanicalassistance to rise and are reluctant or unable towalk, except for veterinary treatment. When usingany handling device, abuse must not be tolerated.

9. Do not transport animals with bone fractures ofthe limbs or injuries to the spine. Animals with arecent fracture unrelated to mobility should beculled and transported directly to a packing orprocessing facility.

10. Do not transport animals with conditions that willnot pass pre-slaughter inspection at a packing orprocessing facility. If unsure, consult with yourveterinarian before transporting an animal to apacking or processing facility.

The dairy industry needs to shift our thoughtprocesses regarding the classification of surplusanimals. There are actually two classes of animals ondairy farms, production animals and market animals.Production animals would include lactating cows,dry cows, replacement heifers and potentially bullsfor breeding. Market animals would include cullcows and bull calves. All production animalseventually become market animals! To that end, thedairy industry should discontinue using terms likecull, spent, salvage, junk and surplus, and beginusing the term market when referring to animals thatare no longer economically productive.

Market cattle, non-fed beef and dairy animals supply20 percent of the total beef produced in the UnitedStates. In 1998, 2.5 billion pounds of market cow beefwas produced in the U.S. with nearly half of thatamount from dairy cows. Almost three quarters ofthe market cow beef is destined for processed beefproducts. Most dairy producers assume that themajor product from market cows is ground beef soldas hamburgers through fast-food restaurants. Inreality, ground beef is a very important product frommarket cattle, but it is only one of many products.Depending upon the operation, market cow packers

102

Improving the Value of Cull CowsRichard L. Wallace, DVM, MSDairy Extension Veterinarian

University of Illinois

utilize tenderloins, ribeyes and strip loins,particularly from younger cows as well as the hideand many other inedible products.

The decision to market a cow is a complex one. Whenmaking a marketing decision, dairy producers mayconsider many cow factors, such as age, stage oflactation, milk production, health status, disposition,and reproductive performance. Other economicfactors such as current milk price, market cow price,as well as cost and availability of replacement heifersmay have a role in determining whether or not tomarket a cow.

Dairy cow marketing decisions have an importantinfluence on the financial success of the dairy.Marketing decisions can function as a component ofgenetic improvement programs designed for long-term gain and improved production efficiency(voluntary marketing). At the same time, marketingmay also represent failure or limited success of healthprograms resulting in cows leaving the herdprematurely due to death, disease or health-relatedproblems (involuntary marketing).

Annual market rates for DHIA Holstein herd herds inIllinois and the Midwest as of September 2008 areshown below. The data is averaged for the bottom,middle and top third of herds based on rolling herdaverage milk production.

Location/RHA < 18,000 18,001-22,000 > 22,001Illinois 33.4 (126) 36.4 (172) 36.1 (107)Midwest 34.3 (1583) 35.2 (2508) 36.3 (2271)

Marketing decisions are important from severaldifferent perspectives. Costs for replacement heifersmay represent up to 20 percent of the dairy operatingbudget (Fetrow 1988, AABP). Negative cash flowsoccur when a cow is sold for beef and a heifer isadded to the lactating herd as a replacement. Cowsretained in the herd represent capital investments,which are subject to various forms of risk that mayalter the earnings from those investments. Cowshave different risks of being marketed depending ontheir age. Although there is a tendency for increasedmarketing rates with advancing age, managementconstraints and biases can modify this relationship.The typical cow remains in the milking herd less than4 years even though peak milk production related tomaturity ordinarily does not decline until 8 or 9 yearsof age. The reluctance of some producers to marketfirst calf heifers and choosing instead to give them asecond chance is an example of management biasaffecting marketing policy.

A recent study (Bascom and Young, JDS 1998)summarized the reasons dairies market cows and

determined whether cows were marketed for multiplereasons. Dairy producers identified a secondaryreason for marketing 35 percent of the time, and atertiary reason for marketing 11 percent of the time.Unfortunately, DHIA data only provides the producerwith one choice when categorizing marketingdecisions. The most prevalent reason for marketingwas reproduction. Producers may be unaware of thecost associated with reproductive marketing. In herdswith less than optimal reproductive performance,dairy operators must find a balance between incomeloss caused by excessive days open and income losscaused by high marketing rates.

