Sorting Agronomic Fact from Fiction Manitoba Agronomists ......December 13, 2011 12 Emergence Rate...

Sorting Agronomic Fact from Fiction

Manitoba Agronomists Conference

December 13, 2011

1



December 13, 2011

2

The Challenge for Growers • Majority of growers have already adopted more

broadly accepted BMP’s and are seeking new ways to increase productivity & profitability

• The number of products available to growers have grown dramatically in recent years with many new products diverging from what has been recommended and used on the Prairies

• While often intrigued by new or novel products, growers realize it is not possible to utilize every available input / tool and still remain profitable

• In many cases access to sound, third-party data to help determine which products are most likely to provide a return on investment is limited



December 13, 2011

3

Specialty Products spe·cial·ty (sp sh l-t ) • An item or a product of a distinctive kind or of particular superiority

Examples in Agriculture 1. Controlled release fertilizers / fertilizer enhancers

– ESN® , Agrotain®, Avail®, Ortho-P (ie: Alpine®), Wolftrax DDP® micronutrients, MES15®

2. Seed dressings / inoculant – Wolftrax ProtinusTM, OMEX Primer®, Alpine® Seed Nutrition, Jumpstart®)

3. Soil Enhancers – Best Environmenal TechnologiesTM – Custom Formula Fertilizers

4. Foliar Nutrition – OMEX – P3®/C3®, Alpine® Foliar, Loveland/UAP - Black Label® Zn, etc.)

5. Other miscellaneous products – pod sealants, growth regulators, etc.

• Can be difficult to make distinction between specialty and conventional products depending on the context and frequency in which they are used (ie: fungicides)



December 13, 2011

4

What about practices? • Many practices are also

promoted and/or adopted, again often with limited supporting 3rd party data

Examples in Agriculture

– variable rate fertilizer

– fungicide timing (ie: with herbicide)

– canola harvest management

– varietal blends for disease management

– intercropping

– row spacing



December 13, 2011

5

The Origins of Yield Busters • Initiated by IHARF Board of Directors February 2010 in

response to two main concerns: 1. Strong desire as Directors (& Farmers) to become more directly

engaged in process of establishing research priorities 2. Unprecedented influx of products introduced & marketed with

little or no 3rd party research supporting their efficacy

• Researchers saw the project as an effective means of connecting with farmers to identify their current challenges & potential gaps in research knowledge while enhancing public awareness & interest in activities

• Process involved canvassing individuals within agricultural community & challenging them to present the top 2 or 3 agronomic questions which they would like to see addressed

• All ideas put forward considered with final selections based on what was: 1. Important to producers 2. Practical and relatively straight forward to evaluate 3. Has not / is not already been extensively tested in W. Canada



December 13, 2011

6

Field Trials - 2010

• Two separate trials initated for 2010 growing season with funding provided by IHARF and Viterra and in-kind contributions from Western Ag Labs, BASF and Western Applied Research Corporation (WARC)

1. Micronutrient Seed Dressings on Various Crops

2. Fungicide Applications on Flax



December 13, 2011

7

• Secured additional funding from ADOPT & initiated a 3rd trial in 2011

1. Evaluating Various Fungicide Applications on Canola

– In-kind contributions from BASF, Bayer CropScience & Syngenta

AGRICULTURAL DEMONTRATION OF PRACTICES & TECHNOLOGIES

Field Trials - 2011



December 13, 2011

8

MicroNutrient Seed Dressings on

Various Crops Locations 1) Canora 2) Indian Head 3)

Scott 4) Swift Current

Crops 1) Wheat 2) Canola 3) Lentil

4) Field Pea

Seed Treatments 1) Untreated 2) Treated*

*Omex Zn Primer for wheat/canola & Omex Pulse Primer for lentil/field pea)

Data Collection 1) Emergence 2) Yield



December 13, 2011

9

Emergence Rate (All Crops) Indian Head 2010

Days From Planting

0 5 10 15 20 25

Pla

nt

De

nsity (

pla

nts

m-2

)

0

50

100

150

200

250

Untreated

Treated

ns

ns

ns

ns

ns : not significant* : 0.05 < P



December 13, 2011

10

Emergence Rate (All Crops) Indian Head 2011

Days From Planting

0 5 10 15 20 25

Pla

nt

De

nsity (

pla

nts

m-2

)

0

20

40

60

80

100

120

140

Untreated

Treated

ns

nsns




December 13, 2011

11

Emergence Rate (All Crops) Scott 2011

Days From Planting

0 5 10 15 20 25

Pla

nt

De

nsity (

pla

nts

m-2

)

0

20

40

60

80

100

120

Untreated

Treated

ns

nsns




December 13, 2011

12

Emergence Rate (All Crops) Swift Current 2011

Days From Planting

0 5 10 15 20

Pla

nt

De

nsity (

pla

nts

m-2

)

0

20

40

60

80

100

120

140

Untreated

Treated

ns

ns




December 13, 2011

13

Seed Dressing Effects on Grain Yield Canora 2010

Treated vs Untreated*

Wheat: P = 0.376

Canola: P = 0.878

Lentil: P = 0.109

Pea: P = 0.720 All: P = 0.995

*Results presented are

from contrasts comparing

yield with treated seed

directly to untreated

yields for each crop

Crop Type

Wheat Canola Lentil Field Pea All Crops

Gra

in Y

ield

(kg

ha

-1)

