The Eighth International Starch Technology Conference€¦ · The International Starch Technology...

The Eighth International Starch Technology

Conference

Program Proceedings

University of Illinois Champaign, Illinois USA

June 3-5, 2013

Edited by

Kent Rausch Vijay Singh

Mike Tumbleson

Eighth International Starch Technology Conference June 3-5, 2013 University of Illinois

i

DEDICATION

Professor Mark Shannon 1955-2012

The Eighth International Starch Technology Conference proceedings is dedicated to Professor Mark Shannon. Mark Alan Shannon, MechSE professor at the University of Illinois, died on Sunday, October 14, 2012 after a three-year battle with amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig’s disease. He was 56. Dr. Shannon was a keynote speaker at the Sixth ISTC in 2009 and spoke on “Water Sustainability for Peoples of the World: Nexus to Food Production and Processing”. His presentations and papers on global demands for limited water supplies were balanced and supported by quality data. Mark A. Shannon was Director of the NSF STC WaterCAMPWS, which is a multiple university and government laboratory center for advancing the science and engineering of materials and systems for revolutionary improvements in water purification for human use. He was also Director of the Micro-Nano-Mechanical Systems (MNMS) Laboratory at the University of Illinois at Urbana-Champaign, a laboratory devoted to research and education in the design and fabrication of micro- and nanoelectromechanical systems (MEMS & NEMS), microscale fuel cells and gas sensors, high temperature microchemical reactors, micro-nanofluidic sensors for biological fluids. He chaired the Instrument Systems Development Study Session for the National Institutes of Health. He was the James W. Bayne Professor of Mechanical Engineering and received his B.S. (1989) M.S. (1991) and Ph.D. (1993) degrees in Mechanical Engineering from the University of California at Berkeley. He received an NSF Career Award in 1997 to advance microfabrication technologies, the Xerox Award for Excellence in Research (2004), the Kritzer Scholar (2003-2006), the Willet Faculty Scholar (2004-2007) and received the BP Innovation in Education Award in 2006.


ii

THE CONFERENCE The International Starch Technology Conference (ISTC) has been offered every two years since 1999. The conference is designed to facilitate interaction among international representatives from the starch processing industry, government research agencies and allied industries. Speakers from industry, research agencies and occasional academia are invited from around the world to speak and present a paper. While there are many trade expos and conferences that promote entrepreneurial efforts, and quite a few scientific conferences that focus on carbohydrate chemistry, ISTC is unique in that it focuses on research and advances in processing of cereal grains and other starch bearing crops. The International Starch Technology Conference is an entirely self supported endeavour. As such, it does not receive funding from the University of Illinois other than to support the faculty efforts in organizing the conference and editing the proceedings. Speakers and organizers do not receive reimbursement or honoraria for their contributions. There is no overarching support or project funding; conference expenses are met primarily by registration fees. As a result, we are deeply appreciative of the exhibitors and sponsors that support our conference.


iii

EXHIBITORS Please visit our exhibit area and thank them for supporting the Eighth International Starch Technology Conference:

Novozymes 77 Perry Chapel Church Road Franklinton, NC 27525 Phone: 919-494-3000 Fax: 919-494-3415 Bill Sherksnas


iv

EXHIBITORS (cont.) Please visit our exhibit area and thank them for supporting the Eighth International Starch Technology Conference:

Outotec (USA) Inc. 6100 Philips Highway Jacksonville FL 32216 Phone: 904-309-5412 www.outotec.com Joe Skafar


v

SPONSORS We gratefully acknowledge these sponsors of the Eighth International Starch Technology Conference:

College of Agricultural, Consumer and Environmental Sciences 34 Animal Science Laboratory 1207 West Gregory Drive Urbana, IL 61801 Phone: 217-244-9270 Fax: 217-244-9275 Natalie Bosecker


vi

SPONSORS (cont.) We gratefully acknowledge these sponsors of the Eighth International Starch Technology Conference:

Novozymes 77 Perry Chapel Church Road Franklinton, NC 27525 Phone: 919-494-3000 Fax: 919-494-3415 Bill Sherksnas


*indicates speaker vii

Table of Contents

Dedication ....................................................................................... i

The Conference ............................................................................. ii

Exhibitors ..................................................................................... iii

Sponsors ......................................................................................... v

Tentative Conference Agenda ..................................................... x

Paper Presentations ...................................................................... 1

AGRICULTURAL RESEARCH AND LAND GRANT UNIVERSITIES ........................1 Robert J. Hauser* College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign

ECONOMIC ANALYSIS OF HIGH FRUCTOSE CORN SYRUP PRODUCTION ....................................................................................................................3

David B. Johnston*1, Winnie Yee1, Andy McAloon1 and Vijay Singh2 1United States Department of Agriculture, Agricultural Research Service, Eastern Regional Research Center2Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign

SEPARATION OF PHYTOCHEMICALS AND XYLOSE OLIGOMERS USING CENTRIFUGAL PARTITION CHROMATOGRAPHY (CPC) ...........................7

Kris Bunnell and Danielle Julie Carrier*Biological and Agricultural Engineering, University of Arkansas

NOVEL PRODUCTS FROM STARCH BASED FEEDSTOCKS...................................18 Victoria Finkenstadt* National Center for Agricultural Utilization Research, Agricultural Research Service, United States Department of Agriculture

IMPROVED CORN FRACTIONATION USING ENZYME SOLUTIONS ...................21 Tom Gibbons*


*indicates speaker viii

Novozymes North America Inc.

COMPOSITIONAL AND PHYSICAL QUALITY FACTORS OF THE 2012 U.S. CORN CROP .............................................................................................................29

Marvin R. Paulsen*1, Sharon Bard2, John C. McKinney3, Lowell D. Hill4, Tom Whitaker5 and Frederick E. Below6

1Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign

THE VALUE OF ILLINOIS LAND .................................................................................47 Bradley Uken* Champaign County Farm Bureau

TROPICAL MAIZE FOR THE BIOPROCESSING INDUSTRY ...................................49 Laura F. Gentry*, Gary A. Letterly, and Frederick E. BelowCrop Sciences, University of Illinois at Urbana-Champaign

ENZYMES IN STARCH PROCESSING: NEW ENZYMES FOR THE PRODUCTION OF SPECIALTY SYRUPS .....................................................................60

Pauline Teunissen*, Tom Kleinhout, Bart Koops, Sung Ho Lee and Donald Ward Danisco US Inc.

IMPACT OF DEFICIT IRRIGATION ON CROP PHYSICAL AND CHEMICAL PROPERTIES AND ETHANOL YIELD ....................................................62

Donghai Wang*, Liman Liu, Norman Klocke, Danny Rogers, Freddie Lamm and Alan Schlegel Biological and Agricultural Engineering, Kansas State University

POTENTIAL APPLICATIONS FOR AMYLOSE INCLUSION COMPLEXES PRODUCED BY STEAM JET COOKING ......................................................................80

Frederick C. Felker*1, James A. Kenar1, Jeffrey A. Byars1, Mukti Singh1, Sean X. Liu1 and George F. Fanta2

1Functional Foods and 2Plant Polymer Research UnitsNational Center for Agricultural Utilization Research, Agricultural Research Service, United States Department of Agriculture

EFFLUENT WATER FOR ETHANOL PRODUCTION .................................................97 Kishore Rajagopalan* Illinois Sustainable Technology Center, Prairie Research Institute, University of Illinois at Urbana-Champaign

CORN COPRODUCTS IN COMPANION ANIMAL NUTRITION .............................111 Maria R. C. de Godoy* and George C. Fahey, Jr.Animal Sciences, University of Illinois at Urbana-Champaign


*indicates speaker ix

GLUCOSE DEMUDDING BY A DECANTER-MEMBRANE SYNERGY PROCESS: DEVELOPMENT UPDATE ........................................................................119

Dell Hummel*1 and Frank Lipnizki2

1Alfa Laval Inc.

UPDATE ON CELLULOSIC ETHANOL ......................................................................122 Bruce S. Dien*,2 National Center for Agricultural Utilization Research, Agricultural Research Service, United States Department of Agriculture

Speaker Biographies ................................................................. 130

Author and Affiliation Index ................................................... 134

Future Dates and Information ................................................. 136

Notes ........................................................................................... 137

Notes ........................................................................................... 138

Notes ........................................................................................... 139


x

TENTATIVE CONFERENCE AGENDA

Monday, June 3, 2013 8:30 Welcome and Introductions 9:00 Robert Hauser, University of Illinois – Agricultural Research and Land

Grant Universities 9:15 David Johnston, USDA/ARS/ERRC – Economic Analysis of High Fructose

Corn Syrup Production 10:15 Break 10:45 Julie Carrier, University of Arkansas – Xylooligosaccharides from Biomass 11:30 Victoria Finkenstadt, NCAUR/ARS/NCAUR – Novel Products from Starch

Based Feedstocks 12:15 Lunch 1:45 Tom Gibbons, Novozymes NA – Improved Corn Fractionation Utilizing

Enzyme Solutions 2:30 Marvin Paulsen, University of Illinois – Compositional Factors of the

2012 U.S. Corn Crop 3:15 Brad Uken, Champaign County Farm Bureau – Understanding Farm Inputs 3:45 Break 6:00 Casual dinner at Sunken Gardens, University of Illinois Tuesday, June 4, 2013 9:00 Laura Gentry, University of Illinois – Tropical Maize for the Bioprocessing Industry 10:00 Pauline Teunissen, DuPont Industrial Biosciences – Enzymes in Starch Processing 10:45 Break 11:15 Donghai Wang, Kansas State University – Deficit Irrigation, Grain Properties

and Ethanol Yields 12:15 Lunch 1:45 Fred Felker, USDA/ARS/NCAUR – Amylose Inclusion Complexes 2:30 Kishore Rajagopalan, Illinois Sustainable Technology Center – Effluent Water for

Biofuels 3:30 Break 4:30 Reception with light refreshments at CABER, University of Illinois Wednesday, June 5, 2013 8:30 Maria Godoy, University of Illinois – Use of Wet Milling Products in Pet Foods 9:30 Dell Hummel, Alfa Laval – Decanter Centrifuges 10:30 Break 11:00 Bruce Dien, USDA/ARS/NCAUR – Update on Cellulosic Ethanol 12:00 Conference adjournment


PAPER PRESENTATIONS


1

AGRICULTURAL RESEARCH AND LAND GRANT UNIVERSITIES

Robert J. Hauser*

College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign

1301 West Gregory Drive, Urbana, IL 61801 (217) 244-2807, [email protected]

The U.S. land grant university system currently is undergoing several significant

transitions. These public universities were founded with the mission to conduct teaching,

research and outreach activities focused on development of efficient agricultural

production. The first transition is the reduction in public support. In recent years, the

economic atmosphere in federal and state government budgets has created a change in

funding models for public universities. Also, support at the state level and federal level

for these institutions has been decreasing. As a result, student tuition has become the

major source of revenue supporting land grant institutions. To overcome the growing

shortfall in public funding and to competitively solve society’s great challenges,

Universities will rely increasingly on private support, endowments and gifts to conduct

research.

Another transition is that the land grant system and the University of Illinois are

serving students with changing demographics and cultural backgrounds. For agricultural

education, land grant universities historically served students from rural backgrounds.

This continues to shift so that we are serving more students from urban areas and with

limited exposure to agricultural production. Additionally, increasing numbers of

undergraduates come from foreign countries. Differing backgrounds and cultures mean

that the teaching strategies will need to be adapted to address gaps in their agricultural

education.

A third transition, economic development, has been added as a main objective for

the University of Illinois and land grant universities in general. This means more

research projects will need to have practical and economic importance. “Blue sky”

research is no longer the norm, and will occur less frequently. One of the new efforts that


2

the U of I will be leading is development of UI LABS, modeled in many ways after Bell

Labs.

Recently, the University of Illinois completed a visioning session and defined six

areas of thematic research, called Future Excellence at Illinois. These six themes are:

1) Economic Development,

2) Education,

3) Energy and the Environment,

4) Health and Wellness,

5) Information and Technology and

6) Social Equality and Cultural Understanding.

Within each theme, major topics were identified. Food supply, production and safety,

energy availability and costs, and innovative alternative energies major topics are

included in the theme of Energy and Environment. These topics are well represented at

the International Starch Technology Conference. The University of Illinois will be

supporting these themes in the near future, including plans to cluster hire 500 new faculty

during the next five years to address these research themes.


3

ECONOMIC ANALYSIS OF HIGH FRUCTOSE CORN SYRUP PRODUCTION

David B. Johnston*1, Winnie Yee1, Andy McAloon1 and Vijay Singh2

1United States Department of Agriculture, Agricultural Research Service,

Eastern Regional Research Center 600 East Mermaid Lane, Wyndmoor, PA 19038, USA

2Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign Urbana, IL, USA

(215) 836-3756, [email protected]

ABSTRACT

The production of high fructose corn syrup (HFCS) was first introduced in 1957

but it was not until about 1975 that it started to become introduced to many processed

foods and soft drinks in the United States. The production of HFCS begins by wet

milling corn to produce intact starch. The starch is converted enzymatically to a syrup

that is almost entirely glucose. The syrup is treated with another enzyme to isomerize a

portion of the glucose into fructose. A technical model of the conventional wet milling

process was developed previously, published and made available to the public using

SuperPro Designer® software. Recently available information and commercial interest

in sugars led us to develop a process model for the production of HFCS. Details of the

wet milling and syrup processes will be described and important economic factors

discussed.

Wet milling process

Corn is steeped first in a solution of sulfurous acid for 24 to 48 hr. The steeped

corn is ground coarsely to release intact germ and the germ recovered using

hydrocyclones. The remaining material is finely ground and fiber is recovered and

washed of free starch using parabolic screens. The stream now called millstarch contains

primarily starch granules and protein (also called corn gluten). The starch and protein are

separated by centrifugation. The slurry stream is processed further depending on the final

product (Figure 1).

4

Sulfur Burner

Corn

SulfurAir

Water

1st GrindingSeparation 1/2

2nd GrindingSeparation 3/4

Germ Wash (x3)Germ Dewatering

Germ DryerGerm

3rd Grinding

Starch Wash

Starch Slurry

Starch Wash (x11)

Clarifier

Fiber Wash (x5) Fiber WashFiber Press

Dryer

Gluten Feed

MS Thickener Separator

ThickenerDewatering

Gluten DryerGluten Meal

Wash Water

Steeping (x8)

Figure 1. Simplified schematic diagram of the conventional corn wet milling process. Only major unit operations are shown.


5

HFCS Production

The corn starch slurry stream from the wet milling process is mixed with a

thermostable alpha amylase and heated to gelatinize the starch. The alpha-amylase will

convert gelatinized starch into dextrins (short chain polymers of glucose) at an elevated

temperature. The stream is cooled and glucoamylase is added. This enzyme will convert

dextrins into free glucose. The glucose stream is concentrated and passed through an

immobilized enzyme column with xylose isomerase (also referred to as glucose

isomerase). This will convert a portion of the glucose into fructose, resulting in a mixture

of 42% fructose and 58% glucose. A portion of this stream is separated by

chromatography to produce separate fructose (about 90% purity) and glucose (close to

100% purity) streams. The glucose stream is recycled upstream to pass through the

isomerization step again and the 90% fructose stream is blended with the 42% stream to

produce 55% fructose (HFCS-55). Products are both liquid streams with either 42 or

55% fructose. The overall flow diagram for the process model is depicted in Figure 2.

LITERATURE CITED

Ramirez E.C., Johnston D.B., McAloon A.J., Yee W., Singh V. 2008. Engineering

process and cost model for a conventional corn wet milling facility. Industrial

Crops and Products 27(1):91-97.

V-101Tank

Starch Slurry

H2O

HX-102Heater1 FL-103

Flash

V-104Holding Tank

HX-105Heater2 FL-106

Flash

V-107Liquefaction

S-276

S-278

S-279 S-280

S-281

S-282

a-Amylase2

a-Amylase1

V-108 / V-108Mixing Tank

S-283

HClDS-109 / DS-109

Centrifugation

S-284

Mud

HX-110 / HX-110Cooling

S-286

V-113

V-112Saccharification

Glucoamylase

V-114 / V-114Blending / Storage

S-287

V-117Filter Aid Tank

Filter Aid

S-291MX-115 / MX-115

Mixing

S-290

FP-116Filter Press

S-285

Filter Cake

S-294

S-295

V-118Ion Exchange Feed Tank INX-120

Anion ExchangeINX-121

Cation Exchange

S-289

S-292

S-293

S-296

S-297S-301

S-304

S-306

S-303S-307

S-308

EV-135Evaporation

S-305

Condensates

S-311

V-136Blending / Storage

Filter Aid2

S-309

FP-138Filter Press

S-312

FIlter Cake2V-139Enzyme Prep Tank

BSS

V-151Blending / Storage

Activated Carbon

FIlter Aid3

FR-152Filter

S-315

Filter Cake3

V-154Tank

S-317

INX-162Anion Exchange

INX-163Cation Exchange

S-319

S-320S-321

S-323S-324

S-325S-326S-327 S-328

EV-166Evaporation

S-322

S-329

S-330

ISO-145Isomerization

MgSO4

S-314S-332

S-333

C-168Chromatography

S-335

Reg

S-310 S-337V-170

Mixing Tank

FR-171Filter

S-331

Activited Carbon2

Filter Aid4

S-341

Filter Cake4

INX-173Anion Exchange

INX-174Cation Exchange

S-316S-339

S-340

S-342

S-343

S-344

S-345

S-346S-347S-348

EV-175Evaporation

S-349

S-351

S-352

MX-178Blending

S-338

HFCS-42

HFCS-90

HFCS-55

S-350

S-353

S-355

Figure 2. Draft model of the HFCS process. Input is from the 100,000 bushel per day corn wet milling model.


7

SEPARATION OF PHYTOCHEMICALS AND XYLOSE OLIGOMERS USING CENTRIFUGAL PARTITION CHROMATOGRAPHY (CPC)

Kris Bunnell and Danielle Julie Carrier*

Biological and Agricultural Engineering, University of Arkansas

203 Engineering Hall Fayetteville, Arkansas 72701

(479) 575-2351, [email protected] ABSTRACT

Mixtures of silymarin, Silybum marinanum phytochemicals, and of xylose oligomers

were fractionated via centrifugal partition chromatography (CPC) with solvent systems

composed of heptane:ethyl acetate:methanol:water (1:4:3:4, V:V:V:V) and of

butanol:methanol:water (5:1:4, V:V:V), respectively. Using this technique, 1.5 mg of 97% pure

silydianin, a component of silymarin, was purified from a crude extract that originally contained

4 mg of this compound. Using CPC for separation of xylose oligomers, yields of xylobiose

(DP2), xylotriose (DP3), xylotetraose (DP4) and xylopentose (DP5) were 13, 10, 14 and 21 mg,

respectively, per g birchwood xylan; and yields of purified xylose, DP2, DP3, DP4, DP5 and

xylohexose (DP6) were 26.7, 2.4, 12.1, 11.0, 6.8 and 11.6 mg per g purified switchgrass

hemicellulose, respectively.

INTRODUCTION

The preparation of plant based crude extracts is widely reported in literature (Tanko et al

2005). As an example, Engelberth et al (2008) produced crude extracts from Silybum marianum

(L.) fruits in 120°C water. S. marianum extracts contain the flavonolignans silychristin,

silydianin, silybin and isosilybin, which often are referred to collectively as silymarin. S.

marianum crude extracts, silymarin, are sold as nutraceuticals for promoting liver health (Flora

et al 1998).

Xylose oligomers are composed of xylose molecules with degree of polymerization (DP)

ranging from 2 to 10, linked together by β-1-4 bonds (Makelainen et al 2009). Because of their

stability over wide pH range (2.5 to 8.0), and their noncariogenic and prebiotic properties, xylose

oligomers have been used in food applications, such as fortified foods, anti-obesity diets and


8

novel foods (Vazquez et al 2000). Xylose oligomers also are found in pharmaceutical

applications, such as the treatment of gastrointestinal infections, osteoporosis, otitis and pruritus

cutaneous, as well as agricultural applications, such as ripening agents and foodstuffs for

domestic animals (Vazquez et al 2000).

Unfortunately, crude extracts such as silymarin and xylose oligomers are rarely separated

into their individual components. Separating crude extracts enables the evaluation of

corresponding biological activity, catabolism or stability of individual components. Flash

chromatography, preparative high pressure liquid chromatography (HPLC) and centrifugal

partition chromatography (CPC) are techniques used to separate components from crude extracts.

Specifically, CPC is a type of liquid-liquid separation utilizing a constant gravity field produced

by the rotation of a rotor (Foucault and Chevolot 1998). When introduced into CPC, the solute

distributes between the two partially miscible liquid phases that are separated by their densities

(Marchal et al 2003). We will illustrate how CPC can be used to separate crude extracts

composed of flavonolignans from S. marianum, xylose oligomers from birchwood xylan and

xylose oligomers from switchgrass.

MATERIALS AND METHODS

Materials: S. marianum fruits were obtained from Horizon Herbs (Williams, OR) as

reported in Engelberth et al (2008). Flavonolignans were purchased from PhytoLab (Hamburg,

Germany). Birchwood xylan and xylose (DP1) were purchased from Sigma-Aldrich (St. Louis,

MO). Xylobiose (DP2), xylotriose (DP3), xylotetraose (DP4), xylopentose (DP5), and

xylohexose (DP6) were purchased from Megazyme (Wicklow, Ireland). Switchgrass

hemicelluloses were obtained as described in Bunnell et al (2013a).

Sample preparation: S. marianum fruits were ground and extracted in 120°C water as

described by Engelberth et al (2008). To produce xylose oligomers, birchwood xylan was

hydrolyzed in water in 32 mL stainless steel reactors at 200°C for 60 min in a fluidized sand bath

(Techne Ltd., Burlington, NJ) (Lau et al 2011). Switchgrass hemicelluloses were hydrolyzed in

a similar fashion, where 0.8 g switchgrass hemicelluloses were hydrolyzed in water at 160°C for

60 min in the fluidized sand bath (Bunnell et al 2013b).

CPC separation: Flavonolignans were separated using heptane:ethyl

acetate:methanol:water (1:4:3:4, V:V:V:V) in a Kromatron (Angers, France) CPC as reported by


9

Engelberth et al (2008). Birchwood xylose oligomers were fractionated using

butanol:methanol:water (5:1:4, V:V:V) in a Kromatron CPC as reported by Lau et al (2013).

Switchgrass xylose oligomers were also fractionated in butanol:methanol:water (5:1:4, V:V:V),

using an Armen Instrument (Saint Ave, France) CPC as reported by Bunnell et al (2013b).

HPLC analyses of flavonolignans and of birchwood xylose oligomers were as described by

Engelberth et al (2008) and Lau et al (2011), respectively. High performance anion exchange

chromatography with pulsed amperometric detection (HPAEC-PAD) analysis was used to

analyze switchgrass xylose oligomers as reported by Bunnell et al (2013b).

RESULTS AND DISCUSSION

Silymarin is a good starting material to illustrate the use of CPC for separation of a

phytochemical crude extract into its individual components. Figure 1 presents a typical

chromatogram of S. marianum (L.) 120°C water extract.

Figure 1. Chromatogram of Silybum marianum (L.) 120°C water extract. Retention times of silychristin, silydianin, silybin A and B and isosilybin A and B were 16, 17.5, 24, 25, 28 and 29 min, respectively.


10

Retention times of silychristin, silydianin, silybin A and B and isosilybin A and B were

16, 17.5, 24, 25, 28 and 29 min, respectively. The CPC chromatogram corresponding to the S.

marianum (L.) 120°C water extract using heptane:ethyl acetate:methanol:water (1:4:3:4,

V:V:V:V) solvent system is depicted in Figure 2.

The organic upper phase was used as the stationary phase, and the aqueous lower phase

was used as the mobile phase. Silychristin (SC) at 70% purity eluted between 33 and 38 min,

and silydianin (SD) was collected in fractions corresponding to 43 and 48 min of separation. An

HPLC chromatogram of pooled silydianin fractions is shown in Figure 3. CPC can be used for

the production of relatively pure fractions of a phytochemical, such as silydianin (Figure 3).

Engelberth et al (2008) reported that 1.5 mg of 97% pure silydianin was purified from crude

extract that originally contained 4 mg of this flavonolignan.

Figure 2: CPC chromatogram for Silybum marianum (L.) 120 °C water extract separation. Solvent system was heptane:ethyl acetate:methanol:water (1:4:3:4, V:V:V:V). The organic, upper phase was used as the stationary phase, and the aqueous, lower phase was used as the mobile phase.


11

Figure 3. HPLC chromatogram for pooled silydianin fractions collected from 43 to 48 min of CPC separation.

Hydrolyzing 1 g of birchwood xylan in 200 °C water for 60 min yielded 94, 60, 25, 36

and 43 mg of DP1, DP2, DP3, DP4 and DP5, respectively. A typical HPLC chromatogram for

the hydrolysate is presented in Figure 4.

The CPC chromatogram produced using a solvent system of butanol:methanol:water

(5:1:4, V:V:V) for the fractionation of xylose oligomers is presented in Figure 5. The elution

times of DP1, DP2, DP3, DP4 and DP5 were 85 to 95, 108 to 128, 151 to 188, 212 to 250 and

268 to 274 min, respectively. Purities of DP 2, DP 3, DP 4, and DP 5, were 81, 71, 62, and 52%,

respectively. Respective yields were 13, 10, 14 and 21 mg per g of birchwood xylan (Lau et al

2013).

Depicted in Figure 6 is an HPLC chromatogram of the xylotetraose fraction produced

during the CPC fractionation.


12

Figure 4. HPLC chromatogram of hydrolyzed birchwood xylan containing xylose (DP1) and oligomers (DP2 and higher). DP1, DP2, DP3 and DP4 were detected at retention times of 54, 49, 45 and 41 min, respectively.