The second most prevalent reason for marketing wasmastitis. High somatic cell count (SCC) was rarelyused as the reason for marketing, however, clinicalmastitis was the primary reason for 15 percent of thecows marketed in this study. How producersinterpret the difference between mastitis and highSCC is unknown, and marketing for mastitis mayinclude both categories. Cows may be marketed formastitis because they never recover from chronicinfections or because of reduced milk production dueto elevated SCC.

In 1994, the National Cattlemen’s Associationperformed an audit of market beef cows, marketdairy cows, and market bulls. This study wasconducted to determine areas for improvement in themanner by which these classes of animals weremarketed. In 1999, the study was repeated to see ifthe concerns found five years previously hadchanged. Slightly over 6 million head of market cowsand bulls were assessed in the 1999 audit. In general,producers did a good job of managing and marketingsurplus animals. However, quality defects in only 1%of market cows and bulls indicate that thousands ofcattle are below acceptable standards.

On average, 3 percent of all market dairy cows arecondemned at USDA packing plants. Consideringonly emaciated and disabled cattle, over 40 percent ofthese market cows are condemned. Lameness anddisabled cattle represent a problem to the industryfrom a public perception standpoint. Many lamecattle, however, are the result of failure to marketanimals before feet and leg problems progress. Thepacker is required to remove all tissue associated withan arthritic joint. More than 7 percent of cattle had atleast one arthritic joint, and nearly 4 percent had twobad joints. With an average trim loss of 40 pounds,more than 37 million pounds of product would havebeen lost in 1999 due to joint problems alone. Packerslisted arthritis as one of their top concerns.Since lean muscle is the principal end product ofmarket cattle, it is important that market animals dohave adequate muscling and do not have excessive

103

amounts of fat. However, the 1999 audit suggestedthat over 70 percent of dairy cows were inadequatelymuscled.

Certainly, dairy cows are not genetically designed forextreme muscling, but of greater concern is that thepoor meat yield due to emaciation. Extremely thincows amounted to 4.5 percent of dairy cows harvestedin the 1999 audit. In many cases, the most valuablepart of a thin cow is her hide. Emaciated cows aremuch more prone to bruising because they have no fatto serve as padding and they are more likely to bedisabled upon arrival at the packing plant.

The primary concern of packers in the 1999 audit wasthe high incidence of bruising. Only 11.8 percent ofcow carcasses did not have a bruise (down from the1994 audit). Minor, medium, major and extremebruises results in 0.69, 1.42, 4.78 and 15 pounds oftrim loss, respectively. Using these estimates, morethan 14 million pounds of product were lost due tobruising. Unfortunately, the bruises do not just occuron the lower-valued portion of the carcass. The 1999audit revealed that trim loss was observed in the topsirloin, loin, rib, round and chuck. When a bruise iscreated on an animal, it takes time for the body toheal. Handling practices at the farm are veryimportant in minimizing bruises. It is estimated thatone-third of bruises occur on the farm and the othertwo-thirds occur in transport and marketing. Closescrutiny of handling facilities to eliminate sharp,protruding corners can help reduce bruising.Producers should also merchandise market cattlebefore they become emaciated and are moresusceptible to bruises.

Another major concern of packers was the incidenceof injection-site lesions and the potential for antibioticresidues. A recent study at Colorado State Universityrevealed that approximately 29 percent of the roundsof market cows contain an injection-site lesion. Mostof these lesions were detected in the upper portionsof the hip. These lesions do not represent a foodsafety concern, but they are a beef quality problem.Scar tissue from intramuscular (IM) injections ofantibiotics or vaccines causes the muscle tissue to betougher, producing a product that may beunacceptable to the consumer.

Producers should carefully avoid marketing cattlethat have been treated with antibiotics until thespecified withdrawal time has ended. The USDAcurrently monitors the incidence of antibiotic residuesin market cattle, and a trace-back system is already inplace through the use of back tags at the auctionbarn. In the 1994 audit, dairy cows and veal calveswere the two classes with the highest level ofviolative antibiotic residues, 1.5 and 1.8 percent,

respectively. By 1999, the violation level in dairycows had dropped to 1.1 percent (415 positives from37,308 cattle tested). Inspectors at packing plantsidentify animals to be tested both ante mortem andpost mortem. Nearly 85 percent of the residueviolations were from post mortem-identified highrisk cattle. The leading causes of antibioticcontamination included gentamycin (39%), penicillin(25%), sulfadimethoxine (12%), streptomycin (9%),tetracyclines (6%) and several others. Gentamycinmay not be as commonly used as some of these otherantibiotics, but the prolonged tissue retention mayexplain the reason this drug is at the top of the list.

When you look at the overall picture, the 1999 auditsuggests that nearly $70 is lost in value for everymarket cow or bull that is merchandised. Most of thisloss comes from merchandising thin, emaciatedanimals that are more susceptible to bruises and trimloss and have poor yields. Dairy Beef QualityAssurance (DBQA) addresses the day-to-daymanagement practices that influence safety, quality,and wholesomeness of beef and beef products.Reducing the problem starts on the dairy andsuggested changes involve seven steps.

1. Use the neck or shoulder as preferred injection site,when possible.

2. Read and understand injection product labels. 3. Avoid intramuscular (IM) injections when other

labeled administration routes are available. 4. Products approved for subcutaneous injection

should be done with the tenting technique bylifting animal hide between fingers and inject intothe “tent.”

5. Avoid mixing products as this causes more tissuedamage, reduces product efficacy, and extendswithdrawal times.

6. Ask your veterinarian about comparable tissuedamage from different products.

7. Encourage promotion of tissue reactioninformation from pharmaceutical companies thatproduce injectable products.

The first step may be the biggest obstacle. Typically,large groups of dairy cows are not run throughsqueeze chutes like beef cattle. Injections in cowstossing their heads while in the stanchion can bedangerous. Is there an economic incentive from thebuyer to justify the extra effort by the dairy personnelto reduce hindquarter injections? Tracing antibioticresidues is currently being pursued in dairy marketcow carcasses. Tracing carcass quality (injection sitelesions) back to the dairy would be needed topromote this type of quality assurance. Qualityassurance is not an all or none situation and partialimprovements could be beneficial.

104

105

The Wisconsin Dairy Feed Cost Evaluator Victor E. Cabrera

106

107

108

109

110

111

112

113

114

IntroductionHigh producing dairy cows have low reproductiveefficiency due to reduced fertility, reduced expressionof estrus, and reduced detection of estrus [1-3].Ovsynch utilizes GnRH and prostaglandin F2a tosynchronize ovulation (GnRH–7d– PGF–2d-GnRH–16h–AI) allowing timed AI [4]. Although allcows have AI during Ovsynch, fertility is generally notimproved [5-7]. Previous experiments using lactatingdairy cows [8] and dairy heifers [9] found that theideal phase to initiate Ovsynch is from Days 5 to 12 ofthe estrous cycle. Therefore, researchers developedpre-synchronization systems that increase theproportion of cows in the ideal part of the estrous cycleon the day of the first GnRH of Ovsynch. For instance,Moreira and coworkers [10] reported that two PGFtreatments 14 d apart, termed Presynch, increased thepercentage of cows in early to mid-luteal phase andimproved fertility in cycling cows when Ovsynch wasinitiated 12 d later. Anovular cows did not benefit fromPresynch [10]. Other studies using Presynch reportedimproved fertility [11,12]; although, a single treatmentwith PGF prior to Ovsynch was not effective [13].

Anovular cows have reduced fertility to timed AIfollowing Ovsynch [14-16]. On average 20 to 30% ofcows are anovular at the time Ovsynch initiation[10,14,17]. Thus, better Presynch protocols shouldstimulate cyclicity in anovular cows. The CIDR duringPresynch increased percentage of previously anovularcows that were cycling at the start of Ovsynch; but, didnot increase fertility to timed AI [16,18]. Anotherlimitation of the standard PGF-based Presynchprotocol is that follicular and luteal stages are notprecisely synchronized due to variability in time toestrus/ovulation after PGF. The G-6-G protocol [19](PGF–2d–GnRH–6d-Ovsynch) can increase ovulationto the first GnRH of Ovsynch, increase circulatingprogesterone at time of PGF, reduce variation in size ofovulatory follicle, and increase synchronization ratesduring Ovsynch[19].