Figure 5. CPC chromatogram for hydrolyzed birchwood xylan using butanol:methanol:water (5:1:4, V:V:V) solvent system. Fractions were collected as indicated on the figure.


13

Figure 6. HPLC chromatogram of xylotetraose (DP4), which was collected between 212 and 250 min from the CPC separation described in Figure 5.

Switchgrass hemicelluloses, as described in Bunnell et al (2013a), were used as the

starting material for production of xylose oligomers by hydrolyzing in water at 160°C for 60

min. The resulting hydrolysate oligomer profile can be seen in Figure 7.

Yields of 78, 24, 34, 23, 19 and 38 mg of xylose, DP2, DP3, DP4, DP5 and DP6,

respectively, were generated per g of switchgrass hemicelluloses. Using a

butanol:methanol:water (5:1:4, V:V:V) solvent system, xylose, DP2, DP3, DP4, DP5 and DP6

eluted from the CPC column at 61 to 80, 105 to 114, 130 to 165, 175 to 228, 245 to 285 and 291

to 299 min, respectively (Figure 8). Fractions were consolidated based upon HPAEC-PAD

results and corresponding purities were inserted in Figure 8. Yields of purified xylose, DP2,

DP3, DP4, DP5 and DP6 were 27, 2, 12, 11, 7 and 12 mg, respectively, per g of purified

switchgrass hemicelluloses.


14

Figure 7. High performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD) chromatogram for switchgrass hemicelluloses autohydrolysed at 160 oC for 60 min. Retention times of DP1 (xylose), DP2 (xylobiose), DP3 (xylotriose), DP4 (xylotetraose), DP5 (xylopentose) and DP6 (xylohexose) were 2.4, 2.7, 3.3, 4.3, 6.0 and 9.0 min, respectively.


15

Figure 8. CPC separation of switchgrass hemicellulose derived oligomers with inserts of high performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD) chromatograms for consolidated fractions. DP1 (xylose), 61 to 80 min; DP2 (xylobiose), 105 to 114 min; DP3 (xylotriose), 130 to 165 min; DP4 (xylotetraose), 175 to 228 min; DP5 (xylopentose), 245 to 285 min; DP6 (xylohexose), 291 to 299 min.

CONCLUSION

Using CPC, it is possible to separate crude extracts, such as silymarin and xylose

oligomers (DP1 to DP6), into their respective individual compounds. CPC was used to

fractionate switchgrass xylose oligomers, which are not yet available as commercial standards.

Economic analyses would be required to determine viability of CPC based processes for

industrial use, but nevertheless, this separation tool is useful for lab scale production of reference

compounds for research.


16

Acknowledgments

The authors gratefully acknowledge financial support from the University of Arkansas, National

Science Foundation (award #0828875), U.S. Department of Energy (award #08GO88036),

CSREES National Research Initiative (award #2008-01499) and the Plant Powered Production

(P3) Center, which is funded wholly or in part by the National Science Foundation (NSF)

EPSCoR Program and the Arkansas Science and Technology Authority (award # EPS-1003970).

LITERATURE CITED

Bunnell, K., Rich, A., Luckett, C., Wang, Y., Martin, E. and Carrier, J. 2013. Plant maturity

effects on the physicochemical properties and dilute acid hydrolysis of switchgrass

(Panicum virgatum, L.) hemicelluloses. ACS Sustainable Chem. Eng. (in press).

Bunnell, K., Lau, C.S., Lay, J.O., Gidden, J. and Carrier, D.J. 2013. Production and

fractionation of xylose oligomers from switchgrass using centrifugal partition

chromatography (CPC). Industrial & Engineering Chemistry Research (submitted).

Engelberth, A.S., Carrier, D.J. and Clausen, E. 2008. Separation of silymarins from milk thistle

(Silybum marianum L.) extracted with pressurized hot water using fast centrifugal

partition chromatography. J. Liq. Chromatogr. Relat. Technol. 31:3001-3011.

Flora, K., Hahn, M., Rosen, H. and Benner, K. 1998. Milk thistle (Silybum marianum) for the

therapy of liver disease. Am. J. Gastroenterol. 93:139-143.

Foucault, A.P. and Chevolot, L. 1998. Counter-current chromatography: Instrumentation,

solvent selection and some recent applications to natural product purification.

J. Chromatogr. A. 808:3-22.

Lau, C.S., Bunnell, K.A., Clausen, E., Thoma, G.J., Lay, J.O., Gidden, J. and Carrier, D.J. 2011.

Separation and purification of xylose oligomers using centrifugal partition

chromatography. J. Ind. Microbiol. Biotechnol. 38:363-370.

Lau, C., Clausen, E., Lay, J., Gidden, J. and Carrier, D.J. 2013. Separation of xylose oligomers

using centrifugal partition chromatography with a butanol-methanol-water system. J.

Ind. Microbiol. Biotechnol. 40:51-62.


17

Marchal, L., Legrand, J. and Foucault, A. 2003. Centrifugal partition chromatography: A survey

of its history, and our recent advances in the field. Chem. Rec. 3:133-143.

Makelainen, H., Juntunen, M. and Hasselwander, O. 2009. Prebiotic potential of xylo-

oligosaccharides. In: Prebiotics and Probiotics Science and Technology;

Charalampopoulos, D. and Rastall, R., Eds.; Springer, New York, NY, pp. 245-258.

Tanko, H., Carrier, D.J., Duan, L. and Clausen, E. 2005. Pre and post harvesting processing of

medicinal plants. Plant Genet. Resour. 3:304-313.

Vazquez, M., Alonso, J., Dominguez, H. and Parajo, J. 2000. Xylooligosaccharides:

manufacture and applications. Trends Food Sci. Technol. 11:387-393.


18

NOVEL PRODUCTS FROM STARCH BASED FEEDSTOCKS

Victoria Finkenstadt*

National Center for Agricultural Utilization Research, Agricultural Research Service, United States Department of Agriculture

1815 North University Street, Peoria IL 61614, USA (309) 681-6469, [email protected]

There has been progress in the utilization of starch as a partial replacement for petroleum

based plastics, but it remains a poor direct substitute for plastics and a moderate one for

composites. We focused our research on using polymers produced from direct fermentation such

as poly(lactic acid) or microbial exopolymers made by cell free enzymatic solutions fed by the

starch based sugars. Both of these polymers were considered to be undesirable: ethanol was

preferred over lactic acid and microbial biofilms fouled equipment. Each of them was able to

support its own market for green polymer composites and anticorrosive coatings, respectively.

Green polymer composites with poly(lactic acid) PLA

Green polymer composites using biodegradable and bio based polymers such as poly

lactic acid and agricultural products were manufactured using twin screw reactive extrusion and

injection molding (Figure 1). Using agricultural “waste” as a filler, green composites were

formed that showed ductile behavior which is a good combination of tensile strength and

flexibility. Mechanical properties of the composite were comparable to expensive thermoplastic

residence, but were more economical showing a potential for nonweight bearing building

materials or automotive interior panels. An additional use as agricultural mulch films was

identified as the composite can be produced in thin sheets and has been shown to prevent weed

growth and degrades in the field during the growing season. The composite can be impregnated

with fertilizer or pesticide for gradual release over time.


19

Figure 1. Green polymer composites using biodegradable and biobased polymers manufactured using twin screw reactive extrusion and injection molding. Anticorrosive coatings using biofilms

Biobased polymers, produced from specific bacteria in a commercially available process, have

shown to inhibit corrosion on metal substrates. Extensive electrochemical analyses showed that

the exopolysaccharide, purified from cell free cultures, adhered strongly to the metal substrate,

provided active resistance to corrosive environments and displayed limited self healing after

scratching (Figure 2). The coating is applied through commercial spray technology with a

controlled thickness of 50 to 500 nm. We hypothesized the anticorrosive ability was controlled

by several properties of the environment-coating-metal system such as:

1) film forming capability and adhesion;

2) polymer mobility as it hydrates;

3) diffusion properties through the coating;

4) ion mobility of the corrosive species through the thin film; and

5) interfacial phenomena between environment-polymer and polymer-metal.


20

The coating can be used as a primer or paint component. This technology has been submitted for

patent protection by ARS and is available for licensing.

Figure 2. Anticorrosive coatings using biofilms.


21

IMPROVED CORN FRACTIONATION USING ENZYME SOLUTIONS

Tom Gibbons*

Novozymes North America Inc. 77 Perrys Chapel Church Road

Franklinton NC 27525 United States (919) 494-3933, [email protected]

INTRODUCTION

The corn wet milling industry produces a wide array of products and raw materials for

food, feed, manufacturing and fuel (Ingledew et al 2009). Products of the wet milling process

provide the backbone of global economies. Rising costs for corn, water and energy have

provided strong incentives for wet millers to focus keeping their operational costs at a minimum

to maximize profits (Ramirez et al 2007).

We will demonstrate the use of enzyme technology in the millhouse can provide better

separation of corn fractions. By improving separation purities, increased yields of the two most

valuable components (corn gluten and starch) can be realized. Enzymes can also access fractions

that are inaccessible by conventional wet mill mechanical processes. A key aspect of the

technology is that it can be applied at different dosing points within a wet mill design while still

achieving the desired effect.

There are also side benefits with enzymatic technology in the millhouse including

decreased bound water in fiber, improved gluten dewatering, improved post saccharification

filtration, more efficient germ separation, reduction in SO2 and improved evaporation of light

steepwater. Another advantage of utilizing enzyme technology is increased throughput by

reducing steep times. As corn wet mills look for competitive and operational gains, enzyme

technology can play a vital role in allowing for an edge in a global market.

Process Entry Point

To facilitate maximum contact area and residence time, enzymes typically are applied

after first grind (Figure 1). Additional incubation tanks can be added in-line to further increase

enzyme residence time, thereby increasing the amount of starch and gluten which are liberated.


22

Proposed Mechanism

In some enzyme formulations, we believe that a partial hydrolysis of the plant cell wall

leads to release of bound starch and protein (Figure 2). This theory is supported through

laboratory measurements of residual starch in fiber which show reductions with enzyme

treatment in comparison to nonenzyme treatment.

Figure 1. Point of enzyme addition in millhouse.


23

Figure 2. Corn fiber cell wall picture and residual starch laboratory data


24

Depicted in Figure 3 are lab generated corn fiber fraction samples. There is more white starch

and yellow gluten on the control sample than on the enzyme treated sample, a visual

confirmation of the residual starch results.

Control Enzyme treatment

Figure 3. Lab generated corn fiber fraction. As a function of the lower starch and gluten in the fiber fractions, better fiber and gluten

dewatering can be observed in lab trials using a spin test (Figure 4). More supernatant in the test

tube signified better dewatering, a trend which has been observed in fiber plant trials. This

dewatering benefit translates into savings of steam, water and electricity during wet mill plant

operations.


25

Figure 4. Laboratory spin test. Enzyme technology when used in the millhouse has no effect on syrup filtration. Internal

lab data shows that starch incubated with enzymes in the millhouse has the same filtration

efficiency when compared to the conventional process (Figure 5). Both starches were liquefied

and saccharified with commercial products and achieved the same %DX (Figure 5).

Control Enzyme


26

Figure 5. Internal lab data on filtration efficiency and %DX. Plant Trial Results

The steam savings observed in plant trials using feed drying on fiber are upwards of 7.2

tons/day. A reduction in fiber press discharge moisture of 3% when using enzyme solutions in

the millhouse has been observed. There was an overall steam reduction of greater than 10%.

This steam savings creates a savings in plant utility costs for wet millers. Decreased moisture of

2% at the input to the rotary vacuum filter for gluten feed was a measurable side benefit of the

enzyme.


27

Additional Benefits

Evaporation of light steepwater is a major energy consumption point for wet mills

(Galitsky et al 2003). The ability to run higher % DS evaporated steepwater would save mills

money in utilities since less water would need to be evaporated. Using enzyme technology in the

millhouse allows for this energy savings. With enzyme incubation there is a sizeable decrease in

steepwater viscosity, particularly for enzyme B (Figure 6).

Figure 6. Changes in steepwater viscosity with enzyme treatment. As the summer season approaches and a corresponding increased demand for high

fructose corn syrup, the ability to increase plant output becomes an extremely valuable option.

Plant trial results demonstrate that wet mills can increase grind by 100 to 150 tons of corn per

day (3600 to 5400 bu per day) when enzyme solutions are added in the millhouse. Another plant

reported an increase in starch production of 30 to 40 tons per day. This increase in throughput is

the culmination of several incremental improvements including shorter steep times, better fiber

dewatering, improved saccharification filtration and steepwater evaporation.

-25.00%

-20.00%

-15.00%

-10.00%

-5.00%

0.00%Enzyme A Enzyme B Enzyme C

% Difference from Control

Steepwater Viscosity

% D

iffe

renc

e fr

om n

o en

zym

e c

ontr

ol


28

A scientific look into the mechanism between the wet mill process and the enzyme

provide a valuable knowledge base. This base applied successfully within industrial settings

provides great scientific satisfaction which fuels scientists’ ability to rethink the wet milling

process and create innovative solutions. With all of the demonstrated benefits of enzymes in the

millhouse seen today, it will be interesting to see what the next twenty years will look like for

enzyme technology and wet mills.

LITERATURE CITED

Ingledew W.M., et al. The Alcohol Textbook. 5th ed. Nottingham University Press, 2009.

Ramirez, Edna C., Johnston, David B., McAloon, Andrew J., Yee, Winnie, Singh, Vijay.

2007. Engineering process and cost model for a conventional corn wet milling

facility. Industrial Crops & Products 27: 91-97.

Galitsky, Christina, Worrell, Ernst, Ruth, Michael. 2003. Energy efficiency improvement

and cost saving opportunities for the corn wet milling industry: An ENERGY STAR

Guide for Energy and Plant Managers. LBNL-52307. Lawrence Berkeley National

Laboratory. Berkeley, CA.


29

COMPOSITIONAL AND PHYSICAL QUALITY FACTORS OF THE 2012 U.S. CORN CROP

Marvin R. Paulsen*1, Sharon Bard2, John C. McKinney3, Lowell D. Hill4,

Tom Whitaker5 and Frederick E. Below6

1Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign

1304 W. Pennsylvania Ave., Urbana, IL 61801 (217) 333-7926, [email protected] 2Centrec Consulting Group, LLC, Savoy, IL

3Identity Preserved Grain Lab, Illinois Crop Improvement Association, Champaign, IL 4Agricultural Economics and Consumer Studies, University of Illinois

5Biological and Agricultural Engineering, NC State University, Raleigh, NC 6Crop Sciences, University of Illinois at Urbana-Champaign

INTRODUCTION

In 2011 and 2012, the U.S. Grains Council conducted studies of the quality of the 2011

and 2012 U.S. corn crops both at harvest and export locations (USGC 2012 and USGC 2013).

The objective of these reports was to provide reliable information on U.S. corn quality at the

farm gate and in export markets, using a transparent and consistent methodology. We will focus

on quality of the 2012 corn crop. These studies were done by the Centrec Consulting Group

(Savoy, IL) with the Identity Preserved Grain Lab (Champaign, IL) conducting sample analyses

for factors outside U.S. grading standards. For the Harvest Reports, Champaign-Danville Grain

Inspection did analyses for grading factors, and for the Export Cargo Reports, grading factors

were analyzed by USDA’s Federal Grain Inspection Service (FGIS) at Gulf, Pacific Northwest

and FGIS designated inspectors at interior locations. The complete Harvest and Export Cargo

Reports are available online (USGC 2012 and USGC 2013).

SAMPLING

For the Harvest Report, a proportionate stratified random sampling process was used to

obtain samples of the U.S. corn crop at its first stage of the marketing channel. The stratification

involved dividing the survey population into distinct nonoverlapping subpopulations. Since

USDA divides each state into many Agricultural Statistic Districts (ASDs) and estimates corn

production for each ASD, total production of corn from each ASD and each ASD’s proportionate

share that is exported could be calculated. This calculation was made for the 12 highest corn


30

producing states that represent 99% of corn exports. The number of samples collected from each

ASD varied based on each ASD’s proportionate share expected to go into export. Exports were

classified into three broad areas; Figure 1 depicts the Export Catchment Areas (ECAs) Gulf,

Pacific Northwest and Southern Rail.

Figure 1. Diagram of Agricultural Statistic Districts (ASD) feeding into three major Export Catchment Areas (ECAs): Gulf, Pacific Northwest and Southern Rail.

Harvest samples were collected at local elevators from 637 inbound farm trucks from

September 6 to November 26, 2012. For the Export Cargo Report, a similar proportionate

stratified sampling was used. The targeted sampling, based on an assumed 426 total samples,

was 284 from the Gulf, 87 from Pacific Northwest and 55 from the Southern Rail. The Gulf and

Pacific Northwest samples were collected by FGIS field offices at ports in those regions. The

Southern Rail samples were provided by several official agencies that were designated by FGIS

for inspecting and grading rail shipments to Mexico. Representative samples were obtained from

diverter samples that made timed “cuts” across a moving stream of grain. The export cargo

sampling period started on October 22, 2012 and ended February 14, 2013. Ultimately only 7


31

samples could be obtained from the Southern Rail during that time period. Gulf and Pacific

Northwest ECAs contributed 284 and 106 samples, respectively, for a total of 397 samples.

DROUGHT YEAR

The 2012 crop year will be remembered for its drought conditions. The Palmer Z index

gives a relative indication of how monthly moisture conditions varied from normal (Figure 2).

Very dry conditions are shown in red and dark red, and sufficient moisture is shown in shades of

green to darker green. Much of the midwest Corn Belt area was in moderate to extreme drought

conditions during July 2012.

The primary question of corn processors, millers, feeders and buyers of corn is “How did

the 2012 drought conditions affect the quality of the U.S. corn crop?” There was also concern

about possible presence of mycotoxins.

Before discussing the quality of the 2012 corn crop, it is interesting to put into

perspective the quantity of corn produced in the U.S. For the 2012 crop year, corn yields were

reduced (123.4 bu/A) and production was decreased to 10.78 billion bushels (274 million metric

tonnes) compared to 147.2 bu/acre and 12.36 billion bushels (314 million metric tonnes),

respectively, in 2011 (USDA 2013).

COMPOSITIONAL FACTOR RESULTS

Lower yields set the backdrop for one immediate effect on corn quality. Nitrogen was

applied at the start of the crop season in expectation of normal yields. When yields were

reduced, it left more nitrogen per acre available for placement into fewer bushels per acre. The

effect was higher average protein (nitrogen) levels at export in 2012 (9.2%) than in 2011 (8.7%),

as shown in Table 1. Protein in the corn kernel is provided by nitrogen and amasses during the

grain fill stage of the corn plant life cycle, which generally occurs during July and early August.

The majority of the nitrogen for protein accumulation comes from nitrogen that has been

assimilated prior to the grain fill stage and is then remobilized from the


32

Figure 2. Palmer Z Index showing short-term conditions in July 2012 (Harvest Report). leaves during grain fill. Starch (sugars), on the other hand, is supplied to the corn kernels via

photosynthesis during grain fill (Below 2013; Below et al 1981; Swank et al 1982). A drought

during grain fill negatively affects photosynthesis which decreases sugars available for starch

synthesis in the corn grain, but does not negatively impact remobilization of nitrogen from leaves

to the grain. Thus, the supply of sugars is reduced more than the protein and higher protein

results during drought or high temperatures during the grain fill period (Below 2013). This helps

explain why in general, when protein in corn goes up, starch levels tend to decline.

All compositional factors were determined by NIT in the Identity Preserved Grain

Laboratory. The standard error of predictions for protein, starch and oil were 0.2, 0.5 and 0.3%,

respectively. Results were reported on a dry matter basis.

Table 1. Corn compositional and physical quality factors for samples collected at export and harvest for 2012 crop year corn.

*Indicates that the 2011 Export Cargo averages were significantly different than the 2012 Export Cargo averages, based on a two tailed t-test at a 95% level of significance.

**Indicates that the 2012 Harvest averages were significantly different than the 2012 Export Cargo averages, based on a two tailed t-test at a 95% level of significance.

2012 Export Cargo 2011 Export Cargo 2012 Harvest Factors No. of

samples Avg Std

Dev Min Max No. of

samples Avg Std

Dev No. of

samples Avg Std

Dev Min Max

Protein, % dry basis 397 9.2 0.37 8.1 11.2 379 8.7* 0.26 637 9.4** 0.66 7.0 12.4

Starch, % dry basis 397 73.5 0.49 71.8 75.3 379 74.1* 0.56 637 73.0** 0.67 70.6 75.6

Oil, % dry basis 397 3.7 0.19 3.1 4.3 379 3.6* 0.23 637 3.7** 0.34 1.7 5.5

Stress cracks, % 397 9 7 0 65 379 10 5 637 4** 5 0 63 100 kernel

weight, g 397 35.86 1.69 26.66 41.45 379 35.14* 1.36 637 34.53** 2.76 17.49 45.39 True density,

g/cm3 397 1.297 0.011 1.264 1.335 379 1.291* 0.009 637 1.276** 0.017 1.199 1.332 Whole kernels,

% 397 89.9 3.0 79.0 97.6 379 87.5* 3.6 637 94.4** 3.4 68.0 100.0 Horneous

endosperm, % 397 85 2 80 94 379 84* 3 637 85 4 74 97


34

Protein

Figures 3 and 4 display distributions of protein at harvest and at export, respectively.

Protein at export was 9.2% with a standard deviation of 0.37% which was slightly lower than the

9.4% and standard deviation of 0.66% at harvest. Protein was much higher in 2012 crop corn

than in 2011 and standard deviations or variability becomes less at the export level than at the

harvest level.

Figure 3. Harvest sample protein distribution (Harvest Report).

Figure 4. Export cargo sample protein distribution (Export Cargo Report).


35

Starch

Starch is the most important consitituent for wet millers. Based on these testing results,

starch appeared to be lower in 2012 corn crop, compared to the 2011 crop, but perhaps not as

much as might be expected. Starch at export in 2012 was 73.5%, a decrease from 74.1% in 2011

(Table 1). At the harvest level, starch averaged 73.0% in 2012, with a range of 70.6 to 75.6%

and a standard deviation of 0.67% (Figure 5). At the export level, starch range was slightly less

from 71.8 to 75.3%, and the standard deviation was less with 0.49% (Figure 6). In Figures 5 and

6, the 2012 starch was distributed less in the higher histogram bars than in 2011.

Figure 5. Harvest sample starch distribution (Harvest Report).

Figure 6. Export cargo sample starch distribution (Export Cargo Report).


36

Oil

Oil percentages remained fairly constant at 3.7% at export and at harvest for 2012 corn, a slight

increase from 3.6% for the 2011 export corn (Table 1). Like protein and starch, the variability or

standard deviations were lower at export levels than at the harvest level. In general, as grain was

handled and more lots were comingled, overall variability on most factors decreased.

GRADING FACTOR RESULTS

Grading factors for corn consist of broken corn and foreign material (BCFM), test

weight, total damage and heat damage. Moisture is not a grade factor but is reported.

BCFM

BCFM is the amount of material passing through a 12/64 inch round hole sieve plus any

noncorn material found on top of the sieve. In 2012, BCFM was low (0.8%) at the harvest level

and somewhat higher (2.7%) at the export level (Table 2), still below the 3.0% allowed for U.S.

Grade No. 2 corn. Figures 7 and 8 show a large difference in the distribution of BCFM as corn

moved through the market channel, demonstrating breakage increased as handling occured.

However, the breakage increase at the higher histogram bars was slightly less in 2012 than in

2011.

Moisture

Moisture content averaged 14.2% for 2012/13 export corn and 15.3% for 2012 harvest

samples (Table 2).

Table 2. Corn grading factors for samples collected at export and harvest for 2012 crop year corn.

2012 Export Cargo 2011 Export Cargo 2012 Harvest

Factors No. of Samples

Avg Std Dev

Min Max No. of Samples

Avg Std Dev

No. of Samples

Avg Std Dev

Min Max

Test weight, lb/bu

397 58.1 0.82 55.2 61.8 379 57.8* 0.57 637 58.8** 1.21 49.4 62.5

BCFM, % 397 2.7 0.68 0.6 5.0 379 3.0* 0.64 637 0.8** 0.53 0.1 5.7

Total damage, %

397 2.0 1.24 0.0 9.1 379 1.7* 0.90 637 0.8** 0.72 0.0 12.7

Heat damage, %

397 0.0 0.02 0.0 0.4 379 0.0 0.02 637 0.0 0.0 0.0 0.0

Moisture, % 397 14.2 0.43 12.7 15.2 379 14.3* 0.29 637 15.3** 1.72 8.9 24.7

*Indicates that the 2011 Export Cargo averages were significantly different than the 2012 Export Cargo averages, based on a two tailed t-test at the 95% level of significance.

**Indicates that the 2012 Harvest averages were significantly different than the 2012 Export Cargo averages, based on a two tailed t-test at the 95% level of significance.


38

Figure 7. Harvest sample BCFM distribution (Harvest Report).

Figure 8. Export cargo BCFM distribution (Export Cargo Report). Test Weight

Test weight is a determination of bulk density based on the weight of corn that fits into a

level full quart cup. Test weight can vary based on moisture content, variety, endosperm

hardness, fine material, maturity and other factors. Test weight in 2012 export corn averaged

58.1 lb/bu for export corn, higher than the 57.8 lb/bu found in 2011 (Table 2). Test weight of

2012 harvest corn was even higher (58.8 lb/bu) than the export corn. Large percentages of 2012

harvest and export corn were above 58 lb/bu (Figures 9 and 10).


39

Figure 9. Harvest sample test weight distribution (Harvest Report).

Figure 10. Export cargo test weight distribution (Export Cargo Report). Total Damage

Total damage is made up of mold damage, insect bored kernels, germ damage, sprout

damage, weather damage, heat damage and other types of damage. U.S. Grade No. 2 is allowed

5.0% total damage. At the harvest level, total damage averaged 0.8%, and at the export level, it

was 2.0% (Table 2). In 2011, export level damage was lower with 1.7%, but all of these damage

levels are still low. In addition, heat damage averaged 0.0% at export and at harvest for 2012

samples (Table 2).