Double Ovsynch (shown in Table 1) uses a completeOvsynch protocol as a presynchronization procedure.The first Ovsynch is generally initiated on Friday witha GnRH treatment followed 7 days later by a PGFtreatment. There is then a 3 day interval between the

PGF treatment and the second GnRH treatment. Thislonger interval allows the cows to come heat andhigher estradiol-17ß concentrations, potentiallycausing more contraction of the uterus and higherprogesterone during the Ovsynch protocol. This firstOvsynch is known as the presynchronizationOvsynch. The second Ovsynch is known as thebreeding Ovsynch and is done in a typical manner asthe Ovsynch-56 protocol. This paper will summarizeour results utilizing Double Ovsynch.

Table 1. Typical calendar for Double Ovsynch.

Fertility following Double OvsynchOur first study [20] compared Double-Ovsynch toPresynch-Ovsynch in two commercial dairies.Lactating Holstein (n = 337) cows, were assigned totwo treatment groups: 1) Presynch (n = 180), twoinjections of PGF 14 d apart, followed by theOvsynch-timed AI protocol 12 d later; 2) Double-Ovsynch (n = 157), received GnRH, PGF 7 d later,and GnRH 3 d later followed by the Ovsynch-timedAI protocol 7 d later. All cows received the sameOvsynch-timed AI protocol: GnRH (G1) at 68 ± 3DIM (mean ± SEM), PGF 7 d later, GnRH (G2) 56 hafter PGF, and AI 16 to 20 h later. Pregnancy wasdiagnosed 39 to 45 d after timed AI. Double-Ovsynchincreased the fertility (% pregnancy per AI) comparedto Presynch-Ovsynch (49.7% vs 41.7%, P = 0.03).Parity (primiparous vs multiparous) had an effect (P= 0.05) on percentage pregnant per AI (Table 2) withprimiparous (54.9%) having greater fertility thanmultiparous (38.5%) cows. Unexpectedly, Double-Ovsynch increased fertility only in primiparous cows(65.2% vs 45.2%; P = 0.02) with no effect of treatmentobserved in multiparous cows (37.5% vs 39.3%; P =0.58).

115

Improving Reproductive Efficiencyusing Double Ovsynch

Milo C. Wiltbank, Alexandre H. Souza, Alexandre P. Cunha, Henderson Ayres, Roberto Sartori, Julio O. Giordano,Paul M. Fricke, Robb Bender, Anibal B. Nascimento, Jerry N. Guenther

Department of Dairy Science, University of Wisconsin-Madison, Madison, WI 53706email: wiltbank@wisc.edu

Table 2. Effects of number of lactations on pregnanciesper AI (P/AI) following presynchronization with astandard Presynch protocol or Double-Ovsynch.

* P-values for comparisons of Primiparous vsMultiparous.

** P-values for comparisons of Double-Ovsynch vsPresynch.

# These analyses were done with GLIMMIX andaccounted for BCS in the model.

There was also an effect (P = 0.04) of BCS on fertility(High = 48.3% vs Low = 28.3%). This negative impactof low BCS on fertility was numerically similar inDouble-Ovsynch (20.1% decrease) and Presynch(19.5% decrease) cows. In addition, there werenumerically similar effects of Double-Ovsynch onfertility in cows with both high (Double-Ovsynch12.5% greater than Presynch; P = 0.06) and low(Double-Ovsynch 11.9% greater than Presynch; P =0.25) BCS; although, statistical differences are clearlynot detected in the small number of cows with lowBCS in this study (only 46 cows in this classification).

Physiology of Double OvsynchIn a subset of 87 cows [20], ovarian ultrasonographyand progesterone measurements were performed atthe first GnRH of the breeding Ovsynch and 7 d later(Table 3). Double-Ovsynch decreased the percentageof cows with low progesterone (< 1 ng/mL) at thefirst GnRH of the breeding Ovsynch (9.4 vs 33.3%)and increased the concentration of progesterone atthe PGF (Table 3).

Table 3. Effects of synchronization protocol onpresence of CL at 1st GnRH, ovulation to first GnRH,concentration of progesterone (P4) at first GnRH,percentage of cows with P4 concentration more than1.0 ng/mL at first GnRH, concentration of P4 at PGF,and percentage of cows with P4 concentration morethan 1.0 ng/mL at PGF (mean ± SEM).

In a second study (Ayres et al., unpublished) weevaluated the follicular dynamics and hormonalconcentrations in a greater number of cows that weretreated with Double Ovsynch compared to Presynch-Ovsynch. Lactating Holstein (n = 193) cows wereassigned to two treatment groups: 1) Presynch (n = 93),two injections of PGF2a· 14 days apart, followed by theOvsynch-timed AI protocol 12 d later; or 2) Double-Ovsynch (n = 100). In this study Double-Ovsynchdecreased the percentage of cows with low circulatingprogesterone concentration (< 0.50 ng/mL) at the firstGnRH (12.0% vs. 30.1%; P = 0.003) and increased thepercentage of cows with medium progesteroneconcentration (0.50 > P4 ≤ 3.0 ng/mL) at the firstGnRH (80.0% vs. 57.0%; P = 0.0009), with CL at thefirst GnRH (94.0% vs. 67.8%; P = 0.0003), and withhigh progesterone concentration (> 3.0 ng/mL) atPGF2a (88.0% vs. 76.3%; P = 0.04). Also, this protocolseemed to increase the ovulation rate at the first GnRH(80.0% vs. 69.9%; P = 0.11) and at second GnRH (98.0%vs. 93.5%; P = 0.08), the serum concentration ofprogesterone at PGF2a (3.52 ± 0.17 vs. 3.09 ± 0.21ng/ml; P = 0.11) and the size of the dominant follicleat G2 (15.95 ± 0.31 vs. 15.26 ± 0.32 mm; P = 0.13). Thus,presynchronization of cows with Double-Ovsynch isprobably inducing ovulation in non-cycling cows andalso improving synchronization of cycling cows.

Modifications of Double OvsynchOne of the potential problems with Ovsynchprotocols is that there may be inadequate luteolysisfollowing the single PGF treatment that is given priorto the final GnRH and timed AI. In one experiment[21] we evaluated whether a second PGF treatmentwould increase luteolysis and improve fertility (Table4). There was a dramatic improvement in percentageof cows that had complete luteolysis by the time ofthe second GnRH (86.1% to 97.5%). There was not astatistically significant improvement in fertility;although there was a 5.7 % improvement in fertilitywith the additional PGF treatment (Table 5). Thiswould be approximately the amount of improvementthat would be expected with the improvement inluteolysis rate (i.e. 11.4% of cows that did not regresstheir CL regressed after the second PGF, if 50% ofthese cows conceive then a 5.7% improvement isexpected [11.4% X 0.5 = 5.7%]). Thus, it seems likelythat an additional PGF will improve fertility inDouble Ovsynch; however a 4-6% increase is aboutthe most that can be expected.

116

Table 4. Experiment with Double Ovsynch to increaseluteolysis by adding a second PGF treatment.

Table 5. Effects of additional PGF on fertility andpercentage of cows with low progesterone (P4) atsecond GnRH of Ovsynch (< 0.5 ng/mlL).

We have recently tested whether Double Ovsynchcan be utilized as a resynchronization strategy, ratherthan just using this strategy for first AI (Giordano etal., unpublished). Table 6 shows the way that wehave used Double Ovsynch for resynchronization.The first GnRH of the protocol was done at Day 22and the pregnancy diagnosis and PGF treatment weredone at Day 29. This was compared to a Resynch-32strategy (normal Ovsynch protocol with first GnRHdone at 32 days after the previous timed AI). TheResynch-32 strategy will result in AI being done at 42days after the previous AI. The Double OvsynchResynch will result in AI being done at 49 days afterthe previous AI. In this experiment Double Ovsynchwas utilized for first AI with good fertility (46.4%;507/1092; primiparous - 53.8%, multiparous - 40.7%).During the Resynch experiment, Double Ovsynchhad much higher (P < 0.0001) fertility (38.2%;305/799) than Resynch-32 (29.9%; 242/810). Thus,Double Ovsynch can be utilized as a Resynchprocedure to improve fertility at second and later AIs;however, it produces a longer interval between AIsand requires more hormonal treatments thanResynch-32.