40

PHYSICAL FACTOR RESULTS

The physical factors tested were stress cracks, 100 kernel weight, true density, whole

kernels and horneous endosperm percentage.

Stress Cracks

Stress cracks were determined by passing light through 100 whole kernels and visually

observing for one, two or more fissures or stress cracks in the endosperm of corn kernels with the

germ side turned down towards the light. Stress cracks averaged 9% for export corn, higher than

4% found for harvest corn in 2012. However, all of these levels are very low and indicate corn

would handle with relatively low levels of breakage generation. Stress crack distributions show

91.4% of the export samples and 96.1% of the harvest samples had stress cracks less than 20%

(Figures 11 and 12). These stress crack percentages are low, compared to 54 and 63% that

typically were found for U.S. yellow dent corn loaded on an ocean vessel at the Gulf in 1985 and

1986, respectively (Paulsen et al 1989).

Figure 11. Harvest sample stress crack distribution (Harvest Report).


41

Figure 12. Export cargo sample stress crack distribution (Export Cargo Report). True Density

True density is calculated by determining the volume of a preweighed 50 g sample of

whole corn kernels using a pycnometer and expressed as g/cm3. Dry millers and alkaline

processors of corn prefer hybrids with higher true densities (well above 1.275 g/cm3) which is

also indicative of hard endosperm presence. Wet millers may prefer a midrange of true densities,

while extremely low true densities would indicate a soft floury corn that would be prone to fairly

rapid breakage during handling. True densities averaged 1.297 g/cm3 for export corn and 1.276

g/cm3 for harvest corn in 2012 (Table 1). This would indicate a medium to hard endosperm

which would be good for dry millers, but still useable for wet millers. Harder endosperm may

require slightly longer steep times. The higher true densities found at export is believed to be

due in part to the lower moisture at export and the fact that true density tests were performed

only on whole, fully intact kernels. Distributions of true densities (Figures 13 and 14) show

2012 corn had higher percentages in the histogram bars with high true densities compared to

corn from 2011.


42

Figure 13. Harvest Sample True Density Distribution (Harvest Report)

Figure 14. Export Cargo True Density Distribution (Export Cargo Report) Whole Kernels

Whole kernel percentages are determined by visually examining 50 g of cleaned corn.

Nonwhole kernels may have chipped kernels, pericarps not intact, cracks, or chips of grain

missing. Whole kernels averaged 89.9% at the export level and 94.4% at the harvest level in

2012. Both percentages were increased slightly from 2011 corn.

Horneous Endosperm and 100 Kernel Weight

Horneous endosperm percentages were determined by visually rating 20 externally sound

kernels, placing the germ side up on a light table. Soft endosperm is opaque and horneous

endosperm is translucent. Thus, each kernel is rated on its ability to transmit light. Ratings of

horneous endosperm are made on a scale of 70 to 100%. Horneous endosperm for export

samples averaged 85%, an increase from 84% in 2011.


43

Weights for 100 kernels averaged 35.86 g for export corn in 2012, up from 35.14 g in

2011. Higher 100 kernel weights are usually indicative of larger kernel size; however,

observation of samples indicated kernel shape (while not measured) tended to have fewer flat

kernels and more round kernels in 2012.

MYCOTOXINS

Tests were conducted for both aflatoxin and deoxynivalenol (DON). For samples at

harvest level, the tests were conducted by the Identity Preserved Grain Lab in Champaign, IL.

For samples at the export level, the aflatoxin tests were conducted by the Federal Grain

Inspection Service (FGIS) and DON tests were conducted by the Identity Preserved Grain Lab.

Aflatoxin

A total of 177 samples at the harvest level were analyzed for aflatoxin in 2012 (Table

3). Results of harvest sample testing indicated:

About 78% of 177 samples had no detectable levels of aflatoxin (less than 2.5 ppb

limit of detection, LOD). In 2011, 97.9% of the samples tested had no detectable levels

of aflatoxin.

About 7.9% of 177 samples showed aflatoxin in levels greater than or equal to the

LOD of 2.5 ppb but less than or equal to the FDA action level of 20 ppb. Thus, 85.9%

of 177 samples were less than or equal to 20 ppb, compared to 97.9% of samples tested

in 2011.

Therefore, 14.1% of 177 samples tested in 2012 were above 20 ppb; while in 2011 only

2.1% exceeded 20 ppb.

Aflatoxin tests on 397 samples at the export level in 2012 showed 77.8% had less than

5 ppb and 22.2% were above or equal to 5 ppb but less than or equal to 20 ppb (Table 3). No

samples tested were found over 20 ppb.

The harvest aflatoxin survey results suggest there were more incidents of aflatoxin

among all Agriculture Statistic Districts (ASDs) in 2012 than in the 2011 crop season. The

higher proportion of harvest samples with aflatoxin levels exceeding 20 ppb in 2012 may in

part be due to the lower rainfall amounts and higher temperatures in June through August 2012

compared to conditions in 2011.


44

Table 3. Percentage of aflatoxin and DON tests for harvest and export corn samples in 2011 and 2012. At the export level tests were performed by FGIS, while at the harvest level tests were performed by the Identity Preserved Grain Laboratory.

Aflatoxin % Number Tests Aflatoxin Limit of detection ˂ 2.5 ppb ≥ 2.5 ≤ 20 ppb ˃ 20 ppb Harvest 2012 N=177 78.0 7.9 14.1 Harvest 2011 N=95 97.9 0 2.1 Aflatoxin Limit of detection ˂ 5 ppb ≥ 5 ≤ 20 ppb ˃ 20 ppb Export 2012 N=397 77.8 22.2 0 Export 2011 N=379 75.2 24.8 0

DON % Number Tests DON Limit of detection ˂ 0.5 ppm ≥ 0.5 ≤ 5 ppm ˃ 5 ppm Harvest 2012 N=177 96.0 4.0 0 Harvest 2011 N=94 78.7 21.3 0 DON Limit of detection ˂ 0.5 ppm ≥ 0.5 ≤ 5 ppm ˃ 5 ppmExport 2012 N=397 97.5 2.5 0 Export 2011 N=379 84.2 15.8 0

DON (deoxynivalenol or vomitoxin)

A total of 177 samples at the harvest level were analyzed for DON in 2012 (Table 3).

Results of the harvest sample testing indicated:

About 94.9% of 177 samples had no detectable levels of DON (less than the 0.5

ppm LOD).

About 5.1% of 177 samples tested greater than or equal to the LOD of 0.5 ppm, but

less than or equal to the FDA advisory level of 5 ppm. Thus, 100% of the samples

tested in 2012 were less than or equal to the FDA advisory level of 5 ppm,

compared to 78.7% in 2011 that tested below 0.5 ppm.

DON tests on 397 samples at the export level in 2012 showed 97.5% had less than 0.5

ppm while 2.5% had over 0.5 ppm but less than or equal to 5.0 ppm (Table 3). No samples

tested were found with DON greater than 5 ppm.

The DON harvest survey results indicate there were less DON contaminations in 2012

than in the 2011 crop season. The fact that 96% of harvest samples in 2012 tested below 0.5

ppm (the 2011 LOD) may be due to weather conditions and the lower rainfall in June through

August 2012 compared to 2011.


45

SUMMARY AND CONCLUSIONS

In 2012, protein averaged 9.2% at export, which was significantly higher than the 8.7%

found in 2011. Protein ranged from 8.1 to 11.2% with a standard deviation of 0.37%. The

higher protein levels found in 2012 were believed to be due to the drought conditions causing

lower levels of starch production than protein accumulation during grain fill. Starch is usually

inversely related to protein content. Thus, since protein increased, starch decreased to 73.5%

in 2012 from 74.1% found in export samples in 2011. Starch ranged from 71.8 to 75.3% with

a standard deviation of 0.49% for export samples in 2012.

Oil content averaged 3.7% in harvest and export corn in 2012, close to the 3.6% found

in 2011. Oil contents ranged from 3.1 to 4.3% with a standard deviation of 0.19%.

BCFM was low (2.7%) at the export level and low (0.8%) at the harvest level in 2012.

Stress cracks averaged 9% for export corn which was higher than the 4% found for harvest

corn; therefore, the corn should continue to handle with relatively low levels of breakage.

Test weight or bulk density in 2012 export corn averaged 58.1 lb/bu for export corn,

higher than the 57.8 lb/bu found in 2011. Similarly, true density averaged 1.297 g/cm3 for

export corn in 2012 and slightly higher than the 1.291 g/cm3 for export corn in 2011. These

two factors indicated kernel densities were higher in 2012 and not surprisingly horneous

endosperm for 2012 export samples was higher with 85%, an increase from 84% in 2011.

In spite of a drought year, average kernel volumes and 100 kernel weights (35.86 g for

export corn) were higher in 2012 than in 2011 (35.14 g). The higher 100 kernel weights usually

were indicative of larger kernel size.

Whole kernels averaged 89.9% at the export level and 94.4% at the harvest level in

2012. Both were up slightly from 2011 corn. In addition, total damage was low averaging

only 0.8% at the harvest level and 2.0% at the export level in 2012. The relatively high

percentages of whole kernels in combination with the low stress cracks provide an indication

of good storable corn that should have reduced breakage in handling.

Larger kernel size, with harder endosperm, higher density and relatively low stress cracks

should be favorable for dry millers and alkaline processors of corn. In addition, low BCFM and

low stress cracks, larger kernel size, high whole kernel percentages and low total damage should

be beneficial for wet millers.


46

Aflatoxin tests on 397 samples at the export level in 2012 showed 77.8% had less than

5 ppb and 22.2% were above 5 ppb but less than or equal to 20 ppb. No samples tested were

found over 20 ppb. The aflatoxin survey results at the harvest level suggest that there were

more incidents of aflatoxin among all ASDs in 2012 than in the 2011 crop season.

DON tests on 397 samples at the export level in 2012 showed 97.5% had less than 0.5

ppm while 2.5% had over 0.5 ppm but less than or equal to 5.0 ppm. No samples tested were

found with DON greater than 5 ppm. The DON survey results indicated there were less DON

contaminations in 2012 than in the 2011 crop season.

LITERATURE CITED

Below, F.E. April 2013. Personal communication.

Below, F.E., L.E. Christensen, A.J. Reed, and R. H. Hageman. 1981. Availability of reduced N

and carbohydrates for ear development of maize. Plant Physiol. 68:1186-1190.

Paulsen, M.R., L.D. Hill, G.C. Shove, and T.J. Kuhn. 1989. Corn breakage in overseas shipments

to Japan. Transactions of ASABE. Vol. 32(3): 1007-1014.

Swank, J.C., F.E. Below, R.J. Lambert, and R. H. Hageman. 1982. Interaction of carbon and

nitrogen metabolism in the production of maize. Plant Physiol. 70: 1185-1190.

USDA, 2013.Corn Supply and Disappearance. disappearance. World Outlook Board. April 11,

2013. http://www.ers.usda.gov/data-products/feed-grains-database/feed-grains-yearbook-

tables.aspx#26954

U.S. Grains Council, 2012. U. S. Grains Council Corn Harvest Quality Report 2012/13.

Washington D.C. http://www.grains.org/images/cornqualityreport/

201213%20Harvest%20Report/Harvest%20Report%20Final%20121205.pdf

U.S. Grains Council, 2013. U.S. Grains Council Corn Export Cargo Quality Report 2012/13.

Washington D.C. http://www.grains.org/images/Export%20Report%202012-13-

final.pdf


47

THE VALUE OF ILLINOIS LAND

Bradley Uken*

Champaign County Farm Bureau 801 N. Country Fair Dr., Champaign, IL 61821 USA


Production of corn and soybeans starts with the land and more specifically the soil. It is

believed the soils of east central Illinois coupled with our climate make us the number one

growing region in the world for corn and soybean production. Our soils are truly amazing! In

near record setting drought years such as 2012, we can still produce a crop; in wetter years like

we are seeing this year, we will still produce a crop, albeit once it is planted. An argument can

be made that seed technology has played a key role in our successes as well, and it has, but at the

end of the day, our soils are what carries us.

This past year we have seen in many places across the Midwest, record setting land

prices, prices paid for land that is not for development purposes but simply for farmers to use in

growing the safest, most abundant and most affordable food supply in the world.

Several key factors have led to these often record high prices:

1. Interest rates on certificates of deposits at banks – with low rates being offered by

banks the return from farmland is much more appealing.

2. Interest rates offered for borrowing money – low interest rates are good for borrowing

money, it is sort of an incentive to borrow money and invest in farmland.

3. Stock market returns – with the stock market in the last several years trending

downward and only until recently are we seeing an uptick in the markets, farmland

was a safe and steady investment.

4. Commodity prices – strong commodity prices have helped provide a robust return

rate on land investments.

During the last several years contrary to the general economy which has seen a severe

decline, agriculture has seen record setting returns and growth. Agriculture has been the silver

lining of the overall economy.


48

So what does the future bring? That is an excellent question that I simply cannot answer.

However, I do have a couple of thoughts:

1. Managing the soil will continue to be a priority for farmers. Fertility levels must be

increased or maintained as we move forward if we are to feed the growing world

population.

2. Tiling of the soil must continue. Though this may bring some challenges as it

pertains to nutrient runoff, we must get the water away from the soil in a timely

manner.

3. Developing a per acre “prescription” program is part of the future. By prescription I

mean using technology such as yield maps and soil sample maps to determine if a

particular acre can handle higher planted seed populations. It also will include

applying the same amount of nitrogen fertilizer a farmer may apply in a single

application but spread over multiple applications to provide that plant the “shot” in

the arm for growth and development. These are just a few examples of what these

future prescriptions may hold.

4. Prices of inputs will play a major role in land prices. For example, we have seen

gaseous nitrogen fertilizer go from $230 per ton to more than $800 per ton. Farmers

must continue to calculate this into their return rates and this will dictate the level of

cash rent they are willing to pay along with overall land prices.

5. Are we in a bubble and will it burst in the future? Perhaps, but compared to the

housing bubble we have seen in recent years, much of the purchases of land has not

been made on credit but a lot of cash payments have been made. With that said I

believe we will see some sort of settle back on land prices along with cash rents based

on a number of factors including world markets, the stock market, interest rates and

commodity prices.

Overall, the future for agriculture, I believe, looks bright. I believe land will continue to

be a sought after asset by farmers and some investors simply because we are not making more of

it and world food demand is increasing every year.


49

TROPICAL MAIZE FOR THE BIOPROCESSING INDUSTRY

Laura F. Gentry*, Gary A. Letterly, and Frederick E. Below

Crop Sciences, University of Illinois at Urbana-Champaign 1102 South Goodwin Avenue, Urbana, IL

(217) 244-9165, [email protected] An Annual Biomass Crop with Multiple Potential Utilities

Tropical maize (Zea mays L.) is a high biomass, high sugar corn hybrid that demonstrates

excellent potential as a renewable fuel crop as well as ruminant forage. Tropical maize is

produced by crossing tropical and temperate adapted maize parents (White et al 2011).

Adaptation to its subequatorial origins provides tropical maize with its photoperiod sensitivity

that, when grown in more northern latitudes, results in delayed flowering and an extended period

in the vegetative state relative to commercially grown U.S. corn hybrids (White et al 2012).

Tropical maize planted in the Midwest and North Central United States grows to be 12 to 15 ft

tall and produces little, if any, grain. Reduced grain production is offset by accumulation of

sugars in the stalk and a diminished nitrogen (N) fertilizer requirement. From its temperate field

corn germplasm, tropical maize gains beneficial agronomic production characteristics such as

adaptation to a broad geographic range, resistance to stalk lodging, higher tolerance to stress, and

greater resistance to diseases and insect pressure. Because it produces very little grain, tropical

maize requires less than 50% of the fertilizer application recommended for field corn (White et

al 2011). The reduced N fertilizer requirement of tropical maize and, consequently, its superior

nitrogen use efficiency, make it very positive from an agricultural sustainability perspective. As

a biofuel feedstock, it can produce large amounts of biomass (9 to 11 ton/acre, dry weight) and

accumulate high levels of sugar (10% sucrose) when grown without supplemental N (White et al

2012). Chen et al (2013) reported that final ethanol concentrations obtained by fermenting

extracted syrup were as great as 92% of the theoretical yield. Tropical maize also represents a

low input, renewable solid fuel source derived from crop residues that can be obtained locally,

thus greatly reducing transportation and additional processing requirements; the biomass itself

can be burned on farm or sold to local municipal, commercial or residential entities with bale


50

burning furnaces. Finally, high biomass, palatability and digestibility of tropical maize make it a

good candidate as a ruminant forage and feed crop.

Additionally, tropical maize is well adapted to many regions of the U.S., unlike

sugarcane, and it is more likely to be accepted by U.S. farmers than perennial grass crops such as

Miscanthus and switchgrass, largely because so many U.S. farmers are experienced and

equipped for producing corn. Finally, because of the genetic diversity of maize species and

breeding technologies that have resulted in unprecedented improvement in corn grain production,

tropical maize is more likely to benefit from breeding enhancements for ethanol production than

other biofuel candidates. Sorghum, in particular, presents concerns for biotechnology

advancement due to concerns about gene flow from cultivated sorghum to its close relative,

johnsongrass, a pernicious weed (Morrell et al 2005; Snow et al 2005). Invasiveness concerns

are issues that must be considered in some areas of the U.S. for dedicated perennial grasses such

as switchgrass and Miscanthus, but no such concerns exist for maize (White et al 2011).

Tropical maize presents great potential as a leading biofuel feedstock and additionally offers

value, flexibility, low risk to the producer and environmental sustainability.

As a Bioethanol Crop

One of the initial challenges posed by the Energy Independence and Security Act (EISA)

of 2007 is identifying biofuel feedstocks that are agriculturally and technologically feasible as

well as socially and environmentally acceptable. Among the possibilities for biomass crops, C4

grass species are among the most favorably considered because they exhibit the greatest

efficiencies for carbon fixation, water use and nitrogen efficiency (Ragouskas et al 2006). There

are three distinct types of biomass feedstocks that can be produced from C4 grasses: sugar, starch

and lignocellulosic biomass (White et al 2011). Currently, the major source of biofuel produced

to meet the EISA standards derives from starch in corn grain which has raised important food

security and environmental concerns. So called “second generation” biofuels are derived

primarily from corn stover, tropical maize, sorghum, sugarcane and switchgrass; among these,

only sugarcane, sweet sorghum and topical maize can provide all three types of biofuel

feedstocks. Of these three multipurpose biomass types, tropical maize has the broadest

geographic production range, possesses the greatest genetic resources for crop improvement and

is the most familiar to U.S. farmers. Other major biofuel feedstock candidates require intensive


51

and expensive start-up arrangements, long term commitment by producers, implementation of

unfamiliar agricultural practices, development and purchase of new equipment, and/or long term

economic risk to the farmer. Alternatively, tropical maize has low start up costs, no long term

commitment by producers, little additional equipment costs and very favorable risk to profit

ratio. And, unlike other grass energy crops, the technology model for ethanol and power

cogeneration using tropical maize biomass is well established and currently implemented by the

sugarcane industry in Brazil.

Efficient cellulosic bioethanol production is not yet a cost effective method of providing

liquid transport fuel, but technologies are being improved; until this technology is made feasible,

viable ethanol fermentations will focus on starches and simple sugars (White et al 2011).

Despite the fact that sugar can be processed for ethanol fermentation for about half the cost of

starch (Jacobs 2006), starch from corn grain is currently the most common feedstock used for

ethanol production in the United States. Unlike Brazil, where sugarcane can be produced

widely, sugarcane is suited to field production in just three U.S. states, Louisiana, Texas and

Hawaii. Tropical maize, however, can be grown on almost any of the approximately 90 million

U.S. corn acres (http://www.ers.usda.gov/topics/crops/corn.aspx#.UYQOEcW5KJt). In tropical

maize, sugars begin to accumulate in stalks around the time of silk emergence and are a

combination of sucrose, glucose and fructose (White et al 2012). Sucrose is the major sugar

form present until frost damages the cellular integrity of the stalk tissues, resulting in the release

of invertase, which can hydrolyze the available sucrose (White et al 2011). Sucrose can be

extracted from the stalk in a method very similar to that used in sugarcane processing and it can

be fermented easily for ethanol production. Similar to sugarcane, stover remaining after sugar

extraction from tropical maize can be burned for energy, used for cellulosic ethanol production

or mixed with dry distillers grain from ethanol plants to enhance food value for ruminant animals

(White et al 2011). Additionally, corn grain ethanol plants, located throughout the Midwest, can

be adapted to ferment sugar from tropical maize (White et al 2011).

White et al (2011) calculated the combined theoretical ethanol yield of sugar and

lignocellulosic ethanol production from select tropical maize hybrids was 25% greater than for

corn grain and required less N fertilizer inputs. In a second analysis with different hybrids,

White et al (2012) concluded that tropical maize hybrids produced the same theoretical yield of

ethanol per unit area when grown without supplemental N as commercial grain hybrids produced


52

with 180 lb N/acre when all components of both crops (sugar, grain and stover) were fully

utilized to produce ethanol. White et al (2012) also determined that tropical maize hybrids

grown with no supplemental N produced biomass levels comparable to sweet sorghum yields

produced with 125 lb N/acre in Iowa (Hallam et al 2001). In a study conducted by Chen et al

(2013) investigating ethanol fermentation potential and effects of various pretreatments of stalk

juice, 92% of the theoretical ethanol yield from tropical maize was achieved; the authors

concluded that tropical maize is a competitive alternative feedstock source for bioethanol

production. The energy balance ratio (energy invested vs energy returned) for ethanol

production from corn grain is 2.3 (Shapouri et al 2010), but the energy balance ratio of tropical

maize is in the range of 8 to 9 (White et al 2012), a value that is similar to that of sugarcane and

sweet sorghum (Goldemberg 2007). Thus, ethanol produced from tropical maize could provide

more energy per unit of land area compared to ethanol production from corn grain, making

tropical maize more efficient for energy production in terms of land usage (White et al 2011).

An additional benefit of tropical maize and one that is shared with sorghum and sugarcane, is the

potential to reduce greenhouse gas emissions by providing its own cofiring byproducts (White et

al 2011). As the sugar from the tropical maize stalks is processed, the tropical maize biomass

itself is cofired to provide energy for the sugar distillation process. Relative to gasoline, ethanol

produced from cellulose by cofiring biomass byproducts can result in an 86% reduction in

greenhouse gas emissions (Wang et al 2007). Finally, because maize has proven to be an

outstanding genetic model species, accommodating traditional breeding as well as advanced

genetic engineering of its genome (Carpita and McCann 2008) and because of the inherent

genetic diversity of all maize species (Yu et al 2008; Schnable et al 2009), tropical maize is

poised to benefit from further genetic improvements. Such improvements likely are to result

from identification of quantitative trait loci containing genes relevant for biomass increase,

sucrose concentration and cell wall properties.

As a Thermal Energy Crop

Burning tropical maize biomass as a thermal energy source is a simple, immediately

implementable and regionally centralized approach to heat generation. Unlike coal, which is

nonrenewable and requires destructive extraction procedures, grass energy crops, like tropical


53

maize, are renewable and can be produced with fewer negative environmental consequences.

Research of tropical maize for thermal energy to date has focused on two cofiring forms, bales

and pellets. Despite densification and related transport advantages of pellets, direct firing of

bales is the most energy efficient means of thermal energy production at the local scale. Bale

furnaces are flexible heat and power systems capable of utilizing a wide variety of combustible

biomass feedstocks (eg, tropical maize, Miscanthus, switchgrass) in bale form. Bale furnaces are

a common method of energy generation in Europe, where coal and other combustible energy

sources are limited. Because of their flexibility in terms of feedstock sources, bale furnaces

reduce costs and risks associated with heat generation from burning crop biomass. However,

bale furnaces are not currently widely available in the U.S. and therefore transport costs

associated with hauling biomass bales or densified biomass forms (eg, pellets, briquettes) long

distances is cost prohibitive, making it most economically effective to utilize biomass bales

locally, where bale furnaces are located. Very few bale furnaces are being manufactured at this

time. For example, the “StorMor” bale furnace (ca. 1980) is out of production. There are

several operating bale furnaces in the U.S. and there are local fabricators who are interested in

mass production. The local development and demonstration of a viable bale furnace that

achieves efficient combustion and heat conversion to useable energy can provide inspiration and

innovation in biomass energy use. The agronomic model we envision for this topical maize

utility involves growing tropical maize hybrids that have been identified as “dual purpose”

because they produce about 75 to 100 bu/acre of high quality (~11% protein) grain as well as

relatively high levels of crop biomass (6 to 7 ton/acre, dry weight) for thermal use. In this

system, growers would harvest the crop grain, which would pay for crop establishment costs

associated with seed and other inputs and would bale the biomass for their own heating purposes

or would sell it locally to commercial, municipal or residential properties heated with bale

furnaces. In the course of such an agreement, the grower could deliver bales to the facility and

remove the ash produced after the bales have been fired. We analyzed ash after cofiring and

found that it contains reasonably high concentrations of plant nutrients which can be added back

to fields to supply a portion of the P, K and micronutrients removed during crop production and

harvest. This would solve the problem of waste disposal by recycling the nutrients in an efficient

and environmentally sound manner.


54

As a Forage & Animal Food Crop

Although it has received less public scrutiny, producing adequate animal food to supply

increasing global demand for animal protein by 2050 is arguably more central to the international

food security issue than the ongoing debate regarding use of corn grain for biofuels. Presumably

this topic is not at the forefront of the U.S. public awareness because 1) animal protein is not

required for human nutrition and 2) animal protein is widely and cheaply available in the U.S.

relative to other nations. However, a brief analysis demonstrates the preference for animal

protein globally in the human diet: by adding the crop land used to produce animal feed (350

million ha) and land used for pasture and grazing, (3.38 billion ha), we find that 75% of the

world’s agricultural land is used to raise animals (Foley et al 2011). Keyzer et al (2005)

produced models based on future supply and demand scenarios for every country in the world;

previous projections of meat and animal food demand underestimate future meat consumption.