Table 6. Use of Double Ovsynch for resynchronizationof Ovulation.

Another modification that we have tested is toeliminate one of the GnRH treatments of the DoubleOvsynch protocol. This has been termed the shortDouble Ovsynch protocol (see Table 7). This protocolwas tested for two reasons. First, this may be a morepractical protocol for use in Resynchronizationstrategies because it could produce a shorter intervalbetween AIs (42 days rather than 49 days withDouble Ovsynch Resynch). Second, we wanted totest whether the progesterone concentration duringthe final follicular wave would alter fertility to thetimed AI. For example the short Double Ovsynchprotocol would have low progesterone concentrationsduring this final follicular wave (only one CL presentbetween GnRH and PGF of breeding Ovsynch);whereas, the normal Double Ovsynch protocolnormally has two CL present at this time due toovulation of a second CL at the first GnRH of thebreeding Ovsynch.

Table 7. Calendar for the short Double Ovsynchprotocol.

Some intriguing effects were observed in thiscomparison of the short and normal Double Ovsynchprotocols. First, the normal Double Ovsynch protocolhad a lower double ovulation rate than the shortprotocol (12.3% [32/261] vs. 23.4% [54/231]; P < 0.001).In addition, there was greater fertility with the normalDouble Ovsynch protocol than short Double Ovsynch(51.0% [149/292] vs. 37.1% [101/272]). Surprisingly,there was also a reduction in pregnancy loss in cowstreated with Double Ovsynch compared to shortDouble Ovsynch (6.8% [10/147] vs. 14.3% [14/98]; P =0.054). The decrease in double ovulation and increasein fertility occurred in both primiparous andmultiparous cows in this study. Thus, the higherprogesterone concentrations that are produced by theDouble Ovsynch protocol are critical for reducingdouble ovulation, increasing fertility, and potentiallyreducing pregnancy loss. Perhaps even greaterprogesterone concentrations would reduce doubleovulation and improve fertility to an even greaterextent.

ConclusionsIn the trials that we have performed, there has been aconsistently high fertility following the DoubleOvsynch protocol. In field observations of fertility inherds that use Double Ovsynch there is somevariability in results that have been obtained. Inalmost all herds that use Double Ovsynch there ismuch higher fertility in first lactation cows

117

(primiparous) than older cows (multiparous) similarto our observation in the published study on DoubleOvsynch [20]. The reason(s) for this difference arenot clear at this time. Further studies are needed tocontinue to evaluate and improve this protocol.Nevertheless, the surprisingly high fertility that isobserved with the Double Ovsynch protocol,particularly in first lactation cows, indicates thatenhanced timed AI protocols may be able to optimizehormonal concentrations and follicle developmentand apparently overcome much of the physiologicalbarriers to high fertility in lactating dairy cows.Unfortunately, the variability between herds indicatesthat many other problems can also reduce fertility inlactating dairy cows (insemination technique,nutrition, disease, etc.) and therefore even the mostoptimized timed AI protocols are unlikely to improvefertility in all commercial dairies.

References[1] Washburn SP, Silvia WJ, Brown CH, McDaniel BT,

McAllister AJ. Trends in reproductive performance insoutheastern Holstein and Jersey DHI herds. J Dairy Sci2002;85:244-251.

[2] Lopez H, Satter LD, Wiltbank MC. Relationship betweenlevel of milk production and estrous behavior of lactatingdairy cows. Anim Reprod Sci 2004;81:209-223.

[3] Wiltbank MC, Lopez H, Sartori R, Sangsritavong S,Gumen A. Changes in reproductive physiology of lactatingdairy cows due to elevated steroid metabolism.Theriogenology 2006;65:17-29.

[4] Pursley RJ, Mee MO, Wiltbank MC. Synchronization ofovulation in dairy cows using PGF2a and GnRH.Theriogenology 1995;44:915-923.

[5] Pursley RJ, Kosorok MR, Wiltbank MC. Reproductivemanagement of lactating dairy cows using synchronizationof ovulation. J Dairy Sci 1997;80:301-306.

[6] Cerri RL, Santos JE, Juchem SO, Galvao KN, Chebel RC.Timed artificial insemination with estradiol cypionate orinsemination at estrus in high-producing dairy cows. JDairy Sci 2004;87:3704-15.

[7] Stevenson JS, Kobayashi Y, Thompson KE. Reproductiveperformance of dairy cows in various programmedbreeding systems including Ovsynch and combinations ofgonadotropin releasing hormone and prostaglandin F2a JDairy Sci 1999;82:506-515.

[8] Vasconcelos JL, Silcox RW, Rosa GJ, Pursley RJ,Wiltbank MC. Synchronization rate, size of the ovulatoryfollicle, and pregnancy rate after synchronization ofovulation beginning on different days of the estrous cyclein lactating dairy cows. Theriogenology 1999;52:1067-1078.

[9] Moreira F, De la Sota RL, Diaz T, Thatcher WW. Effect ofday of the estrous cycle at the initiation of timed artificialinsemination protocol on reproductive responses in dairyheifers. J Anim Sci 2000;78:1568-1576.

[10] Moreira F, Orlandi C, Risco CA, Mattos R, Lopes F,Thatcher WW. Effects of presynchronization and bovinesomatotropin on pregnancy rates to timed artificialinsemination protocol in lactating dairy cows. J Dairy Sci2001;84:1646-1659.

[11] El-Zarkouny SZ, Cartmill JA, Hensley BA, StevensonJS. Pregnancy in dairy cows after synchronized ovulationregimens with or without Presynchronization andprogesterone. J Dairy Sci 2004;87:1024-1037.

[12] Navanukraw C, Redmer DA, Reynolds LP, Kirsch JD,Grazul-Bilska AT, Fricke PM. A modifiedPresynchronization protocol improves fertility to timedartificial insemination in lactating dairy cows. J Dairy Sci2004;87:1551-1557.

[13] LeBlanc SJ, Leslie KE. Short communication:Presynchronization using a single injection of PGF2a beforesynchronized ovulation and first timed artificialinsemination in dairy cows. J Dairy Sci 2003;86:3215-3217.

[14] Gümen A, Guenther JN, Wiltbank MC. Follicular sizeand response to Ovsynch versus detection of estrus inanovular and ovular lactating dairy cows. J Dairy Sci2003;86:3184-3194.

[15] Galvão KN, Santos JEP, Juchem SO, Cerri RLA,Coscioni AC, Villaseñor M. Effect of addition of aprogesterone intravaginal insert to a timed inseminationprotocol using estradiol cypionate on ovulation rate,pregnancy rate, and late embryonic loss in lactating dairycows. J Anim Sci 2004;82:3508-3517.

[16] Chebel RC, Santos JEP, Cerri RLA, Rutigliano HM,Bruno RGS. Reproduction in dairy cows followingprogesterone insert presynchronization andresynchronization protocols. J Dairy Sci 2006;89:4205-4219.

[17] Lopez HD, Caraviello DZ, Satter LD, Fricke PM,Wiltbank MC. Relationship between level of milkproduction and multiple ovulations in lactating dairy cows.J Dairy Sci 2005;88:2783-2793.

[18] Bicalho RC, Cheong SH, Warnick LD, Guard CL.Evaluation of progesterone supplementation in aprostaglandin F2a-based presynchronization protocol beforetimed insemination. J Dairy Sci 2007;90:1193-1200.

[19] Bello NM, Steibel JP, Pursley RJ. Optimizing ovulationto first GnRH improved outcomes to each hormonalinjection of Ovsynch in lactating dairy cows. J Dairy Sci2006;89:3413-3424.

[20] Souza AH, Ayres H, Ferreira RM, Wiltbank MC. A newpresynchronization system (Double-Ovsynch) increasesfertility at first postpartum timed AI in lactating dairy cowsTheriogenology 2008; 70:208–215.

[21] Brusveen DJ, Souza AH, Wiltbank MC, 2009. Effects ofadditional prostaglandin F2a and estradiol-17ß duringOvsynch in lactating dairy cows. Journal of Dairy Science92:1412-1422.

118

119

120

121

122

123

124

125

126

127

128