They conclude that “world cereal food demand will be significantly higher in the coming 30

years than is currently projected by international organizations, even if we allow for price

effects.” This demonstrates a need to increase efficiency of animal production systems. Feeding

trials are being conducted to gather more information regarding nutrient value and digestibility

of tropical maize. In our 2011 forage studies, over 85% of tropical maize was grazed,

demonstrating the high sugar content and impressive biomass give it strong potential for a

grazing crop. Based on previous results, we believe that tropical maize can be used to provide

complete ruminant nutrition for most animal classes. Tropical maize also offers opportunities to

extend the winter grazing season; by harvesting tropical maize in September, rye or other winter

annuals can be planted and grazed throughout the winter in the Midwest.

As an animal feed or grazing crop, tropical maize holds strong potential if managed

properly. When ensiled, tropical maize yielded crude protein levels of greater than 8% and total

digestible nutrients around 60%, making tropical maize forage quality comparable to corn silage.

In a trial conducted at two locations in 2011 (a hot, dry growing season), it was determined that

no till drilled, double cropped (planted after wheat harvest) tropical maize can produce baled

biomass of 5.5 ton/acre; for comparison, state hay yields were less than 4 ton/acre. Unlike sweet

sorghum, tropical maize does not accumulate dangerously high levels of prussic acid.


55

A Sustainable Crop

It is only reasonable that a “green energy” renewable fuel crop be produced with proven

sustainability practices and a commitment to reduced environmental impacts. In the area of

sustainability, tropical maize is a particular standout among bioenergy crops. The reduced N

fertilizer requirement for tropical maize production substantially reduces risk of N fertilizer

movement into ground and surface waters. Integration of tropical maize into cropping systems

in this region would improve nitrogen use efficiency of the Midwest landscape and reduce

eutrophication of our coastal waters. We are investigating use of cover crops and reduced tillage

(strip till) as sustainability practices in tropical maize production systems to maintain soil

productivity and build soil organic matter (Figure 1). Tropical maize particularly is amenable for

production with cover crops. A major deterrent preventing widespread use of cover crops in the

U.S. Midwest has been establishment of the cover crop following corn or soybean harvest before

frost each fall. Because tropical maize is harvested earlier than other major crops in this region,

there will be enough time following harvest for a winter cover crop to become established prior

to frost. Cover crops help protect soil from erosion, build soil organic matter, sequester

atmospheric carbon dioxide and reduce leaching losses associated with N and P fertilization, thus

protecting water quality. Strip tillage is a relatively new conservation tillage system that

establishes a tilled area in a narrow (8 to 12 inch wide) strip encompassing the crop row and

leaving the inter row area undisturbed. Strip tillage protects soil from erosion, retains plant

available water later in the growing season and allows fertilizers to be band applied for more

efficient uptake and reduced nutrient leaching and related water quality risks.

A Crop Compatible With U.S. Agriculture

A practical advantage of tropical maize relative to other energy crops is that it is planted

and managed with the same equipment as commercial grain corn and it fits into most common

crop rotations in the U.S. Midwest (Table 1). Near term implementation of tropical maize is

possible because, being derived from corn and managed like corn; it is familiar to U.S. growers.

The biggest difference between growing commercial grain corn and tropical maize is that

tropical maize requires about half the amount of fertilizer N. Because N is one of the most costly

inputs associated with corn production, there is potential to lower costs associated with tropical

maize production, while at the same time limiting environmental concern associated with N


56

fertilizer use. Most of the well established marketing, distribution, supply and transportation

infrastructures supporting corn grain production can be transferred directly to tropical maize and,

similarly, most aspects of the grain ethanol business model can be technologically transferred to

tropical maize. Finally, because tropical maize is produced for biomass, not fuel, it is largely

excluded from the “food vs. fuel” debate.

Figure 1. Wendy White with a tropical maize plant, more than 12 feet tall, conventional field corn in background.

Table 1. Distinguishing features among C4 grass feedstocks for US renewable energy. From W.G. White et al (2011), with permission.

Distinguishing Features Grain, Corn Sugarcane Sweet

Sorghum Tropical

Maize Corn Stover Switchgrass

Total annual biomass yield (~US average, dry Mg/ha)

8 25 20 20 7 10

Life Cycle Annual Perennial Annual Annual Annual Perennial

Harvestable Carbon Form(s) Starch Sugar /

Lignocellulosic Sugar / Starch / Lignocellulosic

Sugar / Starch / Lignocellulosic

Lignocellulosic Lignocellulosic

Feedstock Stability Years Days Days Days Months Months

Genetic Resources & Breeding Excellent Limited Limited Excellent Excellent Limited

Drought Tolerance Moderate Low Good Moderate Moderate Good

Cold Tolerance Good Poor Moderate Good Good Moderate

Nutrient Use Efficiency Low Low Moderate Good Low Good

Potential for Invasiveness None None Low None None Moderate

Alternative Markets Many Table Sugar Molasses/Forage Sugar / Heat /

Forage Forage Forage

Commercialization Status Current Current In development In development In development In development

U.S. Geographic Range Midwest /

North Central TX, LA, HI

Midwest / Southeast

Midwest / North Central

Midwest / North Central

Midwest / Southeast

Harvest Window September-February

September-December

August-October August-

November September-November

Fall

Fuel Conversion Efficiency Moderate High High High Low Low

Productivity on Marginal Lands Low Low Low Low Low Moderate


58

LITERATURE CITED

Carpita, N.C. and McCann M.C. 2008. Maize and sorghum: genetic resources for bioenergy

grasses. Trends in Plant Science 13: 415-420.

Chen, M.H., Kaur P., Dien B., Below F., Vincent M.L. and Singh V. 2013. Use of tropical

maize for bioethanol production. World J Microbiol Biotechnol (pagination not set).

Foley, J.A., Ramankutty N., Brauman K.A., Cassidy E.S., Gerber J.S., Johnston M., Mueller

N.D., O’Connell C., Ray D.K., West P.C., Balzer C., Bennett E.M., Carpenter S.R., Hill

J., Monfreda C., Polasky S., Rockstrom J., Sheehan J., Siebert S., Tillman D. and Zaks

D.P.M. 2011. Solutions for a cultivated planet. Nature 478: 337-342.

Goldemberg, J. 2007. Ethanol for a sustainable energy future. Science 315: 808-810.

Hallam, A.; Anderson I.C., Buxton D.R. 2002. Comparative economic analysis of perennial,

annual, and intercrops for biomass production. Biomass and Bioenergy 21: 407-424.

Jacobs, J. 2006. Ethanol from sugar: what are the prospects for U.S. sugar co-ops? Rural

Cooperatives 73: 25-38.

Keyzer, M.A.; Merbis M.D., Pavel I.F.P.W., van Wesenbeeck C.F.A. 2005. Diet shifts

towards meat and the effects on cereal use: can we feed the animals in 2030?

Eco. Econ. 55: 187-202.

Morrell, P.L., Williams-Coplin, T.D., Lattu, A.L., Bowers, F.E., Chandler, J.M. Paterson, A.H.

2005. Crop-to-weed introgression has impacted allelic composition of johnsongrass

populations with and without recent exposure to cultivated sorghum. Mol. Ecol. 14:

2143-2154.

Ragouskas, A.J., Williams, C.K., Davison, B.H., Britovsek, G., Cairney, J., Eckert, C.A.,

Frederick, W.J., Hallet, J.P., Leak, D.J., Liotta, C.L., Mielenz, J.R., Murphy, R., Templer,

R., Tschaplinski, T. 2006. The path forward for biofuels and biomaterials.

Science 311: 484-489.

Schnable, P. et al. [158 authors]. 2009. The B73 maize genome: complexity, diversity and

dynamics. Science 326: 1112-1115.

Shapouri, H., Gallagher, P.W., Nefstead, R. 2010. 2008 Energy Balance for the Corn-Ethanol

Industry. Agricultural Economics Report Number 846, Office of Energy, Policy,

and New Uses, Office of the Chief Economist, U.S. Department of Agriculture,

Washington D.C.


59

Snow, A.A., Andow, D.A., Gepts, P., Hallerman, E.M., Power, A. Tiedje, J.M., Wolfenbarger,

L.L. 2005. Genetically engineered organisms and the environment: current status and

recommendations. Ecol. Appl. 15: 377-404.

Wang, M., Wu, M., Hong, H. 2007. Life-cycle energy and greenhouse gas emission impacts of

different corn ethanol plant types. Environ. Res. Letter 2: Art No. 024001.

White, W.G., S.P. Moose, C.F. Weil, M.C. McCann, N.C. Carpita, F.E. Below. 2011. Tropical

Maize: Exploiting Maize Genetic Diversity to Develop a Novel Annual Crop for Biomass

and Sugar Production. Routes to Cellulosic Ethanol pp. 167-179, M.S. Buckeridge and

G.H. Goldman (eds.) Springer Science + Business Media, LLC.

White, W.G.; M.L. Vincent, S.P. Moose, F.E. Below. 2012. The sugar, biomass and biofuel

potential of temperate by tropical maize hybrids. GCB Bioenergy. doi: 10.1111/j.1757-

1707.2012.01158.x

Yu, J.M., Holland, J.B., McMullen, M.D. Buckler, E.S. 2008. Genetic design and statistical

power of nested association mapping in maize. Genetics 178: 539-551.


60

ENZYMES IN STARCH PROCESSING: NEW ENZYMES FOR THE PRODUCTION OF SPECIALTY SYRUPS

Pauline Teunissen*, Tom Kleinhout, Bart Koops,

Sung Ho Lee and Donald Ward

Danisco US Inc. 925 Page Mill Road, Palo Alto, CA 94304


Most common products in the current carbohydrate processing market are glucose (DP1),

fructose and maltose (DP2) syrups and maltodextrins (DE 6 to 20). Most of the production of

these commodity or semicommodity ingredients relies on enzymatic conversions. Alpha-

amylases are used in liquefying the starch and for production of low conversion products; eg,

maltodextrins. Glucoamylases and beta-amylases are used in saccharification resulting in

glucose (or dextrose) and maltose syrups. Glucose isomerase can be used to catalyse the

isomerisation of glucose into fructose; eg, to make high fructose corn syrup. In the past decade

the availability of market products has not changed dramatically, in fact both products and

processes have not seen much change.

With the right technology, the boundaries of the carbohydrate processing market can be

pushed into new territories; a technology which combines processing know-how with the right

tools. DuPont Industrial Biosciences is expanding its carbohydrate processing portfolio with two

new enzymes for specialty syrups. The first is a maltogenic alpha-amylase expressed in Bacillus

licheniformis. This amylase adds value to carbohydrate processing; due to its broad pH and

temperature range and temperature dependent specific activity it proves to be an excellent

enzyme for a variety of maltose applications.

The second product to be presented is a maltotetraose producing amylase from

Pseudomonas saccharophilia expressed in Bacillus licheniformis. OPTIMALT® 4G is able to

convert liquefied starch into more than 45% of maltotetraose and even more than 60% when

used in combination with a debranching enzyme. Its optimal performance matches industrial

standard conditions for maltose production, typically pH 5.0 to 5.5 at a temperature of 60°C with


61

32% DS substrate and DE 10. Maltotetraose syrup has a wide range of applications, among

others within food products it prevents hygroscopicity and colouration, it regulates the freezing

point, it increases viscosity and the syrup itself has a clean taste and mild sweetness. This unique

enzyme will bring opportunities for new products for the carbohydrate processing market.


62

IMPACT OF DEFICIT IRRIGATION ON CROP PHYSICAL AND CHEMICAL PROPERTIES AND ETHANOL YIELD

Donghai Wang*, Liman Liu, Norman Klocke,

Danny Rogers, Freddie Lamm and Alan Schlegel

Biological and Agricultural Engineering, Kansas State University 147 Seaton Hall, Manhattan, Kansas, 66506

(785) 532-2919, [email protected] ABSTRACT

Irrigation had a significant effect on physical properties, chemical compositions, ethanol

yields and fermentation efficiencies of sorghum and corn crops. Sorghum kernel hardness

increased and test weight decreased as irrigation level decreased. Corn kernel weight, density

and breakage susceptibility were decreased as irrigation level decreased. Starch contents of corn

and sorghum samples grown under a low irrigation level were less than those grown under a high

irrigation level. Protein contents increased as irrigation level decreased. Starch pasting

temperature increased significantly and starch peak pasting viscosity and setback viscosity

decreased as the irrigation level decreased. Free amino nitrogen (FAN) increased as irrigation

decreased. Ethanol fermentation efficiency correlated positively with FAN during the first 30 hr

of fermentation. Deficit irrigation level had a negative impact on ethanol yields of corn and

sorghum.

INTRODUCTION

Irrigated agriculture is the primary user of water resources globally and consumes 70 to

80% of total diverted water in arid and semi-arid zones (Fereres and Soriano 2007). Irrigated

agriculture used more than 70% of water withdrawn from earth’s rivers (Heng 2002). Crop

production is dependent on water availability and shortages have an impact on final yields (Kirda

2002; Tognetti et al 2006; Quiroga et al 2011); however, water is a finite resource for which

competition is increasing among agricultural, industrial and domestic sectors. Meeting increased

demand for food production and food security with less water availability is a challenge.


63

With reduced water resources available for agriculture, scientists and engineers have

developed innovative technologies such as deficit irrigation programs aimed at increasing

efficient use of irrigation water (Kirda 2002; Tognetti et al 2006; Fereres and Soriano 2007).

Water deficits during a specific crop development period significantly affect crop yield (bu/acre);

therefore, the yield response to water stress has been studied extensively. Previous research

reported that grain yields decrease as irrigation level decreased (Kirda et al 2005; Fereres and

Soriano 2007; Ayana 2011). Pandey et al (2000) studied effects of deficit irrigation and nitrogen

on maize and found that grain yield reduction was proportional to duration of deficit irrigation.

Because maize is an important irrigated crop, field research has been conducted on maize to

study the relationship between irrigation and yields. Klocke et al (2007) studied yield and

irrigation for maize from 1986 to 1998 in west central Nebraska and found that 90% of full

irrigation grain yields could be gained by applying only 47% of full irrigation. Klocke et al

(2011) conducted a field study of fully irrigated to deficit irrigated maize from 2005 to 2009 in

southwest Kansas and reported that yield variability increased as irrigation decreased, illustrating

a greater income risk with less irrigation.

As water resources continue to decline, deficit irrigation is becoming an important

strategy for minimizing agricultural water uses. Limited or deficit irrigation may affect not only

crop yields, but also grain quality and end uses; however, little attention has been paid to the

effects on grain quality and end use quality, such as in the area of ethanol production. The

objective of this research was to study effects of deficit irrigation on the physical and chemical

properties and ethanol fermentation performance of corn and sorghum.

MATERIALS AND METHODS

Materials

Corn samples: Twenty corn samples were grown in a 5 yr rotation of corn-corn-wheat-

sorghum-sunflower (Corn-Corn) and sunflower-corn-corn-wheat-sorghum (GS-Corn) starting in

2005 and continuing through 2011. GS-Corn and Corn-Corn treated with five irrigation levels

(457, 356, 254, 178 and 102 mm water) were evaluated for physical and chemical properties and

ethanol fermentation performance.

Sorghum samples: Sorghum was grown in a 5 yr rotation of corn-corn-wheat-sorghum-

sunflower from 2005 to 2011. Five irrigation levels (304.8, 228.6, 177.8, 127.0 and 76.2 mm


64

water) were achieved by increasing the time between irrigation events, which were intended to

simulate differences in irrigation system capacity to deliver water using a constant irrigation

amount per event. Irrigation treatments were replicated four times with random locations in each

replication.

The irrigation variable was achieved by increasing the number of days between irrigation

events rather than applying a percentage of full irrigation during each irrigation event. The prior

year’s irrigation treatment effects carried over to the same irrigation treatment in the following

year. Each crop was present every year in five cropping blocks, which were replicated over the

five years. The irrigation treatment protocol was designed to include operational constraints of

commercial center pivot irrigation systems in the Great Plains region, where pumping capacities

limit the frequency of irrigation events. Cultural practices, hybrid selections, planting techniques

and fertilizer and herbicide applications were the same across irrigation treatments and followed

the requirements of no-till management (Klocke et al 2011). This research was conducted at the

Kansas State University Southwest Research-Extension Center near Garden City, Kansas. The

climate is semi arid with long term average annual precipitation of 477 mm, mean summer

growing season daytime high temperature of 29°C (30 yr average May through August), open

pan evaporation (April through September) of 1810 mm and a frost free period of 170 days.

During the study, average annual precipitation was 495 mm.

Methods

Sample Preparation: Corn samples were screened using a Gamet sieve shaker (Dean

Gamet Mfg. Co., Minneapolis, MN) with a 6.35 mm screen and were hand cleaned to remove

large foreign materials. Sorghum samples were hand picked to remove large foreign materials.

For ethanol fermentation, cleaned corn and sorghum samples were finely ground by passing each

through a 0.5 mm screen on a UDY Cyclone Mill (UDY Corporation, Fort Collins, CO).

Physical Properties of Corn and Sorghum Kernels: Kernel density was determined

with an air comparison pycnometer (Model No. MVP-1, Quantachrome Corporation, Syosset,

NY) as described by Pomeranz et al (1984). The 1000 kernel weights were obtained from the

kernel weight of 1000 whole, sound kernels. Test weight was determined by AACC Approved

Method 55-10 (AACC International 2000). Corn kernel breakage susceptibility was tested with


65

a Stein breakage tester (model CK2) using AACC Approved Method 55-20 (AACC International

2000). Sorghum single kernel hardness, weight and size were characterized with the single

kernel characterization system (SKCS 4100, Perten Instruments, Huddinge, Sweden) according

to Bean et al (2006). Microstructures of corn and sorghum endosperm were examined using a

Hitachi S-3500N scanning electron microscope (SEM) with an S-6542 absorbed electron

detector (Hitachinaka, Ibaraki, Japan).

Chemical Composition of Corn and Sorghum: Total starch was analyzed using AACC

Approved Method 76-13 (AACC International 2000). Crude protein was analyzed using AOAC

Approved Methods 990.03 (AOAC International 1999). Free amino nitrogen (FAN) was

determined through the European Brewery Convention method (EBC, 1987) with modification.

A Brabender Micro Visco-Amylo-Graph® -U (MVAG-U, Model # 803222, Brabender GmbH &

Co. KG, Duisburg, Germany) was used to test pasting properties of corn and sorghum flour.

Thermal properties were analyzed using TA DSC Q200 instrument. Ethanol fermentation was

following the procedure described by Wu et al (2006).

RESULTS AND DISCUSSION

Effects on Physical Properties and Chemical Composition of Corn and Sorghum Samples

Corn kernel weight, density and breakage susceptibility were decreased as irrigation level

decreased (Table 1 and Figure 1). Crop rotation had an effect on corn test weight and true

density. For Corn-Corn rotation, the grain test weight and true density did not keep decreasing

like the trend of GS-Corn rotation, when irrigation level decreased from level 3 to level 4 and 5

(Figure 1C and 1D). Sorghum kernels from low irrigation levels had a higher hardness index

than those from the high irrigation level (Table 1). Grain grown under drought conditions would

have higher kernel hardness (Taylor et al 1997; Weightman et al 2008). In this study, sorghum

kernel hardness was significantly related to protein content (P < 0.001) and played an important

role in ethanol yield (P < 0.05). Sorghum samples treated with high irrigation levels had a higher

test weight than those treated with low irrigation levels.

Starch contents of both corn and sorghum samples grown under a low irrigation level

were lower than those under a high irrigation level (Table 1). Protein contents of corn samples

ranged from 9.24 to 11.30% and of sorghum samples ranged from 10.14 to 14.86%, both


66

increased as irrigation level decreased (Table 1). It was expected that the grain protein content

would be higher in the most drought conditions (Guttieri et al 2000; Weightman et al 2008).

Samples with high starch content and low protein content are a better choice for fuel ethanol

production. Higher starch means higher ethanol yield, better processing efficiency and less

leftover residues after fermentation.

Maize

IrrigationMaize-MaizeGS-Maize

5432154321

340

320

300

280

260

240

220

1000

Ker

nel

wt.

(g)

Individual Value Plot of 1000 Kernel wt. vs Maize, Irrigation

Maize


5432154321

8

7

6

5

4

3

Bre

akag

e (%

)

Individual Value Plot of Breakage vs Maize, Irrigation

Maize


5432154321

0.81

0.80

0.79

0.78

0.77

0.76

Test

wt.

(g/

cm^

3)

Individual Value Plot of Test wt. vs Maize, Irrigation

Maize


5432154321

1.33

1.32

1.31

1.30

1.29

1.28

Tru

e de

nsi

ty (

g/cm

^3)

Individual Value Plot of True density vs Maize, Irrigation

Figure 1. Physical properties for corn grown in different rotations and irrigation levels (two way ANOVA; P < 0.05); A: 1000 kernel weight. B: Breakage. C: Test weight. D: True density. : two observations; : mean value.

A B

C D

Table 1. Physical properties, chemical composition, ethanol yield and fermentation efficiency of corn and sorghum samples[a].

[a] Means in the same column followed by different superscript letters indicate significant differences (P < 0.05). * Fermentation efficiency

Irrigation level

1000 kernel wt. (g)

Breakage (%)

Kernel hardness

index

Single kernel

wt (mg)

Kernel diameter

(mm)

Test weight (g/cm3)

True density (g/cm3)

Total starch

(%, db)

Crude protein (%, db)

FAN (mg/L)

Ethanol yield

(mL/ kg)

Ferm. efficiency

(%) 1=High; 5=Low

GS-Corn

1 329.85a 7.70a - - - 0.805a 1.322a 69.45a 9.24d 36.30e 458.6a 91.86ab

2 318.85b 7.72a - - - 0.803a 1.318b 70.02a 9.35c 36.33e 45.8.9a 91.18b

3 228.65f 2.94d - - - 0.790bc 1.304c 68.03bc 10.49b 38.50de 452.3bc 92.48a

4 273.85d 6.22b - - - 0.787c 1.300d 66.93d 11.30a 40.89cd 442.2d 91.91b

5 258.50e 5.96b - - - 0.762d 1.292e 66.46d 11.20a 45.72b 441.4d 92.11ab

Corn-Corn

1 320.15ab 5.70bc - - - 0.809a 1.321a 69.98a 9.59c 39.20cd 457.6ab 90.96bc

2 312.65b 6.06b - - - 0.806a 1.318b 69.82a 9.76c 38.56d 459.2a 91.49b

3 261.40e 3.47d - - - 0.797b 1.308c 68.66b 10.70b 40.35c 450.4c 91.26b

4 272.70d 5.13c - - - 0.795b 1.307c 68.12c 11.02a 45.12b 447.8c 91.44b

5 286.50c 5.20c - - - 0.790bc 1.309c 67.38d 10.99a 47.08a 444.1d 91.68b

Sorghum 1 24.05a - 71.82b 23.73a 2.09a 0.770a 1.359a 72.45a 10.14b 41.11b 473.3a 90.61a

2 23.25a - 78.26b 23.04a 2.05a 0.769a 1.368a 70.95a 11.29b 42.05b 466.9a 90.86a

3 24.40a - 86.16a 24.79a 2.18a 0.770a 1.368a 70.15a 12.38b 45.64b 460.8ab 91.15a

4 24.05a - 84.77a 23.58a 2.11a 0.747b 1.364a 66.90b 13.85a 52.65a 442.4b 91.36a

5 26.00a - 84.59a 26.72a 2.16a 0.745b 1.365a 65.45b 14.86a 54.75a 434.5b 91.39a


68

Figure 2A. SEM images of starch granules and protein matrix in corn endosperm from GS-Corn kernels (irrigation level 1 = highest; 5 = lowest). SG: Starch granule; PB: Protein body.

GS-Corn 217; irrigation level 2



SG

SG

PB

GS-Corn 117; irrigation level 1 GS-Corn 318; irrigation level 4


69

Figure 2B. Scanning electron microscope images of starch granules and protein matrix in sorghum endosperm (irrigation level 1 = highest; 5 = lowest) (SG, starch granule; PB, protein body; CW, cell wall).

Sorghum 425; Irrigation level 1





SG

SG

PB

CW

CW

PB


70

The SEM images from GS-Corn endosperm and sorghum endosperm showed the starch

granule size of the samples with low irrigation levels were smaller than granules from high

irrigation levels (Figure 2). Small starch granules were embedded in the protein matrix and may

have remained ungelatinized during the cooking process, thus were not degradable into glucose

for yeast fermentation by hydrolytic enzyme (Wang et al 2008).

Starch gelatinization onset, peak and conclusion temperature of the corn samples treated

with low irrigation levels were higher than in samples treated with high irrigation levels as

determined by DSC (Figure 3). Enthalpies of gelatinization (ΔHgel) from all corn samples

increased as irrigation level decreased.

MVAG-U starch pasting profiles of corn and sorghum samples treated with low irrigation

levels showed a higher pasting temperature, lower peak viscosity and lower setback viscosity

than samples treated with high irrigation levels (Table 2 and Figure 4).


71

60 70 80 90 100 110 120 130 140

Heat flow µ

W

Temperature °C

GS‐Corn

32154

Figure 3. A: DSC curve for GS-Corn samples from five different irrigation levels (1 = highest; 5 = lowest). B: DSC curve for Corn-Corn samples from five different irrigation levels (1 = highest; 5 = lowest).

A

B

Table 2. Starch pasting properties of corn samples.[a]

Samples

Irrigation level

BOG[b] Peak Start of holding

Start of cooling

End of cooling

Breakdown Setback

1 = High; 5 = Low

Temp [°C]

Torque [BU]

Torque [BU]

Torque [BU]

Torque [BU]

Torque [BU]

Torque [BU]

GS-Corn

117 1 73.3e 162c 160b 158b 417a 4.5a 256.0b

217 2 73.2e 175a 170a 170a 443a 4.5a 272.5a

218 3 76.0b 127d 119c 125c 326b 2.0c 201.0e

318 4 76.0b 111f 102d 110d 287c 1.0d 177.0f

116 5 76.5a 112f 108d 110d 287c 1.5cd 176.5f

Corn-Corn 119 1 73.2e 169b 164b 165a 426a 4.0a 266.0ab

221 2 72.8e 159c 152b 156b 396a 3.0a 240.0c

124 3 75.4c 133d 124c 132c 348b 1.0d 215.5d

123 4 75.9b 122e 115c 120cd 322b 1.5cd 202.0e

120 5 75.1d 125e 120c 123cd 327b 2.0c 203.5e

[a] Means in the same column followed by different superscript letters indicate significant differences (P < 0.05). [b] BOG – beginning of gelatinization


73

Figure 4. Starch pasting properties of sorghum samples from five different irrigation levels (1 = highest; 5 = lowest).

Deficit irrigation had a negative impact on ethanol yield. Corn with low irrigation

yielded about 4.0% less ethanol than corn with higher irrigation; sorghum with low irrigation

yielded about 8.9% less ethanol than samples with higher irrigation (Table 1). Free amino

nitrogen (FAN) in corn and sorghum was affected by irrigation level; it increased as irrigation

decreased (Table 1). Ethanol fermentation efficiency of corn and sorghum positively correlated

with FAN during the first 30 to 32 hr of fermentation (Figure 5).

By monitoring changes in conversion efficiency through the 72 hr fermentation process,

dynamics in the process of reaching their final efficiencies were quite different. Samples from

the low irrigation level had higher conversion efficiency than samples from the high irrigation

level, which we observed during the first 36 hr for both corn and sorghum (Figure 6).

Residual starch contents in the distillers dried grains with solubles (DDGS) of corn

samples were in a range of 0.80 to 1.02% and were below 1% for sorghum samples (Table 3).

DDGS of both corn and sorghum samples with low irrigation levels had higher crude protein

content (Table 3), which means better quality for livestock food uses.

1 2

3 4

5

1 23 4 5

Temp (°C)


74

Figure 5. A: Linear correlation between free amino nitrogen content (mg/L) in 20 original corn samples and fermentation efficiency after 32 hr of fermentation. B: Linear correlation between free amino nitrogen content (mg/L) in original sorghum samples and fermentation efficiency after 30 hr of fermentation.

A

B


75

Figure 6. A: Relationship between fermentation efficiency and fermentation time among 20 corn samples from five different irrigation levels (1 = highest; 5 = lowest). B: Relationship between fermentation efficiency and fermentation time among sorghum samples from five different irrigation levels (1 = highest; 5 = lowest).

A

B


76

Table 3. Chemical Composition of Distillers Dried Grain with Solubles from Corn and Sorghum Samples (%, db).[a]

Irrigation level

Chemical composition (%, db)

Total starch

Crude protein

Crude fat Crude fiber

Ash

1=High; 5=Low

GS-Corn 1 0.96a 30.36d 9.73a 3.94a 5.16a

2 0.94a 30.44d 10.09a 4.40a 5.01a

3 1.01a 32.86b 9.69a 4.78a 4.93a

4 0.81a 33.78a 9.32a 3.91a 4.70a

5 0.80a 32.98b 9.10a 4.40a 5.27a

Corn-Corn 1 0.95a 31.02cd 9.88a 4.76a 4.96a

2 0.92a 31.20c 9.62a 3.90a 4.80a

3 1.02a 33.08b 9.48a 3.90a 4.62a

4 0.88a 33.80a 9.48a 3.92a 4.89a

5 0.85a 32.74b 9.18a 4.16a 5.00a

Sorghum 1 0.70b 33.04b 10.20a 4.24a 5.40a

2 0.74ab 35.89ab 10.08a 4.90a 5.16a

3 0.84a 37.28ab 9.52a 4.14a 5.08a

4 0.81ab 39.82a 9.37a 4.03a 4.91a

5 0.78ab 39.47a 8.76a 3.76a 4.96a

[a] Means in the same column followed by different superscript letters indicate significant differences (P < 0.05).


77

CONCLUSIONS

Deficit irrigation had effects on grain physical properties, chemical compositions and

ethanol yields. Grain kernel weight, density and breakage susceptibility decreased as irrigation

level decreased. Starch contents in samples at the low irrigation level were lower than those at

the high irrigation level and gave the lowest ethanol yield. FAN contents increased as irrigation

level decreased and affected fermentation efficiency at the early stage (the first 36 hr), which had

a positive linear correlation with 30 to 32 hr fermentation efficiency. The starch granule size

was affected by irrigation level and the starch-protein matrix in the grain may affect fermentation

efficiency. Crop rotation had effects on grain test weight and true density.

ACKNOWLEDGMENT

This research was supported in part by the Ogallala Aquifer Program, a consortium

among USDA Agricultural Research Service, Kansas State University, Texas AgriLife Research,

Texas AgriLife Extension Service, Texas Tech University and West Texas A&M University.

LITERATURE CITED AACC International. 2000. Approved methods of the American association of cereal chemists,

10th Ed. Methods 55-10, 55-20 and 76-13. The Association: St. Paul, MN.

AOAC. 1999. Official Methods of Analysis of AOAC International. Methods 990.03, 920.39 and

942.05, eighteenth ed. AOAC International, Gaithersburg, MD.

AOCS. 2006. Approved Procedure Ba 6a-05. ANKOM Technology Method 10.

Ayana, M., 2011. Deficit irrigation practices as alternative means of improving water use

efficiencies in irrigated agriculture: case study of maize crop at Arba Minch Ethiopia.

African J. Agric. Res. 6: 226–235.

Bean, S. R., O. K. Chung, M. R. Tuinstra, J. F. Pedersen and J. Erpelding. 2006. Evaluation of

single kernel characterization system (SKCS) for measurement of sorghum grain

attributes. Cereal Chem. 83(1): 108–113.

EBC. 1987. Free amino nitrogen-ninhydrin colorimentric method. Pp E141–142 in Analytical

EBC, 4th Ed. Braurei Getraenke Rundschau: Zurich.


78

Fereres, E. and Sorizno, M.A. 2007. Deficit irrigation for reduced agricultural water use. J. of

Experimental Botany 58: 147–159.

Guttieri, M. J., Ahmad, R., Stark, J. C. and Souza, E. 2000. End-use quality of six hard red

spring wheat cultivars at different irrigation levels. Crop Sci. 40: 631–635.

Heng, L. K. 2002. Deficit irrigation practices 22 FTP-FAO. Food and agriculture organization of

the United Nations. ISSN 1020–1203.

Kirda, C. 2002. Deficit irrigation scheduling based on plant growth stages showing water stress

tolerance In Water Report: Deficit Irrigation Practices. Food and Agri. Organization the

United Nations, NY.

Kirda, C., S., Topcu, H., Kaman, A. C., Ulger, A., Yazici, M. and Certin, M. R. Derici. 2005.

Grain yield response and N-fertilizer recovery of maize under deficit irrigation. Field

Crops Res. 93: 132–141.

Klocke, N. L., Payero, J. O. and Schneekloth, J. P. 2007. Long-term response of corn to limited

irrigation and crop rotation. Trans. ASABE 50: 2117–2124.

Klocke, N. L., Currie, R. S., Tomsicek, D. J. and Koehn, J. W. 2011. Corn yield response to

deficit irrigation. Am. Soc. Agric. Biolo. Engi. 54: 931–940.

Pandey, R. K., Maranville, J. W. and Admou, A. 2000. Deficit irrigation and nitrogen effects on

maize in a sahelian environment I. Grain yield and yield components. Agri. Water

Management 46: 1–13.

Pomeranz, Y., Martin, C. R. Traylor, D. D. and Lai, F. S. 1984. Corn hardness determination.

Cereal Chem. 61: 147.

Taylor, F. R. N., Dewar, J., Taylor, J. and von Ascheraden, R. F. 1997. Factors affecting the

porridge-making quality of South African sorghums. J. Sci. Food Agric. 73: 464–470.

Tognetti, R., d’Andria, R., Lavini, A. and Morelli, G. 2006. The effect of deficit irrigation on

crop yield and vegetative development of Olea europaea L. (cvs. Frantoio and Leccino).

European J. Agronomy 25: 356–364.

Wang, D., S. R. Bean, J. McLaren, P. Seib, R. Madl, M. Tuinstra, Y. Shi, M. Lenz, X. Wu, R.

Zhao. 2008. Grain sorghum is a viable feedstock for ethanol production. J. Ind.

Microbiology Biotech. 35(5): 313–320.


79

Weightman R. M., Millar S., Alava J., Foulkes M. J., Fish L. and Snape J. W. 2008. Effects of

drought and the presence of the 1BL/1RS translocation on grain vitreosity, hardness and

protein content in winter wheat. J. Cereal Sci. 47: 457–468.

Wu, X., Zhao, R., Wang, D., Bean, S.R., Seib, P.A., Tuinstra, M.R., Campbell, M. and Brien,

A.O. 2006. Effects of amylose, corn protein and corn fiber contents on production of

ethanol from starch-rich media. Cereal Chem. 83: 569–575.


80

POTENTIAL APPLICATIONS FOR AMYLOSE INCLUSION COMPLEXES PRODUCED BY STEAM JET COOKING

Frederick C. Felker*1, James A. Kenar1, Jeffrey A. Byars1,

Mukti Singh1, Sean X. Liu1 and George F. Fanta2

1Functional Foods and 2Plant Polymer Research Units National Center for Agricultural Utilization Research, Agricultural Research Service, United

States Department of Agriculture 1815 N. University Street, Peoria, IL 61604

(309) 681-6663, [email protected] Starch granules isolated from cereal grains or tubers consist primarily of amylose, a

straight chain polymer of α-(1,4)-linked glucose units and amylopectin, a much larger starch

molecule with α-(1,6) branches. The linear nature of amylose in conjunction with the torsion

angles around the α-(1,4) glucan bonds confer a natural helical twist to the amylose chain. When

amylose is in solution and these helices spontaneously form, it happens that most of the hydroxyl

groups are on the outside, providing a relatively hydrophobic interior channel. Therefore, any

available molecule with an aliphatic structure compatible with the volume of the helix can form

an inclusion complex with amylose. Complexes with fatty acids have been most often described

and characterized.

Most published research about amylose inclusion complexes involves very small,

laboratory scale preparations, typically using purified amylose dissolved in water, alkali or

dimethysulfoxide (DMSO). Numerous ligands have been reported to form inclusion complexes

and these have been characterized in great detail with sophisticated analytical methods. In

addition to studies of amylose complexes specifically synthesized for research purposes, the

involvement of starch complexes in practical applications such as inhibition of bread staling have

been investigated. Despite the extensive and rapidly increasing body of knowledge about

amylose inclusion complexes, little emphasis has been placed on their commercial utilization,

although many potential applications have been reported. We have established that steam jet

cooking provides a relatively simple, direct and environmentally benign method of preparing

large quantities of complexes and we are exploring some practical applications that will

ultimately enhance the utilization of starch in food and industrial products.


81

Steam Jet Cooking

Many applications of starch require heating (cooking) the starch granules in hot water to

disrupt the granule structure to form aqueous dispersions of amylose and amylopectin, which can

be used as a liquid, gel, or dried by various techniques. Steam is widely used to provide the heat

for cooking starch; technology for cooking starch on an industrial scale has changed very little

for much of the 20th century. A primitive, continuous steam cooking apparatus was described

(Coppock 1940) and an engineering improvement described later (Winfrey and Black 1964)

introduced the possibility of applying excess steam flow to improve the properties of the cooked

starch dispersion. Modern jet cookers can be used in the “thermal” mode to apply just enough

steam to gelatinize or paste the starch granules (Kasica and Eden 1992), or in the “excess steam”

mode, in which additional steam flow reduces the viscosity and molecular weight of the starch

(Klem and Brogly 1981, Dintzis and Fanta 1996). Byars (2003) discovered that the increased

shear forces encountered in excess steam jet cooking were most significant in reducing the

molecular weight of waxy starch.

Steam jet cooking equipment is commercially available from numerous companies in a

broad range of throughput capacities, from research scale (1 liter/min) to industrial scale

(>10,000 gpm). As a thermomechanical processing technique, steam jet cooking does not

chemically modify the starch other than reduction of molecular weight, depending on heat and

shear conditions. The degree of sophistication of available jet cooking systems with respect to

control, automation and documentation varies widely.

Starch-Lipid Composites

A discovery was made in the 1990s at NCAUR when a coarse mixture of soybean oil and

cornstarch was passed through an excess steam jet cooker. The resulting starch dispersion

contained oil droplets from 1 to 10 µm diameter that did not coalesce with time, even after

prolonged storage (Fanta and Eskins 1995). The stability of the encapsulated oil in liquid and

drumdried forms was demonstrated, suggesting a specific starch-oil interaction (Knutson et al

1996). Microscopy of the composites revealed a boundary layer around the oil droplets

consisting of starch and starch-fatty acid complexes (Fanta et al 1999). Figure 1 shows a light

micrograph of a typical composite in liquid form and the shells that form around the oil droplets


82

Figure 1. Light micrograph (left) of liquid starch-soybean oil composite prepared by steam jet cooking. SEM images (center, right) of starch shells revealed by dispersing isolated coated droplets into ethanol, which dehydrated the starch and extracted the oil. as revealed by SEM after precipitating the adhering starch and extracting the oil with ethanol.

The crystalline nature and composition of the adsorbed starch layers was described by Fanta et al

(2001).

The basic research on the chemistry and physics of jet cooked starch-oil composites

supported the development of many applications using the technology, including fat replacers in

ground beef patties (Garzon et al 2003a), cookies (Garzon et al 2003b), soft serve ice cream

(Byars 2002) and yogurt (Singh and Byars 2009). Nonfood applications demonstrating the

efficacy of oil delivery in an aqueous starch based medium included biodegradable polyurethane

foams (Cunningham et al 1997) and lubricants for water-based oil drilling muds (Sifferman et al

2003) and metalworking (Kenar et al 2009). Using this technology to deliver a soybean oil

based UV absorbing agent to provide UV protection in cosmetic and agricultural adjuvant

applications was shown to increase the efficiency of UV absorption (Compton et al 2007).

Starch Spherulites

In addition to the involvement of amylose inclusion complexes in the stabilization of

starch-lipid composites, it was observed that spherical, lobed and toroidal spherulites formed in

slowly cooled, jet cooked starch dispersions under certain conditions. Davies et al (1980)

described the formation of spherocrystalline particles composed of helical inclusion complexes

of amylose with native lipids normally present in starch granules. Similar particles were noted,


83

but not described, in other reports (Zobel 1988, Jane et al 1996, Heinemann et al 2003). The

crystallization of uncomplexed amylose into various structures, including spherulites, has been

studied in the context of investigations of in vivo starch granule biosynthesis (Buleon et al 2007,

Ziegler et al 2005). A detailed description of the various morphological types of these

spherulites obtained under the jet cooking conditions established at NCAUR was first made in

2002 (Figure 2) (Fanta et al 2002). Conditions for their formation were investigated further by

using defatted cornstarch and supplementing the starch with specific fatty acids (Fanta et al

2006). Spherulite yields of about 60%, based on total starch, were obtained; the type of

spherulites could be modified by selecting cooling rates and stirring conditions for jet cooked

starch dispersions (Fanta et al 2008). The identity of the fatty acid ligands contained in the

various spherulite types was determined by extraction and analysis (Peterson et al 2005).

Figure 2. Phase contrast (top) and SEM (bottom) images of spherical/lobed (left) and toroidal (right) spherulites obtained from slowly-cooled dispersions of steam jet cooked starch.


84

A remarkable characteristic of these particles is that in a given experiment essentially all

of the spherulites of a particular morphology are of similar size, even though the size obtained

varies considerably between experiments. Considerable work has been done to sort out the

factors that drive the formation of a particular type of spherulite particle; it was discovered that

crystal transformations can take place after their formation by changes in parameters such as

hydration and organic extraction (Shogren et al 2006). Submicron spherulites formed by rapidly

cooling dispersions of high amylose starch jet cooked with oleic or palmitic acids could be dried

and then reconstituted into gel like dispersions with spreadability similar to shortening (Byars et

al 2009). Although the formation of crystalline spherulites after jet cooking starch is considered

an undesirable problem in the papermaking industry, if their formation can be controlled and

amplified by deliberate processing methods, a potentially valuable new form of durable,

biobased and biodegradable particulate material could be produced commercially using green

technology and inexpensive, biobased feedstocks.

Methods of Preparing Amylose Inclusion Complexes

Numerous investigators have dealt with small scale preparation of a variety of amylose

inclusion complexes utilizing ligands including iodine, dimethyl sulfoxide, cyclic and aliphatic

alcohols, fatty acids and their corresponding derivatives, monoglycerides, aliphatic and aromatic

esters, cyclic and aliphatic hydrocarbons, surface active compounds and other polymeric

materials. Many reaction conditions such as concentration, starch type, temperature, pressure,

shear, solvents and cooling rates have been used to prepare amylose complexes. In some cases,

even when the same ligand is used, the resulting complexes can have different properties. This is

not surprising, since starch type may vary and factors such as molecular weight, polydispersity,

degree of branching, polymer concentration and crystallization conditions are expected to

influence the supramolecular structure of the complexes (Jovanovich and Añón 1999).

Dimethyl sulfoxide (DMSO), a solvent associated with negative environmental issues, is

commonly used to solubilize the starch and ligand together which are mixed under carefully

controlled conditions to induce amylose complex formation (Gelders et al 2006). The use of

DMSO presents additional problems during complex formation as DMSO is also capable of

forming a complex with amylose and, when used as a solvent, the high concentration of DMSO

allows it to compete with other ligands for occupancy within the helix (Raphaelides and Karkalas


85

1988). Amylose complexes can be prepared under low shear conditions by predissolution of the

starch granules in cold or hot alkali solutions for up to 24 hr before use followed by extended

times at high temperatures to induce complex formation followed by adjustment of the pH to

induce precipitation of the complex (Kawada and Marchessault 2004, Karkalas et al 1995).

Lesmes and coworkers used continuous dual feed high pressure homogenization of

alkaline treated starch mixtures to prepare amylose lipid inclusion complexes (Lesmes et al

2008). Homogenization pressures upward of 25,000 psi were needed to produce the desired

complexes from alkaline solutions which were neutralized simultaneously using phosphoric acid.

Amylose-lipid complexes from cereal flours and corn starch have been produced by high

temperature single and twin screw extrusion processing (Bhatnagar and Hanna 1996, Colonna

and Mercier 1983, Strauss et al 1992, Hausmanns et al 2004). Extrusion processing is a

continuous process and is used extensively by the food industry. Amylose-lipid complexes can

be formed during the extrusion process when amylose and lipid are present. These studies

focused on amylose complex formation as a way to modify properties of the bulk extrudate. The

extent of complexation between the amylose and lipid within the extrudate has not been defined

clearly since separation and isolation of the amylose complexes from the bulk material is

difficult and has not been performed. More recently, biotechnology approaches have been

examined as a means to prepare amylose inclusion complexes using potato phosphorylase to

enzymatically construct an amylose helix around lipids (Putseys et al 2009, Gelders et al 2006,

Kaneko et al 2008). This approach can give monodisperse amylose complexes; however, a

glycogen primer must be synthesized prior to the reaction and extended reaction times are

needed to prepare small quantities of amylose complexes.

Many of the methods cited above for amylose inclusion complex production are

characterized by aspects which clearly preclude large scale production for high volume

applications. These limitations not only present challenges for the implementation of

commercial production, but in many cases it is difficult or impossible to produce sufficient

quantities of a given complex type for extensive experimental work, product development or

field testing. For these reasons, our research is aimed at characterizing amylose complexes

prepared with different ligands by excess steam jet cooking, optimizing the processing variables

and drying techniques and investigating specific applications for which large scale production of


86

amylose complexes would provide a commercially viable approach. Some of our initial studies

are described below.

Amylose-Sodium Palmitate Complexes

Aqueous dispersions of high amylose corn starch were steam jet cooked and blended with

aqueous solutions of sodium palmitate to form amylose inclusion complexes (Fanta et al 2010).

Rheological properties of the cooled dispersions were dependent upon starch concentration used

in the jet cooking process and varied from low viscosity liquids (at 3.75 and 5.00% solids) to

gels (at 6.64% solids). Despite these differences in properties, the amylose complexes became

dissolved as individual molecules, regardless of their initial concentration, when they were

diluted to about 0.2% solids, indicating the absence of permanent cross-links. Complete titration

of sodium palmitate in these complexes with 0.02 N HCl was observed at both room temperature

and 70°C (Figure 3), as opposed to uncomplexed sodium palmitate, which required heating to

70°C to achieve the water solubility required for complete titration. Titrations indicated that 12

to 15 % of sodium palmitate was converted into free palmitic acid during the preparative process,

probably due to slight acidity of the high amylose starch used. Viscosities of jet cooked starch-

sodium palmitate dispersions increased as titrations approached the end-point; and at about pH

3.6, about 90% of dispersed solid precipitated from the aqueous dispersion, due to conversion of

complexed sodium palmitate into insoluble palmitic acid (Figure 3). Addition of 0.5 M sodium

chloride solution also increased the viscosity of the jet cooked dispersion and 90% of the

dispersed solid precipitated from the dispersion when excess sodium chloride was added (Figure

3). Although freeze drying was used to isolate small quantities of amylose-sodium palmitate

complexes, spray drying also was used to isolate larger quantities of material. The spray dried

powder could be dispersed in water; properties of the resulting dispersion were similar to those

of a jet cooked dispersion that had never been dried.

Further investigation of the effects of pH, concentration and temperature on the

rheological characteristics of the complexes suggested that at high pH, electrostatic repulsion

kept the molecules in solution, but as pH was lowered and the sodium palmitate was converted to

palmitic acid, junction zones formed, leading to viscosity increase and gel formation (Byars et al

2012). Upon heating, the modulus values decreased rapidly at about 70°C, but recovered upon

cooling. In contrast, gels formed by the retrogradation of uncomplexed amylose-containing


87

starches were not thermally reversible. Complexes also can be made using normal cornstarch or

blends of normal and high amylose starch. As amylopectin content increases, rheological

properties are affected; amylopectin does not contribute to the gel network (Byars et al 2013).

The gelling properties of the amylose-sodium palmitate complexes suggest practical applications

as thickeners and dispersants for lipids in foods, lotions and water based lubricants, as well as

those described below.

Figure 3. Effect of titration with HCl (left) and NaCl (right) on the viscosity of dispersions of amylose-sodium palmitate complexes prepared by steam jet cooking. Silver Nanoparticles Prepared with Amylose-Sodium Palmitate Complexes

Starch stabilized silver nanoparticles (AgNP) were prepared from amylose-sodium

palmitate helical inclusion complexes by first converting sodium palmitate within the amylose

helix to silver palmitate by an ion exchange reaction with silver nitrate and then reducing the

complexed silver palmitate salt with NaBH4 (Fanta et al 2013). This process yielded stable

aqueous solutions that could be dried and dispersed in water for end use applications. Addition

of acid to reduce the pH of aqueous starch-AgNP solutions produced an increase in viscosity;

nearly quantitative precipitation of starch-AgNP was observed at low pH. Smaller AgNP (Figure

4) and higher conversions of silver nitrate to water-soluble starch-AgNP were obtained in this

process, as compared with a process carried out under similar conditions using a commercial

soluble starch as a stabilizer.


88

Figure 4. TEM images of silver nanoparticles prepared from amylose-sodium palmitate complexes (A) and soluble starch (B), showing substantial difference in size. Guar Gum Replacement for Hydromulch Application

Cellulosic materials combined with guar gum have been used as hydromulch products for

soil erosion control. Hydraulic fracturing by the oil industry has caused increased demand for

guar gum; substantial price increases led Vaughn and coworkers (2013) to test alternative

biobased adhesives, including amylose-sodium palmitate complexes, as guar gum replacements.

A test was devised to quantify resistance to simulated rainfall as a rainfastness index. Amylose-

sodium palmitate complexes made with high amylose cornstarch performed as well as guar gum,

while preparations made with normal and waxy cornstarch did not. Therefore, the surfactant

nature of the complex rather than starch itself conferred the necessary properties as a hydromulch

binder, since the straw fragments have hydrophobic surface characteristics. Using steam jet

cooking technology, a large quantity of complexes was readily prepared for field testing.

Cationic Amylose-Hexadecylamine Complexes

We prepared amylose inclusion complexes from jet cooked aqueous mixtures of high

amylose corn starch and 1-hexadecylamine (HDA), the amine analog of palmitic acid. Slow

cooling produced toroidal and disc shaped spherulites; whereas, aggregates of smaller spherulites


89

were obtained by rapid cooling in ice. The morphologies and 61V X-ray diffraction patterns of

these spherulites were similar to those of spherulites obtained previously with palmitic acid,

indicating that spherulite morphology is influenced largely by the hydrophobic structure of the

carbon chain of the complex forming ligand and to a lesser extent by the nature of the more polar

head group. Water soluble, cationic amylose inclusion complexes were prepared by adding an

aqueous solution of the HCl salt of HDA to a jet cooked dispersion of high amylose starch. The

cationic nature of these HDA·HCl complexes suggests possible applications as flocculating

agents for water purification and as retention aids in papermaking.

Comparison of Jet Cooking and Microwave Processing for Production of Spherulites

Helical inclusion complexes of amylose with fatty acids can form spherulites of various

morphological types. Researchers have described the spherulites obtained by cooling dispersions

of steam jet cooked corn starch either by itself or supplemented with various fatty acids. In light

of potential advantages of microwave processing, we investigated the use of a laboratory

microwave instrument as an alternative method for spherulite production (Felker et al 2013).

With native high amylose corn starch (HAS), spherulites were formed with morphology similar

to those observed previously by steam jet cooking. Adjustments to the reaction conditions such

as holding time at 140°C during initial heating and holding time at 100°C before slow cooling

led to a slight improvement in yield over jet cooking (Table 1).

Table 1. Formation of spherulites from native high amylose starch and palmitic acid using steam jet cooking and microwave processing.

Experiment # Method min 140°C hold min 100°C hold % yield/amylosea

1 jet cooker n/a n/a 82.9 (1.7)

2 microwave 10 0 58.1 (6.9)

3 microwave 10 60 85.3 (3.3)

4 microwave 0 60 88.7 (2.8) aYield of spherulites based on amylose content, mean (standard deviation) of three experiments.


90

Using solvent defatted HAS supplemented with straight chain fatty acids (C10:0 to

C22:0), microwave processing produced only small, disc shaped spherulites in a gel matrix.

However, when defatted HAS was supplemented with either capric or palmitic acid and

processed by steam jet cooking, uniform dispersions of toroidal spherulites were obtained.

Although jet cooking is not required for spherulite formation when native HAS is used, defatted

HAS requires the high shear steam jet cooking method of heating for optimal spherulite growth.

Researchers and product developers could use the results of microwave experiments to refine jet

cooking methods for large scale spherulite production.

High Oil Composites Made with Amylose-Oleic Acid Complexes

The use of amylose-oleic complexes to form submicron spherulites enabled the formation

of much higher oil:starch ratios in starch-oil composites than could be obtained with starch by

itself. Aqueous mixtures of soybean oil and starch were jet cooked at oil:starch ratios ranging

from 0.5:1 to 4:1 to yield dispersions of micron sized oil droplets that were coated with a thin

layer of starch at the oil-water interface (Fanta et al 2009). The jet cooked dispersions were then

centrifuged at 2060 and 10,800 x g, the buoyant, high oil fractions that rose to the surface were

isolated and the size distributions of the oil droplets were determined. Experiments were carried

out with normal dent, waxy and high amylose cornstarches; oleic acid was added during jet

cooking to form helical inclusion complexes with amylose. With normal dent and waxy

cornstarches, nearly all of the oil was recovered in the buoyant layers; only small amounts of oil

were found in the aqueous mid layers and settled solids. Oil droplet diameters in the buoyant

layers obtained with normal dent and waxy cornstarch ranged from <5 to >50 µm. With high

amylose starch, most of the oil droplets were encapsulated within networks of submicron

spherulites that were formed from amylose-oleic acid inclusion complexes when the dispersions

were cooled (Figure 5). SEM images of the interfacial starch shells formed from waxy

cornstarch and normal dent cornstarch in the presence of oleic acid showed only minor

differences in morphology. X-ray diffraction showed the starch shells formed from dent

cornstarch in the presence of oleic acid were comprised largely of amylose-oleic acid complexes

in the 61V conformation. Depending on the composition and preparation method, a wide range

of stable, high oil materials from low viscosity liquids to smooth pastes can be formed and


91

applications for these materials includes spray lubricants, lotions and fat delivery in cake mixes

(Byars et al 2011).

CONCLUSIONS

The extensive scientific literature on amylose inclusion complexes reveals a vast array of

variations regarding the source of amylose, the diverse range of possible ligands and numerous

methods of forming and purifying amylose inclusion complexes. By characterizing complexes

prepared by steam jet cooking, we are enabling the development of new products that can be

made by simply combining appropriate ligands with thermomechanically processed starch. The

commercial viability of this approach will be enhanced by using relatively inexpensive

unmodified starch and biobased ligands as feedstocks. Steam jet cooking is a commercially

scalable method and both soluble and spherulite forms of complexes can be obtained in high

yield. Most importantly, complexes based on this technology are useful for clean label products

made with green manufacturing methods due to the absence of covalent modification of the

starch. We have begun to investigate the production factors, properties and performance of these

complexes for specific applications. As more information becomes available, it will be possible

for both manufacturers of starch based products and those who utilize modified starches and

nonbiobased materials for various purposes to adopt this approach for increased utilization of

biobased feedstocks.


92

Figure 5. Phase contrast (left) and SEM (right) images of high oil ratio composites prepared with high amylose starch and oleic acid. Larger droplets were seen near the top of the dispersions (top), while mostly smaller droplets were encapsulated in spherulite networks in the settled layer (bottom). LITERATURE CITED

Bhatnagar, S. and Hanna, M.A. 1996. Starch-stearic acid complex development within single

and twin screw extruders. J. Food Sci. 61:778-782.

Buléon, A., Véronèse, G. and Putaux, J.-L. 2007. Self-association and crystallization of

amylose. Aust. J. Chem. 60:706-718.

Byars, J.A. 2002. Effect of starch-lipid fat replacer on the rheology of soft-serve ice cream. J.

Food Sci. 67:2177-2182.

Byars, J.A. 2003. Jet cooking of waxy maize starch: solution rheology and molecular weight

degradation of amylopectin. Cereal Chem. 80:87-90.


93

Byars, J.A., Fanta, G.F. and Felker, F.C. 2009. Rheological properties of dispersions of

spherulites from jet-cooked high amylose corn starch and fatty acids. Cereal Chem.

86:76-81.

Byars, J.A., Fanta, G.F. and Felker, F.C. 2011. Rheological properties of starch-oil composites

with high oil-to-starch ratios. Cereal Chem. 88:260-263.

Byars, J.A., Fanta, G.F., Kenar, J.A. and Felker, F.C. 2012. Influence of pH and temperature on

the rheological properties of aqueous dispersions of starch-sodium palmitate complexes.

Carbohydr. Polym. 88:91-95.

Byars, J.A., Fanta, G.F. and Kenar, J.A. 2013. Effect of amylopectin on the rheological

properties of aqueous dispersions of starch-sodium palmitate complexes. Carbohydr.

Polym. 95:171-176.

Colonna, P. and Mercier, C. 1983. Macromolecular modifications of manioc starch components

by extrusion-cooking with and without lipids. Carbohydr. Polym. 3:87-108.

Compton, D.L., Kenar, J.A., Laszlo, J.A. and Felker, F.C. 2007. Starch-encapsulated, soy-

based, ultraviolet-absorbing composites with feruloylated monoacyl- and diacylglycerol

lipids. Ind. Crops Prod. 25:17-23.

Coppock, P.D. 1940. Manufacture of starch paste. U.S. Patent 2,202,573.

Cunningham, R.L., Gordon, S.H., Felker, F.C. and Eskins, K. 1997. Jet-cooked starch-oil

composite in polyurethane foams. J. Appl. Polym. Sci. 64:1355-1361.

Davies, T., Miller, D.C. and Procter, A.A. 1980. Inclusion complexes of free fatty acids with

amylose. Starch/Stärke 32:149-158.

Dintzis, F.R. and Fanta, G.F. 1996. Effects of jet-cooking conditions upon intrinsic viscosity

and flow properties of starches. J. Appl. Polym. Sci. 62:749-753.

Fanta, G.F. and Eskins, K. 1995. Stable starch-lipid compositions prepared by steam jet

cooking. Carbohydr. Polym. 28:171-175.

Fanta, G.F., Felker, F.C., Eskins, K. and Baker, F.L. 1999. Aqueous starch-oil dispersions

prepared by steam jet cooking. Starch films at the oil-water interface. Carbohydr.

Polym. 38:25-35.

Fanta, G.F., Felker, F.C., Shogren, R.L. and Knutson, C.A. 2001. Starch-paraffin wax

compositions prepared by steam jet cooking. Examination of starch adsorbed at the

paraffin-water interface. Carbohydr. Polym. 46:29-38.


94

Fanta, G.F., Felker, F.C. and Shogren, R.L. 2002. Formation of crystalline aggregates in

slowly-cooled starch solutions prepared by steam jet cooking. Carbohydr. Polym.

48:161-170.

Fanta, G.F., Felker, F.C., Shogren, R.L. and Salch, J.H. 2006. Effect of fatty acid structure on

the morphology of spherulites formed from jet cooked mixtures of fatty acids and

defatted cornstarch. Carbohydr. Polym. 66:60-70.

Fanta, G.F., Felker, F.C., Shogren, R.L. and Salch, J.H. 2008. Preparation of spherulites from

jet cooked mixtures of high amylose starch and fatty acids. Effect of preparative

conditions on spherulite morphology and yield. Carbohydr. Polym. 71:253-262.

Fanta, G.F., Felker, F.C., Byars, J.A., Kenar, J.A. and Shogren, R.L. 2009. Starch-soybean oil

composites with high oil:starch ratios prepared by steam jet cooking. Starch/Stärke

61:590-600.

Fanta, G.F., Kenar, J.A., Byars, J.A., Felker, F.C. and Shogren, R.L. 2010. Properties of

aqueous dispersions of amylose-sodium palmitate complexes prepared by steam jet

cooking. Carb. Polym. 81:645-651.

Fanta, G.F., Kenar, J.A., Felker, F.C. and Byars, J.A. 2013. Preparation of starch-stabilized

silver nanoparticles from amylose-sodium palmitate inclusion complexes. Carb. Polym.

92:260-268.

Felker, F.C., Kenar, J.A., Fanta, G.F. and Biswas, A. 2013. Comparison of microwave

processing and excess steam jet cooking for spherulite production from amylose-fatty

acid inclusion complexes. Starch/Stärke DOI 10.1002/star.201200218

Garzon, G.A., McKeith, F.K., Gooding, J.P., Felker, F.C., Palmquist, D.E. and Brewer, M.S.

2003a. Characteristics of low-fat beef patties formulated with carbohydrate-lipid

composites. J. Food Sci. 68:2050-2056.

Garzon. G.A., Gaines, C.S. and Palmquist, D.E. 2003b. Use of wheat flour-lipid and waxy

maize starch-lipid composites in wire-cut formula cookies. J. Food Sci. 68:654-659.

Gelders, G.G., Goesaert, H. and Delcour, J.A. 2006. Amylose-lipid complexes as controlled

lipid release agents during starch gelatinization and pasting. J. Agric. Food Chem.

54:1493-1499.

Hausmanns, S., Kiy, T., Fabritius, D. and Tomka, I. 2004. Molecular inclusion compounds.

U.S. Patent Application 2004/0048829 A1.


95

Heinemann, C., Escher, F. and Conde-Petit, B. 2003. Structural features of starch-lactone

inclusion complexes in aqueous potato starch dispersions: the role of amylose and

amylopectin. Carbohydr. Polym. 51:159-168.

Jane, J., Kasensuwan, T., Chen, J.F. and Juliano, B.O. 1996. Phosphorus in rice and other

starches. Cereal Food World 41:827-832.

Jovanovich, G. and Añón, M.C. 1999. Amylose-lipid complex dissociation. A study of the

kinetic parameters. Biopolymers 49:81-89.

Kaneko, Y., Saito, Y., Nakaya, A., Kadokawa, J.-I. and Tagaya, H. 2008. Preparation of

inclusion complexes composed of amylose and strongly hydrophobic polyesters in

parallel enzymatic polymerization system. Macromolecules 41:5665-5670.

Karkalas, J., Ma, S., Morrison, W. and Pethrick, R. A. 1995. Some factors determining

the thermal properties of amylose inclusion complexes with fatty acids. Carbohydr.

Res. 268:233-247.

Kasica, J.J. and Eden, J.L. 1992. Continuous coupled jet-cooking/spray drying process and

novel pregelatinized high amylose starches prepared thereby. U.S. Patent 5,131,953.

Kawada, J. and Marchessault, R.H. 2004. Solid state NMR and X-ray studies on amylose

complexes with small organic molecules. Starch/ Stärke 56:13-19.

Kenar, J.A., Felker, F.C., Biresaw, G. and Kurth, T.L. 2009. Properties of dry film

lubricants prepared by spray application of aqueous starch-oil composites. Ind. Crops

Prod. 29:45-52.

Klem, R.E. and Brogly, D.A. 1981. Methods for selecting the optimum starch binder

preparation system. Pulp and Paper 55:98-103.

Knutson, C.A., Eskins, K. and Fanta, G.F. 1996. Composition and oil-retaining capacity of jet-

cooked starch-oil composites. Cereal Chem. 73:185-188.

Lesmes, U., Barchechath, J. and Shimoni, E. 2008. Continuous dual feed homogenization for

the production of starch inclusion complexes for controlled release of nutrients. Innov.

Food Sci. Emerging Technol. 9:507-515.

Peterson, S.C., Fanta, G.F., Adlof, R.O. and Felker, F.C. 2005. Identification of complexed

native lipids in crystalline aggregates formed from jet cooked cornstarch. Carbohydr.

Polym. 61:162-167.


96

Putseys, J.A., Derde, L.J., Lamberts, L., Goesaert, H. and Delcour, J.A. 2009. Production of

tailor made short chain amylose-lipid complexes using varying reaction conditions.


Raphaelides, S. and Karkalas, J. 1988. Thermal dissociation of amylose-fatty acid complexes.

Carbohydr. Res. 172:65-82.

Shogren, R.L., Fanta, G.F. and Felker, F.C. 2006. X-ray diffraction study of crystal

transformations in spherulitic amylose/lipid complexes from jet-cooked starch.


Sifferman, T.R., Muijs, H.M., Fanta, G.F., Felker, F.C. and Erhan, S.M. 2003. Starch-lubricant

compositions for improved lubricity and fluid loss in water-based drilling muds. SPE

80213, SPE Symposium on Oilfield Chemistry, Society of Petroleum Engineers,

Richardson, TX. pp. 1-5.

Singh, M. and Byars, J.A. 2009. Starch-lipid composites in plain set yogurt. Int. J. Food Sci.

Technol. 44:106-110.

Strauss, G., Gibson, Z. and Adachi, J. 1992. Molecular restructuring and complexation during

extrusion of cornmeal. In: Food Extrusion Science and Technology, Kokini, J.L., Ho,

C.T. and Karwe, M.V. (Eds.), Marcel Dekker, New York. pp. 437-448.

Vaughn, S.F., Kenar, J.A., Felker, F.C., Berhow, M.A., Cermak, S.C., Evangelista, R.L., Fanta,

G.F., Behle, R.W. and Lee, E. 2013. Evaluation of alternatives to guar gum as tackifiers

for hydromulch and as clumping agents for biodegradable cat litter. Ind. Crops Prod.

43:798-801.

Winfrey, V.L. and Black, W.C. 1964. Method of treating starch with steam. U.S. Patent

3,133,836.

Ziegler, G.R., Creek, J.A. and Runt, J. 2005. Spherulitic crystallization in starch as a model for

starch granule initiation. Biomacromolecules 6:1547-1554.

Zobel, H.F. 1988. Starch crystal transformations and their industrial importance.

Starch/Stärke 40:1-7.


97

EFFLUENT WATER FOR ETHANOL PRODUCTION

Kishore Rajagopalan*

Illinois Sustainable Technology Center, Prairie Research Institute, University of Illinois at Urbana-Champaign

(217) 244-8905, [email protected] INTRODUCTION

Energy independence and enhanced national security are tied inextricably to the

production of transportation fuels from biomass. This has encouraged enormous amounts of

private and public investment in biofuels. It also has resulted in an energy policy (EISA 2007)

that mandates the production of 36 billion gallons per year (BGY) of biofuels by 2022: 15

(BGY) from corn by 2015 and an additional 21 BGY from noncorn sources. Ethanol is by far

the largest biofuel on the market. It will continue to play an important role for many decades to

come in the nation’s fuel portfolio. While corn is the primary feedstock for ethanol production at

the present time, cellulosic sources are expected to play a larger role within the next decade.

Ethanol production under the current state of art requires the use of copious amounts of water.

Currently, dry grind ethanol plants use 3 to 4 gallons H2O/gal EtOH and lignocellulosic plants

may use 6 to 10 gallons H2O/gal EtOH (Wu et al 2009). These represent a concentrated use

point that can place an undue burden on local water supplies, especially in areas that may have

marginal water resources. In other areas, the use of water for biofuel production may compete

with alternative uses forcing exclusionary development pathways, locking in opportunity costs

and sparking debate on the merits of biofuels production. It is therefore necessary to ensure that

water does not become such a bottleneck through reducing its utilization in ethanol production.

Nontraditional sources of water such as agricultural runoff, mine water (Veil et al 2003),

produced water (Defilippo 1981) and treated municipal effluent can be used for industrial

purposes. The use of treated municipal effluent for ethanol production, in particular, is of

interest due to its widespread occurrence, reliability as a source and lower salinity relative to

agricultural runoff.

We will present results of a year long study of effluent quality at a municipal effluent

plant located in the vicinity of an ethanol plant to provide a perspective on the variability in


98

water quality. Also we will present an estimate of costs associated with upgrading and

transmission.

METHODS

Samples were collected at the outfall of the Rochelle WWTP (RWWTP) plant in Illinois. The

effluent treatment plant primarily treated 3 million gallons per day (mgd) of domestic sewage.

Operations carried out include equalization, solids removal, aeration, biological treatment and

clarification. Sludge was dewatered with polymer addition. Supernatant from the dewatering

operation was discharged with the effluent. Treated waste water was disinfected using chlorine

followed by dechlorination prior to discharge to the Kyte River.

Samples were collected at the location shown in Figure 1. Effluent (150 ml) was

collected every 15 min during a 24 hr period in a 5 gal plastic jug by RWWTP personnel to

constitute a composite sample. A prepurge prior to sampling and a postpurge after sampling was

built into the sampling protocol to minimize sample carryover. The sampler was calibrated

monthly. Collected samples were shipped by UPS next day service in coolers to the Illinois

Sustainable Technology Center, Champaign, IL and PDC Laboratories, Peoria, IL for analyses.

Treated waste water from RWTTP was sampled over a period of 12mo to capture seasonal

variations in water quality. Samples were obtained twice monthly. Sampling twice a month has

been reported to reduce serial correlation in data (Nelson and Ward 1981).

Sampling was carried out around the first and third week of the month. While a fixed

period sampling strategy was the goal, allowances were made to accommodate the work

schedules of the RWWTP personnel. A fixed period sampling shows least bias in estimating

mean concentrations (±20-30%) (Robertson 2003). However, precipitation events may introduce

a negative bias for maximum analyte concentrations. During this sampling round, 5 data points

out of 24 were preceded by rainfall events with just one event being greater than 1 inch. Hence,

the data should not be influenced by precipitation caused dilution bias. Effluent was

characterized as listed in Table 1.


99

RESULTS

The average ionic composition of treated waste water based on sampling over a 12 mo

period compared it to city water quality depicted in Table 2. The total dissolved solids (TDS)

level of the treated waste water was approximately double that of city water. Levels of sodium

and chloride ions in treated waste water are also much higher in comparison. Chemical oxygen

demand (COD) of treated waste water ranged 6 to 27 mg/L with a mean of 17.83 mg/L.

Biological oxygen demand (BOD) was less than 4 mg/L for all samples. Oil and grease was less

than 2 mg/L with a couple of outliers at levels of approximately 100 mg/L. Total suspended

solids was low, ranging from 0.6 to 2.8 mg/L with a mean of 1.7 mg/L. Microbial load in the

treated waste water was variable with occasionally high loads. Heterotrophic plate count varied

widely with a minimum of 47 cfu/mL to 496,000 cfu/mL. Fecal coliforms were normally less

than 100 cfu/mL with one sample reporting 400 cfu/mL. Information on the fluctuations in

water quality over the period of one year is provided in Figure 2.

Figure 1. Sampling location (see arrow).


101

Table 1. List of effluent parameters analyzed and methods employed Analysis Method Preservation Max. Holding

Period pH STM 4500 None In situ

Conductivity STM 2510 None In situ Total Dissolved Solids STM 2540B None 14 days Total suspended Solids STM 2540D None 14 days

TOC STM 5310B Acidify to pH 2, 4°C 28 days Oil and Grease EPA 1664 Acidify to pH 2, 4°C 28 days

COD STM 5220D Acidify to pH 2, 4°C 28 days BOD STM 5210 4°C 1 day max

Bacteria , Heterotrophs 4°C Fecal Coliforms 4°C Total Phosphate STM 4500, digestion followed

by IC or ICP/MS Acidify to pH 2, 4°C 2 days

Nitrogen, Ammonia STM 4500-NH3 D Acidify to pH 2, 4°C 28 days Total Alkalinity STM 2320B 4°C 7 days

Metals Aluminum ICP/MS Acidify to pH 2, 4°C 6 months

Arsenic ICP/MS Acidify to pH 2, 4°C 6 months Barium ICP/MS Acidify to pH 2, 4°C 6 months

Beryllium ICP/MS Acidify to pH 2, 4°C 6 months Boron ICP/MS Acidify to pH 2, 4°C 6 months

Cadmium ICP/MS Acidify to pH 2, 4°C 6 months Calcium ICP/MS Acidify to pH 2, 4°C 6 months

Chromium ICP/MS Acidify to pH 2, 4°C 6 months Cobalt ICP/MS Acidify to pH 2, 4°C 6 months Copper ICP/MS Acidify to pH 2, 4°C 6 months

Iron ICP/MS Acidify to pH 2, 4°C 6 months Lead ADD

ICP/MS Acidify to pH 2, 4°C 6 months

Magnesium ICP/MS Acidify to pH 2, 4°C 6 months Manganese ICP/MS Acidify to pH 2, 4°C 6 months

Molybdenum ICP/MS Acidify to pH 2, 4°C 6 months Nickel ICP/MS Acidify to pH 2, 4°C 6 months

Potassium ICP/MS Acidify to pH 2, 4°C 6 months Selenium ICP/MS Acidify to pH 2, 4°C 6 months

Silica ICP/MS Acidify to pH 2, 4°C 6 months Sodium ICP/MS Acidify to pH 2, 4°C 6 months

Strontium ICP/MS Acidify to pH 2, 4°C 6 months Thallium ICP/MS Acidify to pH 2, 4°C 6 months

Tin ICP/MS Acidify to pH 2, 4°C 6 months Titanium ICP/MS Acidify to pH 2, 4°C 6 months Vanadium ICP/MS Acidify to pH 2, 4°C 6 months

Zinc ICP/MS Acidify to pH 2, 4°C 6 months Anions

Chloride EPA 300 4°C 28 days Bromide EPA 300 4°C 28 days Fluoride EPA 300 4°C 28 days Nitrate EPA 300 4°C 2 days Nitrite EPA 300 4°C 2 days Sulfate EPA 300 4°C 28 days


102

Table 2. Average ionic composition of treated waste water and city water

Water Quality Parameter

Units TreatedWaste Water

City Water

Total Dissolved Solids mg/L 1111.3 514 Sodium (Na) mg/L 245.7 22.75 Potassium (K) mg/L 12.4 2.03 Calcium (Ca) mg/L 85.0 60.12 Magnesium (Mg) mg/L 41.5 30.63 Strontium (Sr) mg/L 0.27 0.39 Barium (Ba) mg/L 0.13 0.12 Chloride (Cl-) mg/L 392.9 5.5 Bicarbonate (HCO3

-) mg/L 412.1 364 Sulfate (S04

2-) mg/L 36.5 12.48 Nitrate (NO3

-) mg/L 20.4 2.23 Fluoride (F-) mg/L 1.5 1.06 Bromide (Br-) mg/L 0.08 Silicon mg/L 11.3 9.45


103

Figure 7a. Seasonal variations in select analytical parameters of RMU effluent.

6.006.206.406.606.807.007.207.407.607.808.00

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

pH (mg/L)

Sampling Date

pH of RMU Effluent

pH0

200

400

600

800

1000

1200

1400

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

TDS (mg/L)

Sampling Date

TDS of RMU Effluent

TDS (mg/L)

5.6005.8006.0006.2006.4006.6006.8007.0007.2007.4007.600

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

Alkalinity (meq/L)

Sampling Date

Alkalinity in RMU Effluent

Alkalinity

0

50

100

150

200

250

300

350

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

Sodium (mg/L)

Sampling Date

Sodium in RMU Effluent

Sodium340.00

360.00

380.00

400.00

420.00

440.00

460.00

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

Bicarbonate (mg/L)

Sampling Date

Bicarbonate in RMU Effluent

Bicarbonate

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

TSS (mg/L)

Sampling Date

TSS in RMU Effluent

TSS


104

Figure 2b. Seasonal variations in select analytical parameters of RMU effluent.

050100150200250300350400450500

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

Chloride (mg/L)

Sampling Date

Chloride in RMU Effluent

Chloride

0

2

4

68

10

1214

16

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

Silica (mg/L)

Sampling Date

Silica in RMU Effluent

Silica0.00

0.05

0.10

0.15

0.20

0.25

0.30

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

Barium (mg/L)

Sampling Date

Barium in RMU Effluent

Barium

0.00

0.05

0.100.15

0.20

0.25

0.300.35

0.40

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

Strontium (mg/L)

Sampling Date

Strontium in RMU Effluent

Strontium0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

Fluoride (mg/L)

Sampling Date

Fluoride in RMU Effluent

Fluoride

0102030405060708090100

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

Calcium (mg/L)

Sampling Date

Calcium in RMU Effluent

Calcium


105

Figure 2c. Seasonal variations in select analytical parameters of RMU effluent.

Upgrading of effluent water

The treated waste water needs to be upgraded to allow it to be used in lieu of city water.

It is assumed the upgrading would take place at the waste water treatment plant. Micro- and

ultrafiltration, followed by reverse osmosis would be the preferred option as bacterial removal

and dissolved solids reduction would be required (Figure 3). About 60% of microfiltered water

needs to be further processed by reverse osmosis prior to blending to obtain a TDS roughly

similar to current city water supply (Table 3).

0102030405060708090100

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

O& G (mg/L)

Sampling Date

Oil & Grease in RMU Effluent

Oil & Grease0

5

10

15

20

25

30

3/15/09

4/15/09

5/15/09

6/15/09

7/15/09

8/15/09

9/15/09

10/15/09

11/15/09

12/15/09

1/15/10

2/15/10

COD (mg/L)

Sampling Date

COD in RMU Effluent

COD

0.00

5.00

10.00

15.00

20.00

25.00

Jan

Feb

March

April

May

June

July

Aug

Sep

Oct

Nov

Dec

Temperature (C)

Sampling_Date

Temperature of RMU Effluent

Temperature0

100000

200000

300000

400000

500000

600000

HPC (cfu/mL)

Sampling Date

Heterotrophic Plate Count in RMU Effluent

HPC (cfu/mL)


106

Figure 8. Process scheme to upgrade treated municipal wastewater Table 3. Composition of upgraded effluent relative to City water Water Quality Parameter

Units TreatedWaste Water

City Water

Total Dissolved Solids mg/L 555 514 Sodium (Na) mg/L 123 22.75 Potassium (K) mg/L 6 2.03 Calcium (Ca) mg/L 43 60.12 Magnesium (Mg) mg/L 22 30.63 Strontium (Sr) mg/L 0.14 0.39 Barium (Ba) mg/L 0.06 0.12 Chloride (Cl-) mg/L 197 5.5 Bicarbonate (HCO3-) mg/L 206 364 Sulfate (SO4

2-) mg/L 19 12.48 Nitrate (NO3

-) mg/L 10 2.23 Fluoride (F-) mg/L 0.8 1.06 Bromide (Br-) mg/L 0.04 Silicon mg/L 5 9.45


107

The process will also produce an effluent stream equivalent to116 gpm. This amount

reflects the waste produced in the RO process. The concentrate generated from the RO process

can be mixed with the rest of the effluent plant discharge of roughly 1.5 mgd. This will raise the

TDS of the discharge to approximately 1400 mg/L.

Table 4 estimates the total costs associated with treatment, transmission and disinfection.

The construction costs associated with conveying water from RMU to the ethanol plant is

estimated for an 8 inch PVC line, C-900 pipeline over a distance of 19,400 ft. The unit costs

include pipeline, trenching, excavation, backfill with 4 feet cover and valves. Costs include 870

feet of horizontal drilling. The total costs represent an increase of 48 to 84% in costs of water

compared to the baseline. However, the impact on ethanol production costs should be barely

noticeable.

Table 4. Estimated costs of treating and transporting treated municipal effluent to ethanol facility

Item Unit Cost $ Treatment on-site $/1000 gallons 0.75 to 1.09 Transmission and piping $/1000 gallons 0.59 Disinfection $/1000 gallons 0.07

Estimated Total Cost $/1000 gallons $1.41 to $1.75 Environmental implications of water withdrawal

The discharge of the municipal treatment plant is currently to the Kyte River. It is

classified as a General Use water with a Q7,10 of 0.59 cfs (265 gpm) just upstream of the effluent

plant. The Kyte River is a tributary of the Rock River. It has a drainage area of 116 square

miles. It is rated as a B stream under the Biological Stream Characterization system. Data

compiled by the Illinois State Water Survey on Q7,10 flow in the Kyte River (as of 2002) is

presented in Figure 4. The 7 day, 10 year low flow (Q7,10) is a statistical estimate of the lowest

average flow that would be experienced during a consecutive 7 day period with an average

recurrence interval of ten years. Because it is estimated to recur on average only once in 10

years it is usually an indicator of low flow conditions during drought. In particular, these flows

are used for defining permit limits for effluent standards and mixing zones. The Q7,10 is used as a

reference flow for several drought water resource management issues.


108

The wastewater plant at Rochelle contributes roughly 1/3 of the Q7,10 flow of the Kyte

River as it empties into the Rock River but more than 4/5 at locations slightly south of Rochelle.

The wastewater flow of 3.2 cfs (1435 gpm) (data from 2002 underestimates current flow

condition of 2020 gpm) is the main flow to the Kyte at this point. Abstracting about 900 gpm

will reduce flow just south of Rochelle by 44%. The effect of these withdrawals on the stream

ecology will have to be examined to ensure no unintended consequences ensue.


109

Figure 9. Q7,10 flows in the Kyte River.


110

CONCLUSIONS

The use of treated municipal water is feasible where the effluent is readily available and

within a short distance. No major challenges are expected from a technical perspective in

upgrading the water in this particular case. The costs of treatment and transmission are not

particularly expensive in this scenario as well.

The ecological impacts of withdrawal require further analysis. In particular, the

withdrawal of a significant portion of the discharge to the river and the increase in TDS of the

plant discharge due to generation of RO concentrate will need closer examination from both an

ecological and NPDES permit modification perspective.

LITERATURE CITED

Energy Independence and Security Act of 2007: Summary of provisions. Available at:

http://www.eia.doe.gov/oiaf/aeo/otheranalysis/aeo_2008analysispapers/eisa.html.

Accessed July 11, 2009.

Wu M, Mintz M, Wang M, Arora S. Consumptive water use in the production of ethanol and

petroleum gasoline. ANL/ESD/09-1, Argonne National Laboratory (ANL); 2009.

Veil, J.A.; Kupar, J.M.; Puder, M.G. 2003. Use of Mine Pool Water for Power Plant Cooling.

W-31-109-Eng-38. U.S. Department of Energy, National Energy Technology

Laboratory, Pittsburgh, PA.

Defilippo MN. Use of produced water in recirculating cooling systems at power generating

facilities. Palo Alto, CA: EPRI; 2005.

Nelson JD, Ward RC. Statistical considerations and sampling techniques for ground-water

quality monitoring. Ground Water 1981;19 (6):617-26.

Robertson DM. Influence of different temporal sampling strategies on estimating total

phosphorus and suspended sediment concentration and transport in small streams. Journal

of the American Water Resources Association 2003;39 (5):1281-308.


111

CORN COPRODUCTS IN COMPANION ANIMAL NUTRITION

Maria R. C. de Godoy* and George C. Fahey, Jr.

Animal Sciences, University of Illinois at Urbana-Champaign 1207 W. Gregory Dr., Urbana, IL 61801 (217) 333-7348, [email protected]

INTRODUCTION

The ethanol industry is the fastest growing renewable energy industry in the world

(Tolman and Tumbleson, 2006). Proportionally, with the increase in ethanol, higher amounts of

coproducts have been produced, which has raised the interest in expanding the utilization of

these coproducts in animal nutrition. In the U.S., corn is the main raw material used in ethanol

production. Ethanol is produced mainly by the dry grind process, which generates distillers dried

grains with solubles (DDGS) as a coproduct and the wet milling process. The latter produces

corn gluten meal (CGM), corn germ meal (CGeM), corn gluten feed (CGF) and corn fiber (CF)

as coproducts. Most corn coproducts from both processes have been utilized in ruminant diets

because of their higher concentration of structural carbohydrates, poor amino acid profile and

high variability.

New technology utilized by the ethanol industry, however, may result in new

opportunities for the utilization of corn coproducts in animal nutrition. Improvements in protein

quality and lower phosphorus content can make these coproducts appropriate for swine, poultry

and companion animals. More consistent quality will motivate companies to use these

coproducts in their food formulations. The ethanol industry can benefit from this scenario

because its revenue can be increased. Moreover, these coproducts can be of use in the animal

nutrition field once they have higher (or at least equivalent) nutritional value as most foodstuffs

currently used in formulations.

The pet food industry is constantly expanding and searching for new ingredients to be

added to its broad product repertoire. Pet owners demand high quality products for their

companions; they also expect the food to promote health throughout the animal’s life.

Furthermore, reflective of today’s lifestyle, most companion animals are indoor animals and

owners expect stools that are small, well shaped and mild in odor. Little research has been done


112

evaluating the efficacy of corn coproducts from the ethanol industry in nonruminant species.

Scarcity of such research is pronounced especially in the case of companion animals. The lack

of data on these coproducts prevents their maximal utilization in companion animal foods.

Therefore, expansion of the database on chemical composition, nutrient digestibility and possible

benefits on health of dogs and cats would promote utilization of these ingredients in the

companion animal food industry. The objective of this review is to present current literature

available on utilization of corn coproducts from the wet milling process in companion animal

nutrition.

Use of corn coproducts in companion animal nutrition

Dietary protein sources are important to provide essential amino acids to the body and to

sustain physiological functions (eg, enzymatic synthesis, protein synthesis). Animals have

dietary amino acid requirement that need to be met to avoid deficiency and to maintain optimal

health. Therefore, high quality and digestible protein sources are desirable in diets of dogs and

cats. CGM is a coproduct from the wet milling process, characterized by its low crude fiber

(2.4%) and high protein (67%) content. The high protein concentration and the amino acid

profile make CGM a valuable protein source for poultry, swine, fish and companion animals

(Rausch and Belyea 2006). High phosphorus and sulfur concentrations, 0.54 and 0.70%,

respectively, can be a concern when CGM is fed to animals due to waste disposal difficulties and

palatability issues (Rausch and Belyea 2006).

A comparison of the nutritional value of CGM and meat meal as dietary sources of

protein in dry food for adult cats showed that cats fed the meat meal diet had higher nitrogen

intake, dry matter digestibility and mineral utilization. Lower utilization of absorbed nitrogen by

cats on the CGM diet indicates lower biological value of CGM protein compared to the

biological value of meat meal (Funaba et al 2002). Nonetheless, CGM has an unusual feature

among other cereal grain products; it is high in sulfur containing amino acids, which mimics the

amino acid profile of animal proteins, usually rich in methionine and cysteine, which are

metabolized to sulfate and excreted as acidic metabolites (Skoch et al 1991). Thus, CGM has a

strong acidifying effect on the urine of cats (Case et al 2000). Acidification of urine pH is

critical in cats to prevent struvite crystal formation. Complete solubilization of struvite crystals

occurs at a pH below 6.7; both CGM and meat meal diets resulted in this pH (Funaba et al 2002).


113

Nutritional effects of fish meal and CGM were investigated in adult cats. Nitrogen

balance, urinary pH, dry matter digestibility, food intake, water intake and urine volume were not

different between the two protein sources. Fecal weight and fecal moisture content were lower

for CGM (Funaba et al 2001). Thus, CGM and fish meal were of comparable nutritional value

and had similar urine acidifying properties (Funaba et al 2001).

When meat meal, poultry meal and CGM were evaluated as protein sources in adult cat

diets, dry matter digestibility was higher for meat meal, followed by poultry meal and CGM.

Nitrogen utilization did not differ between poultry meal and CGM. The number of struvite

crystals in urine were lower in cats fed the CGM diet (Funaba et al 2005). In a similar study,

CGM also had the most potent prophylactic effect on feline urological syndrome when compared

to poultry meal and meat meal. Additionally, acidification of urine was dependent on the

concentration of test ingredient used and on the feeding management (ad libitum or meal).

Higher concentrations of CGM (32.6%) and poultry meal (37.2%) were more effective than

lower concentrations, while ad libitum feeding was more effective than meal feeding (Skoch et al

1991).

Increasing dietary concentrations of CGM (8, 16, 24 and 32%) in canine diets did not

affect the amino acid profile of the diets. Coefficients for apparent dry matter and crude protein

ileal digestibilities ranged from 83 to 89% and 73 to 83%, respectively (Yamka et al 2004),

which were higher than values obtained by Zuo et al (1996) using soybean meal as a protein

source. Puppies (8 weeks old) fed diets with CGM and meat and bone meal as the main protein

sources had a lower protein requirement (25.2%) when compared to puppies fed a poor quality

poultry byproduct meal (27.5%; Case and Czarmecki-Maulden 1990). de Godoy et al (2009)

determined the chemical composition and protein quality of CGM and two novel corn protein

concentrates produced without the use of SO2 during the wet milling process. Crude protein

concentration varied from 74% to 50% for these ingredients. Total amino acid (AA), essential

and nonessential AA concentrations followed a similar pattern. In vitro crude protein

disappearance was greater for CGM (94%) when compared with the two novel corn protein

concentrates (average 76%). In this study, protein quality of corn protein ingredients was

assessed by protein efficiency ratio (PER) and cecectomized rooster assays. The PER assay

indicated that CGM and the two novel corn protein concentrates had poor protein quality as the

PER value was lower than 2.0. This outcome probably was due to lower lysine concentrations in


114

these ingredients in relation to the total AA, profile and the lower food intake of diets containing

these ingredients. In contrast, a good amino acid digestibility was observed for these ingredients

using the cecectomized rooster assay. Total AA digestibility was greatest for CGM and one of

the corn protein concentrates (95 and 90%, respectively) in contrast to the other corn protein

concentrate that had an AA digestibility of 82%. CGM and novel corn protein concentrates are

adequate protein sources in pet food; however, dietary lysine supplementation may be needed.

In addition, utilization of CGM may help to ameliorate or prevent struvite crystal occurrence in

cats.

In contrast to protein (amino acids), dietary fiber is not required by dogs and cats. However,

increasing attention has been given to this nutrient as several health attributes have been linked

to its consumption. Limited information is available on the use of corn fiber as an ingredient in

companion animal diets. However, because of its low cost, relative high abundance (with

increased ethanol production) and nutritional characteristics, it is important to investigate

whether corn fiber can be used successfully in companion animal diets and whether its quality is

comparable to standard fiber sources used by this industry. Guevara et al (2008) examined

chemical composition, in vitro fermentation characteristics and in vivo nutrient digestibility of

fiber rich corn coproducts: native corn fiber (wet milled corn pericarp), native corn fiber with

fines (90% wet milled corn pericarp and 10% fine corn fiber particles), hydrolyzed corn fiber

(native corn fiber subjected to steam injection followed by removal of solubilized hydrolyzate)

and hydrolyzed extracted corn fiber (hydrolyzed corn fiber extracted with ethanol) in adult dogs.

On a DM basis, crude protein (CP) ranged from 10.8 to 14.1%, total dietary fiber (TDF) varied

from 63.0 to 88.2% and acid hydrolyzed fiber (AHF) from 2.4 to 6.8%. The native corn fiber

with fines had the lowest TDF and highest CP concentrations. In vitro organic matter

disappearance (OMD) during the hydrolytic-enzymatic digestion ranged from 7.2 to 31.1%,

being greatest for native corn fiber with fines and smallest for hydrolyzed extract corn fiber.

After 16 hr of in vitro fermentation, native corn fibers showed intermediate fermentation (mean

9.6%), while fermentation of the hydrolyzable corn fibers was negligible in contrast to beet pulp

(17.7%). When 7% of corn fiber sources were added to dog foods to replace beet pulp, no

negative effects on food intake, nutrient digestibility, or fecal quality were observed. Corn fiber

is an adequate fiber source for companion animal food, resulting in no detrimental effects on

palatability and being well tolerated by adult dogs at the 7% inclusion level (Guevara et al 2008).


115

de Godoy et al (2009) determined chemical compositions and in vitro fermentation

characteristics of three corn fibers (two commercially available corn fiber products and a novel

corn fiber produced without the use of SO2 during the wet milling process). In general, similar

chemical composition to the corn fibers of the aforementioned study was observed herein. On a

DM basis, corn fibers contained 71.4 to 82.2% TDF, 5.0 to 6.0% AHF, 7.5 to 11.0% CP and 0.8

to 0.9% ash. In contrast, beet pulp had a higher ash concentration (6.8%) and lower TDF

(68.8%) and CP (6.3%) concentrations, whereas cellulose was comprised entirely of TDF

(100%). The low ash content of corn fibers and the high concentration of TDF favor their

utilization in companion animal food matrices, resulting in little interference with other nutrient

categories, especially ash, where a maximum content needs to be guaranteed on the food label.

OMD after in vitro hydrolytic digestion of corn fibers varied from 6.5 to 22.0%. Beet pulp, used

as a positive control, had an OMD of 20.5%, whereas OMD for cellulose and peanut hulls

(negative controls) were 0.0 and 3.3%, respectively. After 16 hr of in vitro fermentation using

canine fecal inoculum, corn fibers were poorly fermented, with OMD ranging from 3.0 to 5.7%,

in contrast to 17.7% for beet pulp and 0.0% for cellulose. The chemical composition and in vitro

fermentation data were suggestive that corn fibers can be used in companion animal foods; they

behave mostly as insoluble and nonfermentable fibers (de Godoy et al 2009).

Because of the increased incidence in companion animal obesity, use of dietary fiber has

been studied as a means to dilute caloric density and to ameliorate postprandial glycemic and

insulinemic responses, often negatively impacted by body weight gain. A study using different

sources of soluble corn fiber investigated their effect on in vitro hydrolytic digestion, glycemic

and insulinemic responses and true metabolizable energy using canine and avian models (de

Godoy et al 2013a). A series of soluble corn fibers originated from different processing

methods: hydrochloric acid and (or) phosphoric acid catalyzation, hydrogenation and spray

drying were tested. Processing method had a major impact on the in vitro hydrolytic digestion of

these substrates. In general, spray dried, hydrogenated and phosphoric acid treated soluble corn

fibers were more digestible (~47%) than fibers produced by hydrochloric acid or the

combination of phosphoric and hydrochloric acids (29%). Soluble corn fibers when orally dosed

to adult dogs resulted in lower glycemic and insulinemic responses when compared with

maltodextrin, a highly digestible and rapidly absorbable carbohydrate used as a positive control.

In agreement with glycemic response data, all soluble corn fibers had lower (1.3 to 3.0 kcal/g)


116

true metabolizable energy in contrast to maltodextrin (4.1 kcal/g; de Godoy et al 2013a). de

Godoy et al (2013b) examined the effects of blends of soluble corn fibers with pullulan, sorbitol

(slowly digestible carbohydrate sources) and fructose, a noninsulinemic sugar. Soluble corn

fiber had an in vitro hydrolytic digestion of 50%. Blending soluble corn fiber with low

concentrations fructose (5 or 15%) resulted in similar monosaccharide digestibility values.

However, blending soluble corn fiber with 30 or 50% of fructose, sorbitol, or pullulan led to

greater digestibility, up to 91%. Soluble corn fiber and its blends had lower glycemic and

insulinemic responses than maltodextrin. The lowest glycemic response was observed for blends

containing 30 to 50% fructose or sorbitol, resulting in an average relative glycemic response of

4.8% in contrast to maltodextrin (100%; de Godoy et al 2013b). Similarly to soluble corn fiber,

corn based soluble fiber dextrin (produced by subjecting corn starch to a thermal, chemical and

enzymatic treatment) has been shown to lower glycemic and insulinemic responses by as much

as 27 and 20%, respectively, in adult dogs and to have a lower true metabolizable energy (37%)

using the cecectomized rooster model when compared to maltodextrin (Knapp et al 2010).

Overall, corn fiber sources are good candidate ingredients that may be utilized in companion

animal diets. In addition, corn fibers seem to be effective in reducing the glycemic response and

caloric density of companion animal foods.

CONCLUSIONS

Corn coproducts from the wet milling process can provide economical and high quality

ingredients for companion animal diets. In vitro and in vivo studies have shown that wet milling

coproducts can be used as protein or fiber sources and are well tolerated by dogs and cats. Corn

gluten meal and corn protein concentrates are highly digestible protein sources; however, lysine

supplementation may be needed to improve the protein quality of these ingredients in companion

animal foods. In addition, utilization of CGM in feline diets is an effective way to maintain

urine acidic pH and it may aid in the prevention and management of struvite crystal formation.

Corn fiber is well tolerated by dogs at concentrations up to 7%, showing no negative effects on

nutrient digestibility or fecal quality. Corn fiber is comprised of mostly insoluble fiber and

shows little fermentation, which makes it a good ingredient to be added in companion animal

diets to decrease caloric density and to maintain normal gastrointestinal function.


117

LITERATURE CITED

Case, L. P. and Czarnecki-Maulden, G. L. 1990. Protein requirements of growing pups fed

practical dry-type diets containing mixed-protein sources. Amer. J. Vet. Res. 51: 808-812.

Case, L. P., Carey, D. P., Hirakawa, D. A. and Daristotle, L. 2000. Feline lower urinary tract

disease. In: Canine and Feline Nutrition. St. Louis: Mosby Year Book Inc., pp. 409-428.

de Godoy, M. R. C., Bauer, L. L., Parsons, C. M. and Fahey, G. C., Jr. 2009. Select corn

coproducts from the ethanol industry and their potential as ingredients in pet foods. J.

Anim. Sci. 87:189-199.

de Godoy, M. R. C., Bauer, L. L., Parsons, C. M., Swanson, K. S. and Fahey, G. C., Jr. 2013a.

In vitro hydrolytic digestion, glycemic response in dogs and true metabolizable energy

content of soluble corn fibers. J. Anim. Sci. (submitted)

de Godoy, M. R. C., Bauer, L. L., Parsons, C. M., Swanson, K. S. and Fahey, G. C., Jr. 2013b.

Blending of soluble corn fiber with pullulan, sorbitol, or fructose attenuates glycemic

and insulinemic responses in the dog and affects hydrolytic digestion in vitro. J. Anim.

Sci. (in press)

Funaba, M., Tanaka, T., Kaneko, M., Iriki, T., Hatano, Y. and Abe, M. 2001. Fish meal vs. corn

gluten meal as a protein source for dry cat food. J. Vet. Med. Sci. 63: 1355-1357.

Funaba, M., Matsumoto, C., Matsuki, K., Gotoh, K., Kaneko, M., Iriki, T., Hatano, Y. and Abe,

M. 2002. Comparison of corn gluten meal and meat meal as a protein source in dry foods

formulated for cats. Amer. J. Vet. Res. 63: 1247-1251.

Funaba, M., Oka, Y., Kobayashi, S., Kaneko, M., Yamamoto, H., Namikawa, K., Iriki, T.,

Hatano, Y. and Abe, M. 2005. Evaluation of meat meal, chicken meal, and corn gluten

meal as dietary sources of protein in dry cat food. Canadian J. Vet. Res. 69:299-304.

Guevara, M. A., Bauer, L. L., Abbas, C. A., Beery, K. E., Holzsgraefe, D. P., Cecava, M. J. and

Fahey, G. C., Jr. 2008. Chemical composition, in vitro fermentation characteristics, and in

vivo digestibility responses by dogs to select corn fibers. J. Agric. Food Chem.

56:1619-1626.

Knapp, B. K., Parsons, C. M., Bauer, L. L., Swanson, K. S. and Fahey, G. C., Jr. 2010. Soluble

fiber dextrins and pullulans vary in extent of hydrolytic digestion in vitro and in energy


118

value and attenuate glycemic and insulinemic responses in dogs. J. Agric. Food Chem.

58:1355-1363.

Rausch, K. D. and Belyea, R. L.. 2006. The future of coproducts from corn processing. Appl.

Biochem. Biotechnol. 128: 47-86.

Skoch, E. R., Chandler, E. A., Douglas, G. M. and, Richardson, D. P. 1991. Influence of diet on

urine pH and the feline urological syndrome. J. Small Anim. Pract. 32: 413-419.

Tolman, R. and Tumbleson, G. 2006. Raising American Standards–World of Corn. National

Corn Growers Association–NCGA.

Yamka, R. M., Kitts, S. E., True, A. D. and Harmon, D. L. 2004. Evaluation of maize gluten

meal as a protein source in canine foods. Anim. Feed Sci. Technol. 116: 239-248.

Zuo, Y., Fahey, G. C., Jr, Merchen, N. R. and Bajjalieh, N. L. 1996. Digestion responses to low

oligosaccharide soybean meal by ileally-cannulated dogs. J. Anim. Sci. 74: 2441-2449.


119

GLUCOSE DEMUDDING BY A DECANTER-MEMBRANE SYNERGY PROCESS: DEVELOPMENT UPDATE

Dell Hummel*1 and Frank Lipnizki2

1Alfa Laval Inc.

321 Foster Avenue - Wood Dale, IL 60191 (United States) Tel: +1 630 571 5107. Email: [email protected]

2Alfa Laval Copenhagen A/S, Denmark Maskinvej 5, 2860 Søborg (Denmark)

Rotary vacuum filters (RVFs) with diatomaceous earth (kieselguhr) coatings as filter aid

are the most established technology for the removal of the so called mud fraction after

liquefaction and saccharification in the production of starch based sweeteners. The RVFs open

up the process to the atmosphere and disposal of the filter aid is an increasing challenge. Based

on these environmental issues, there is a demand from the industry for alternative demudding

solutions.

Since about 2005, Alfa Laval has been working on development and introduction of a

new concept for demudding, a synergy process consisting of a decanter and a membrane unit.

The initial large scale pilot tests were carried out in 2008 focusing on low DE wheat based

sweeteners, DE45 and maltose. These tests proved that the basic principles of the concept were

working and were in line with previous experience on starch-based sweetener demudding using

decanters and membranes independently. The decanter before the ultrafiltration unit removed

over 95% of the mud fraction and the subsequent ultrafiltration unit polished the sweeteners to a

quality higher than achieved by existing RVFs with regard to turbidity and colour removal.

Hence, this concept was found to be not only suitable to replace the RVFs but also to have the

potential to lower downstream processing costs. Based on these tests and previous experience,

two full scale demudding systems were installed for corn based sweeteners in 2011. The first

system operates on low DE sweeteners, DE 40 to 45 and maltose; the second system works on a

higher DE sweetener level, DE 95. Both systems operate 24hr/7days per week. To achieve this,

the membrane systems are operating with sequential cleaning; one of the five loops of the


120

Figure 1. Five loop membrane unit with sequential cleaning for demudding of corn based sweetener. membrane plant is in cleaning/maintenance mode, while the other four loops are in production

mode. A layout drawing of one of the membrane units is shown in Figure 1.

The membranes installed in the plant are dedicated ultrafiltration membranes for

demudding with a high hydrophilicity. Compared to conventional membranes used for

demudding, this particular membrane has a relatively low molecular weight cut off which

provides a high removal of turbidity and colour without significant impact on the Brix in the

polished permeate stream compared to the original feed stream plus a resistance against

retrograded starch. Further, to increase plant capacity, the module design was optimized to the

requirements of the application. Most recently, Alfa Laval optimized performance of the

synergy process for DE 96 wheat based sweeteners at a large pilot scale.


121

Overall, Alfa Laval has developed over the years a comprehensive knowledge base

covering wheat and corn based sweeteners from low DEs (40+) to high DEs (95/96). Current

development work is focusing on optimization of performance parameters and extrapolation of

the achieved performance to other starch sources.


122

UPDATE ON CELLULOSIC ETHANOL

Bruce S. Dien*1,2

National Center for Agricultural Utilization Research, Agricultural Research Service, United States Department of Agriculture

1815 University Avenue, Peoria, IL 61604; (309) 681-6270, [email protected]

Commercial lignocellulosic ethanol is set to become a reality with one commercial plant

already in startup phase and several under construction throughout the world. As is

characteristic of a new industry, the commercial efforts show a wide breath of technologies.

These include processes that rely on thermochemical, biochemical and a hybrid of these two

approaches. The biochemical processes, which will be the focus of this paper, include

hydrothermal, dilute sulfuric acid and ammonia processes. These processes rely on the use of

genetically engineered yeast, such as Saccharomyces cerevisiae and Zymomonas mobilis. What

follows is a general introduction to lignocellulosic ethanol. We will emphasize current

commercial efforts and include additional material.

Lignocellulosic based processes are of interest because the potential availability of

lignocellulose is vast, up to 1.3 billion tons/year just in the U.S., and is the only potential

renewable resource available for substantially expanding ethanol production. Lignocellulose

resources include agricultural residues, such as corn stover and wheat straw, pulp and paper

wastes and (potentially) dedicated herbaceous and woody bioenergy crops. It is expected that

lignocelluloses will sell at a discount to corn. However, processing and especially capital costs

will be substantially higher than corn.

There are multiple process scenarios for biochemically converting biomass into ethanol.

As shown in Figure 1, the biocatalysts define the process. In the most conservative process

design, separate microorganisms are used to produce cellulases, ferment hexoses and pentoses

and enzymatic hydrolysis is conducted in a fourth tank. The enzyme hydrolyzer can be

1 Bioenergy Research Unit, Agricultural Research Service, United States Department of Agricultural,

Peoria, IL 61604. Names are necessary to report factually on available data; however, the USDA neither guarantees nor warrants the standard of the product, and the use of the name by USDA implies no approval of the product to the exclusion of others that may also be suitable.

2 This paper was modified from a proceedings submitted to Symposium Microorganism in Agroenergy, Brasilia, Brazil, 2002.

Figure 1. Biocatalysts define the entire process.

O

SH SS SHC SSC CBCellulase production

Cellulose hydrolysis

Hexose Fermentation

Pentose Fermentation

O O O

Each box equals one bioreactor Biofuels

Biomass


124

eliminated when cellulase and the glucose fermenting microorganism are combined for

simultaneous saccharification and fermentation (SSF). And, if hydrolysis, glucose and pentose

fermentation are all combined, which requires a microorganism capable of cofermenting these

sugars, the process can be conducted in two bioreactors as a Simultaneous Saccharification and

coFermentation (SSCF). Finally, in the ideal case of consolidated bioprocessing (CBP), a single

or consortium of microorganisms is used that produces its own enzymes as well as fermenting all

the sugars to biofuel. In this last case, only a single bioreactor is needed. Therefore, as the

complexity of the biocatalyst is increased, fewer number of tanks are needed and (hopefully)

capital costs decrease.

Process and Pretreatment

The core unit operations for producing cellulosic biofuels are pretreatment, enzymatic

hydrolysis and fermentation. Biomass is recalcitrant to enzymatic hydrolysis and therefore

extensive thermochemical processing is required to open up the structure of the plant cell wall.

The primary task for pretreatment is to allow cellulase enzymes access to individual cellulose

chains. An auxiliary purpose is to hydrolyze either completely or partially the hemicellulose

affording fermentation of these sugars. Pretreatments include processing with strong or dilute

mineral acids, various organic or ionic solvents, alkali or solely hot water.

At the Agricultural Research Service, we have developed a dilute ammonium hydroxide

process that is effective for pretreating herbaceous biomass. Biomass is pretreated at 170 to

180C for 20 min with 4 to 8%w/v ammonium solution. The ammonium is removed by

evaporation and biomass either converted to sugars by enzymes or to ethanol by SSF. Typical

glucose fermentation yields are above 80% (Table 1) and 52.9 to 79.6% for glucose and xylose

cofermentation. Total sugar yields are lower than for glucose because we are using a first

generation xylose fermenting GMO S. cerevisiae for which xylitol is a primary coproduct. We

are also currently developing on a low moisture ammonium pretreatment that uses 60% solids,

milder temperatures and the same ammonium loading. Early results are promising when used

with switchgrass. Increasing solids loading during pretreatment is advantageous for lowering

overall water usage, decreasing heating requirements because less water is heated and for

achieving higher fermentation titers, which enhances product recovery.


125

Table 2. Ethanol conversion yield efficiencies for biomass pretreated with dilute ammonium

Plant Biomass Glucose Fermentation Total Sugars Fermentation

Alfalfa (stems) (8%, 170C, 20 min) 86.4 to 94.7% 66.0 to 79.6%

Reed Canary Grass (4%, 170C, 20 min) 90.4% 53.9 to 68.2%

Forage Sorghum (4%, 170C, 20 min) 57.3 to 81.8% Not Available

Switchgrass (8%, 180C, 20 min) 67.8 to 82.9% 42.5 to 52.9%

Enzymes

The major problem with enzymes, from an engineering perspective, is they are

expensive. Recently the U.S. Department of Energy (Humbird et al 2011) estimated that even

with onsite production of cellulases, enzymes would account for 16% of production costs, which

is equal to nearly 50% of the biomass feedstock cost! The reason for this high cost is that

relative to amylases for starch hydrolysis, much higher enzyme loadings are needed for

lignocelluloses. Comparing corn fermentation (Dien et al 2012) and lignocellulose fermentations

(McMillan et al 2011) for enzyme loadings, it was observed the enzyme loading was 22× higher

and productivities 10× lower. Slower conversion rates added to capital costs because it

necessitates longer holding times and larger tanks. But the dominant reason that enzyme costs

were so high is because of the higher loadings. However, enzyme companies have and continue

to make great strides in improving enzyme efficiencies.

The choice of pretreatment also influences the selection and amount of needed enzymes.

Strong acid pretreatments hydrolyze cellulose and hemicellulose to sugars and therefore dispense

with the need for enzymes. Pretreatments that eliminate cellulose’s crystal structure lower

amount of required cellulases. These pretreatments include organosolv, concentrated phosphoric

acid and room temperature liquid ionic solutions. However, all of the above pretreatments use

nonaqueous solvents as their reaction media and are, therefore, critically dependent upon

efficient recycling loops. Dilute acid will hydrolyze hemicellulose and therefore cellulases are

required primarily for cellulose hydrolysis. As the cost of hemicellulases declines, lower

severity pretreatment conditions might be favored; this will lead to limited xylan hydrolysis.


126

Hydrothermal and alkaline pretreatments do not saccharify hemicellulose and therefore depend

upon a full suite of cellulases and hemicellulases for producing fermentable sugars.

There are numerous research strategies being applied to producing less expensive

enzymes (Table 2). While much work has been done on some of these ideas, progress continues

to be made in all of these areas. Within the ARS, we are exploring developing higher quality

feedstocks. We have observed that lowering lignin contents within forage sorghum increases

ethanol yields by 157% at similar enzyme loadings. We have been able to increase ethanol

yields using alfalfa cultivars with altered lignin composition.

Table 2. Strategies for lowering enzyme production costs. Use Less Enzymes

Better biomass and pretreatments More active enzymes and mixtures (per mg protein)

Produce Cheaper Enzymes On-site Enzyme Production (eg, Gulf Process) Produce in situ within green plants Consolidated Bioprocessing Secreted enzymes (eg, fungal enzymes expressed in yeast) Cellulosomes (eg, anaerobic bacteria)

Recycle Enzymes Fermentation and Microorganisms

A list of traits important for commercial application of microorganism is shown in Table

3. The most important traits are yield and product selectivity, tolerance and productivity as each

of these directly impacts production costs. The microorganisms should also be capable of

fermenting sugar mixtures for cofermentation of hexoses and pentoses and if a SSF scheme is

envisioned the fermentation and enzyme operative pHs need to coincide. For example, T. reesei

and S. cerevisiae both operate well at pH 5. The final list of conditions is associated with

minimizing technical risk. The strain needs to be hardy, stable for selected or molecular

engineered traits and resistant to various inhibitors commonly present in hydrolysates. Strains

that grow at a low pH or high temperature also are preferred because these culture conditions

tend to impede microbial contamination.


127

Table 3. Important traits for ethanol producers. High Ethanol Yield and Product Selectivity High Ethanol Tolerance (>50 g/l) High Ethanol Productivity Broad range of sugars fermented in sugar mixtures Compatibility with T. reesei cellulases for SSF Hardiness (in both glucose and xylose cultures) Phenotypic stability Inhibitor Tolerance (eg, furfural, HMF, acetic acid) Growth of low pH (< 5.0) or high temperature (> 50C)

The largest cost for producing cellulosic ethanol is the feedstock, which emphasizes the

importance of obtaining a good yield. Product yield also affects biomass collection and capital

costs. As yield declines more biomass is needed to maintain production, which means biomass

need to be transported from further way and more stored on location. Also, more biomass needs

to be pushed though the facility to make the same amount of ethanol. As equipment is sized

based upon feed volume, processing more biomass also increases equipment size. However, the

goal of achieving the highest possible yield is tempered by productivity. As ethanol yield

increases, so does ethanol concentration and soon ethanol begins to slow the specific

fermentation productivity. As productivity decreases, so does annual ethanol production, which

is shown for 90%+ yield. At some point, loss in potential production from the slowing

fermentation rate exceeds losses from the lower yield and fermentation is halted. In mixed

sugars fermentations, this relationship can be more complex as often xylose is repressed during

glucose fermentation and slow. The third most important fermentation parameter is ethanol

concentration. The energy for ethanol separation increases dramatically as ethanol concentration

falls below 5% w/v; therefore, most processes target 5% or more. Increasing the final ethanol

concentration beyond 5% will lower distillation costs and reduce water usage. Water

management is a critical issue that needs to be explored further.

A trait closely linked with yield, is a broad substrate utilization range. Pentosans

represent 20 to 40% of available carbohydrates. Therefore, only fermenting hexoses represents a

corresponding decrease in yield. It is hard to imagine a commercially successful cellulosic

biofuels plant that does not use pentoses. Some have suggested channeling pentoses to


128

coproducts. While coproducts can increase profitability and insure against market fluctuations,

they can also add capital expenses and (if novel) technical risks.

The final tier of microbial traits insures smooth operation of the process and minimizes

technical risk. Large fermentations are operated as open processes in which slow mixing times

ensures only approximate control of culture conditions relative to those achieved at laboratory

scale. These processes demand microorganisms that are robust and when confronted with a

process upset readily recover. Open systems, equipped with clean in place systems, are also

prone to contamination. Therefore it is helpful if the microorganism grows at either a low pH or

high temperature, which precludes the growth of most other microorganisms. As primary

fermentation reactors are very large, the inoculum needs to go through many doublings. These

microbial process traits need to be stable or population shifts may occur. For example, genetic

traits need to be integrated into the genome or under in situ selection; if the microbe was adapted

for enhanced growth (as strains often are for xylose growth) adapted changes cannot be prone to

reversion.

A final consideration is the ability of the biocatalyst to withstand inhibitory chemicals

generated as side products of pretreatment. Hydrolyzates contain a mixture of aldehydes,

phenolics and organic acids that are released or synthesized during pretreatment. Conditioning

hydrolyzates with chemical methods is expensive and generate excess waste. It is more desirable

to adapt strains to withstand these inhibitors. Biological strategies include using large inoculum,

directed evolution and genetic engineering. An example of the latter is overexpression of

alcohol dehydrogenases involved in reducing furans into their less toxic alcohol counterparts.

Acetic acid can be troublesome as it is naturally released from xylan during hydrolysis and is

often generated from bacterial contaminants. Therefore, particular attention should be played to

acetic acid tolerance, albeit the effect of acetate can be moderated by raising the culture pH. An

alternate strategy is to use a pretreatment that does not generate excess inhibitory compounds.

We have found that treatment with ammonium generates biomass readily fermented by yeast

without a lag or adaptation phase. Ammonium pretreatment does not generate furans and

converts much of the acetic acid to a lesser inhibitory compound.


129

CONCLUSION

Advances in biotechnology have and continue to promote commercialization of cellulosic

ethanol. Much progress has been made in developing cellulases and hemicellulases with

increasing specific activities and strains that more readily ferment hexose and pentose streams

faster and to higher yields. Future trends likely will include enhancing biomass quality without

sacrificing biomass yield by genetically engineering plant cell walls, continued development of

microorganisms that produce their own hydrolytic enzymes and the application of synthetic

biology for production of a broader range of fuel and coproducts.

LITERATURE CITED

Dien, B.S., D.J. Miller, R.E. Hector, R.A. Dixon, F. Chen, M. McCaslin, P. Reisen, G. Sarath

and M.A. Cotta. 2011. Enhancing alfalfa conversion efficiencies for sugar recovery and

ethanol production by altering lignin composition. Bioresource Technol 102:6479–6486

Dien, B.S., G. Sarath, J.F. Pedersen, S.E. Sattler, H. Chen, D.L. Funnell-Harris, N.N. Nichols

and M.A. Cotta. 2009. Improved Sugar Conversion and Ethanol Yield for Forage

Sorghum (Sorghum bicolor L. Moench) Lines with Reduced Lignin Contents. Bioeng.

Res. 2:153-164.

Dien, B.S., Wicklow, D.T., Singh, V., Moreau, R.A., Moser, J.K. and Cotta, M.A. 2012.

Influence of Stenocarpella maydis infected corn on the dry grind ethanol process. Cereal

Chem. 89(1):15–23.

Humbird, D, R. Davis, L. Tao, C. Kinchin, D. Hsu and A. Aden, P. Schoen, J. Lukas, B. Olthof,

M. Worley, D. Sexton and D. Dudgeon. 2011 Process Design and Economics for

Biochemical Conversion of Lignocellulosic Biomass to Ethanol: Dilute-Acid

Pretreatment and Enzymatic Hydrolysis of Corn Stover. NREL/TP-5100-47764.

McMillan J.D., E.W. Jennings, A. Mohagheghi and M. Zuccarello. 2011. Comparative

performance of precommercial cellulases hydrolyzing pretreated corn stover. Biotechnol

for Biofuels 4:29.


130

SPEAKER BIOGRAPHIES Danielle Julie Carrier Julie Carrier is a professor in Biological and Agricultural Engineering at the University of Arkansas. She received her BS, MS and PhD degrees in chemical engineering from McGill University and conducts research in the areas of processing biological materials. She has expertise in biomass saccharification, inhibitory product characterization, compound fractionation and purification as well as biorefinery coproduct development. Maria R. Cattai de Godoy

Maria de Godoy earned her MS degree in companion animal nutrition at the University of Illinois. In 2007, Maria joined the University of Kentucky as a research coordinator for the companion animal nutrition program. In 2011, she earned a PhD degree and obtained a certification in College Teaching and Learning from the University of Kentucky. Maria has given numerous invited presentations and has taught undergraduate and graduate level classes. Currently, she is a postdoctoral research associate in Animal Sciences at the University of Illinois under the guidance of Drs. Kelly Swanson and George Fahey. Bruce Dien

Bruce Dien graduated with a PhD degree in Biochemical Engineering from the University of Minnesota. He received his undergraduate degrees in Biochemistry and Food Process Engineering from Purdue University. Bruce has worked for 14 years in the ethanol field and is author or coauthor of 46 publications. He has also published several invited reviews on bioethanol and presented talks at professional meetings, including invited talks in the U.S., Korea, Japan and Portugal. He is a member of AIChE and ACS and has helped chair the AIChE topical sessions on biorefineries for the past 3 years. The themes of his work have been corn ethanol, microbial strain development and process integration. He is currently developing methods for processing herbaceous energy crops to ethanol and working with plant breeders within ARS to develop better quality energy crops.

Frederick C. Felker

Fred Felker obtained his BS and MS in Horticulture/Plant Physiology from Penn State, and his PhD in Plant Physiology from Purdue. After a postdoc at University of Wisconsin-Madison, he joined the USDA/Agricultural Research Service in Peoria, IL to study sugar movement into developing corn kernels. His research career has centered on microscopy approaches to investigate developing seeds, plant growth regulation, and starch processing technologies. He has been involved in application development for jet-cooked starch-oil composites and more recently amylose complexes prepared from jet-cooked starch.


131

Victoria Finkenstadt Victoria Finkenstadt earned her doctorate in Carbohydrate Chemistry at Purdue

University in 1997. Dr. Finkenstadt has been a research chemist at NCAUR for 15 years and investigates structure-function relationships in plant polymers, develops new materials based on agricultural commodities, and analyzes the properties of functional polymers using sophisticated analytical techniques. Laura Gentry

Laura Gentry, research assistant professor in the Crop Sciences Department at the University of Illinois Champaign-Urbana, researches sustainability of high yielding corn and soybean systems as well as bioenergy crops. Among other research projects, she manages a long-term study investigating various management scenarios for corn yield production and a study examining the feasibility of tropical maize as a bioenergy crop. From 2006 to 2010 she was an assistant professor of soil science at North Dakota State University. She has taught undergraduate courses in soil conservation and management and soil biology. Laura earned her BS degree in botany and her MS and PhD degrees in soil science from North Carolina State University. She has conducted research investigating reduced tillage systems, organic production systems, soil biology, crop rotations, residue and carbon management, sugarbeet production and reclamation of natural systems. Tom Gibbons

Tom graduated from Appalachian State University in Boone, NC with a BS in environmental chemistry. He works at Novozymes in their starch application research department in Franklinton NC.

Dell Hummel

Dell Hummel has a BS degree in Chemical Engineering from the University of Illinois and has 28 years of capital equipment sales experience. He started working closely with the starch industry in the United States and Latin America in 1991 as a sales engineer for Dorr-Oliver. He moved to Alfa Laval in 1999 after they acquired the Merco centrifuge product line from Dorr-Oliver. Dell is currently a regional sales manager for Alfa Laval’s Agro Market Unit based in Oak Brook, Illinois and has been working closely with the ethanol industry in the United States since 2001. His responsibilities include the sizing, sale and start up of separation equipment for the starch and ethanol markets. Dell is currently the Alfa Laval Sales Manager for separation equipment in ethanol, starch and sugar markets and is based in Wood Dale, Illinois. His responsibilities include the testing, sizing, sale and start up of separation equipment including decanter centrifuges, disc stack centrifuges and membranes. He also provides training seminars, technical support and field optimization for existing separation equipment.

David B. Johnston

David Johnston is a Lead Scientist at the USDA-Agricultural Research Service’s Eastern Regional Research Center in Wyndmoor, PA (suburban Philadelphia) where he leads a team conducting research on value added coproducts for improving economics and greenhouse gas emissions of corn and cellulosic fuel ethanol production. Dr. Johnston received his BS degree in Microbiology (1990) and a PhD in Food Biochemistry (1997) from the University of California, Davis. Dr. Johnston is the author of more than 40 peer reviewed and technical publications and


132

2 patents as well as numerous presentations to national and international audiences. He has received several awards for research, including: 2010 Technology Transfer Award, 2006 Bruce Wasserman Young Investigator Award, 2005 Presidential Early Career Award for Scientists and Engineers, 2005 Herbert L. Rothbart Outstanding Early Career Research Scientist; 2005 ARS, North Atlantic Area Early Career Research Scientist; 2003 Federal Executive Board Silver Medal for Excellence in “Technical Accomplishment”; 2001 Outstanding Paper in Cereal Chemistry from the Corn Refiners Association. Marvin Paulsen

Marvin Paulsen is Professor, Emeritus of Agricultural and Biological Engineering at the University of Illinois. He continues work in the area of postharvest losses, grain quality measurements, grain drying, handling and storage as well as near-infrared spectroscopy for corn and milling parameters including ethanol fermentation and coproducts. He received BS and MS degrees in agricultural engineering from the University of Nebraska and a PhD degree in agricultural engineering from Oklahoma State University. Pauline Teunissen

Pauline Teunissen is heading the R&D Grain Applications Research Group of DuPont Industrial Biosciences, formerly Genencor, at Palo Alto, California. In this position she is responsible for the development of grain application model systems which mimic plant scale processes and defining new leads for the grain processing industry. Pauline obtained a master in Food Sciences from Wageningen University in The Netherlands. In 1999, she received a PhD in Industrial Microbiology at Wageningen University, where she studied the lignin degrading enzyme system in white rot fungi. After earning her PhD, she started her career at Genencor, now DuPont Industrial Biosciences. Bradley Uken

Bradley was born and raised on a corn, soybean and wheat farm here in Champaign County. Additionally, the family operated a small farrow to finish hog operation. He attended Parkland College for two years and transferred to Illinois State University in Bloomington-Normal where he earned an Agri-Business degree. After graduation he started with the Farm Bureau. During his career with Farm Bureau he has served in three counties including Stark and Bureau counties, both in northern Illinois and for the last 10 years in Champaign County. With the Farm Bureau he oversees day to day operations of the organization while advocating for the agriculture industry, providing educational and informational material to members and informing the public about the importance of agriculture in their daily lives. The Champaign County Farm Bureau has a 10,000 plus membership based organization driven by efforts of volunteers including a 31 member board of directors.

Donghai Wang

Dr. Donghai Wang is a Professor in Biological and Agricultural Engineering at Kansas State University. His research and teaching program has focused on bioconversion of renewable materials into biofuels, chemicals, and biomaterials, and properties of biological materials. He is the author or coauthor of more than 100 peer reviewed journal articles, 6 book chapters, and 3 US patents. He is an Associate Editor for Transaction of the ASABE and Applied Engineering in Agriculture. He is the recipient of USDA research Award 2008, Frankenhoff Outstanding


133

Research Award, Kansas State University in 2009, ASABE Rain Bird Engineering Concept of the Year Award in 2010, and ASABE Superior Paper Award in 2011 and 2013. He received his Ph.D. in Biological and Agricultural Engineering (1997) from Texas A&M University at College State, TX, and did his Postdoctoral training at USDA-ARS Center for Grains and Animal Health Research, Manhattan, KS.


134

AUTHOR AND AFFILIATION INDEX

Author Affiliation Page

Bard, Sharon Centrec 29

Below, Frederick E. University of Illinois 29, 49

Bunnell, Kris University of Arkansas 7

Byars, Jeffrey A. NCAUR/ARS/USDA 80

Carrier, Danielle Julie University of Arkansas 7

de Godoy, Maria R.C. University of Illinois 111

Dien, Bruce S. NCAUR/ARS/USDA 122

Fahey, George C. Jr. University of Illinois 111

Fanta, George F. NCAUR/ARS/USDA 80

Felker, Frederick C. NCAUR/ARS/USDA 80

Finkenstadt, Victoria NCAUR/ARS/USDA 18

Gentry, Laura F. University of Illinois 49

Gibbons, Tom Novozymes NA 21

Hauser, Robert J. University of Illinois 1

Hill, Lowell University of Illinois 29

Hummel, Dell Alfa Laval 119

Johnston, David B. ERRC/ARS/USDA 3

Kenar, James A. NCAUR/ARS/USDA 80

Kleinhout, Tom Danisco NA 60

Klocke, Norman Kansas State University 62


135

Author Affiliation Page

Koops, Bart Danisco NA 60

Lamm, Freddie Kansas State University 62

Lee, Sung Ho Danisco NA 60

Letterly, Gary A. University of Illinois 49

Lipnizki, Frank Alfa Laval Copenhagen 119

Liu, Liman Kansas State University 62

Liu, Sean X. NCAUR/ARS/USDA 80

McAloon, Andrew ERRC/ARS/USDA 3

McKinney, John C. Illinois Crop Improvement 29

Paulsen, Marvin R. University of Illinois 29

Rajagopalan, Kishore Illinois Sustainable Technology Center 97

Rogers, Danny Kansas State University 62

Schlegel, Alan Kansas State University 62

Singh, Mukti NCAUR/ARS/USDA 80

Singh, Vijay University of Illinois 3

Teunissen, Pauline Danisco NA 60

Uken, Bradley Champaign County Farm Bureau 47

Wang, Donghai Kansas State University 62

Ward, Donald Danisco NA 60

Whitaker, Tom North Carolina State University 29

Yee, Winnie ERRC/ARS/USDA 3


136

FUTURE DATES AND INFORMATION

Upcoming events are listed with tentative dates. Please check our website, www.starchconference.org, for updates. Check this site for announcements and previous conference proceedings. Eventually, the proceedings from this conference will be available in PDF format for downloading at this site. Corn Wet Milling Short Course, Urbana, Illinois January 13-14, 2014 (tentative) The purpose of this course is to provide fundamental understanding of the corn wet milling process, equipment, unit operations and industry trends. Short course is intended for representatives of the wet milling industry and allied industries. The course is ideal for corn wet millers, equipment vendors, enzyme companies, trade organizations and companies associated with the corn processing industry. New Technologies in Ethanol Production, Urbana, Illinois May 19-20, 2014 (tentative) The objective of this course is to provide fundamental understanding of conventional and new ethanol production methods for representatives of the ethanol and allied industries. The course is ideal for plant personnel, technology providers, equipment vendors, enzyme companies, seed companies and trade organizations allied with the ethanol industry. The Ninth International Starch Technology Conference, Champaign, Illinois June 1-3, 2015 (tentative)

Offered every two years since 1999, this conference has facilitated interaction among international representatives from the starch processing industry, government research agencies and allied industries. The conference is unique in that it focuses on the processing of cereal grains and other starch bearing crops.

Contacts and information Kent Rausch [email protected] (217) 265-0697 Vijay Singh [email protected] (217) 333-9510 Mike Tumbleson [email protected] (217) 333-9786 www.starchconference.org


137

NOTES


138

NOTES


139

NOTES

The Eighth International Starch Technology Conference€¦ · The International Starch Technology...

Documents

Transcript of The Eighth International Starch Technology Conference€¦ · The International Starch Technology...