0

1000

2000

3000

4000

5000

Untreated

Treated

ns

ns

ns

ns

ns



December 13, 2011

14

Seed Dressing Effects on Grain Yield Indian Head 2010


Wheat: P = 0.860

Canola: P = 0.720

Lentil: P = 0.288

Pea: n/a

All: P = 0.482






Crop Type

Wheat Canola Lentil Pea All Crops

Gra

in Y

ield

(kg

ha

-1)

0

1000

2000

3000

4000

5000

Untreated

Treated

ns

ns

nsns



December 13, 2011

15

Seed Dressing Effects on Grain Yield Scott 2010

20

.1


Wheat: P = 0.275

Canola: P = 0.725

Lentil: P = 0.607

Pea: P = 0.783

All: P = 0.927






Crop Type


Gra

in Y

ield

(kg

ha

-1)

0

1000

2000

3000

4000

5000

Untreated

Treated

ns

ns

ns

nsns



December 13, 2011

16

Seed Dressing Effects on Grain Yield Swift Current 2010

20

.1

Crop Type


Gra

in Y

ield

(kg

ha

-1)

0

1000

2000

3000

4000

5000

Untreated

Treated

ns

ns

ns

ns

ns


Wheat: P = 0.150

Canola: P = 0.567

Lentil: P = 0.947

Pea: P = 0.597

All: P = 0.973








December 13, 2011

17

Seed Dressing Effects on Grain Yield Canora 2011


Wheat: P = 0.819

Canola: P = 0.195

Lentil: P = 0.257

Pea: P = 0.661

All: P = 0.574






Crop Type


Gra

in Y

ield

(kg h

a-1

)

0

1000

2000

3000

4000

5000

Untreated

Primer

ns

ns

nsns

ns



December 13, 2011

18

Seed Dressing Effects on Grain Yield Indian Head 2011


Wheat: P = 0.157

Canola: P = 0.467

Lentil: P = 0.809

Pea: P = 0.822

All: P = 0.638






Crop Type

Wheat Canola Lentil Pea All Crops

Gra

in Y

ield

(kg

ha

-1)

0

1000

2000

3000

4000

5000

Untreated

Treated

ns

ns

ns

ns

ns



December 13, 2011

19

Seed Dressing Effects on Grain Yield Scott 2011

20

.1


Wheat: P = 0.957

Canola: P = 0.277

Lentil: P = 0.634

Pea: P = 0.792

All: P = 0.650






Crop Type


Gra

in Y

ield

(kg

ha

-1)

0

1000

2000

3000

4000

5000

Untreated

Treated

ns

ns

ns

nsns



December 13, 2011

20

Seed Dressing Effects on Grain Yield Swift Current 2011

20

.1


Wheat: P = 0.858

Canola: P = 0.429

Lentil: P = 0.164

Pea: P = 0.177

All: P = 0.984






Crop Type


Gra

in Y

ield

(kg

ha

-1)

0

1000

2000

3000

4000

5000

Untreated

Treated

ns

ns

ns

ns

ns



December 13, 2011

21

Flax Response to Fungicide Locations:

1) Indian Head 2) Canora 3) Swift Current

Treatments

• Untreated

• Headline® EC

(0.16 l/ac)

• Proline®

(0.15 l/ac - 2011 only)

Data Collected:

1) Seed Yield



December 13, 2011

22

Visible Response



December 13, 2011

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Visible Response



December 13, 2011

24

Effects of Fungicide on Flax Yield Fungicide Treatment by Location

Location

CAN-10 CAN-11 IH-10 IH-11 SWC-10 SWC-11 ALL

Seed

Yie

ld (

kg

/ha)

0

500

1000

1500

2000

2500

3000

Check

Headline

***

ns

ns

***

***

ns

**



December 13, 2011

25

Canola Response to Fungicide Locations

1) Indian Head

2) Canora

3) Swift Current

Treatments

Data Collected

1) Seed Yield

1) Untreated 4) Lance + Headline (142 g/ac+0.12 l/ac)

2) Headline (0.16 l/ac) 5) Proline (0.15 l/ac)

3) Lance (142 g/ac) 6) Astound (390 g/ac)



December 13, 2011

26

Canola Yield Canora 2011

Che

ck

Hea

dlin

e

Lanc

e

Hea

dlin

e &

Lanc

e

Prol

ine

Asto

und

Se

ed

Yie

ld (

kg

/ha

)

0

500

1000

1500

2000

2500

3000

3500

32

a a a aa a

3132

3733

37



December 13, 2011

27

Canola Yield Indian Head 2011

Chec

k

Head

line

Lanc

e

Head

line

& La

nce

Prol

ine

Asto

und

Seed

Yie

ld (

kg

/ha)

0

500

1000

1500

2000

2500

3000

3500

43

c

ab a

bc

abab

49 50 5045

48



December 13, 2011

28

Canola Yield Swift Current 2011

Chec

k

Head

line

Lanc

e

Head

line

& La

nce

Prol

ine

Asto

und

Se

ed

Yie

ld (

kg

/ha

)

0

500

1000

1500

2000

2500

3000

3500

47

a a a aa a

47 47 4845 47



December 13, 2011

29

Canola Yield All Sites 2011

Chec

k

Head

line

Lanc

e

Head

line

& La

nce

Prol

ine

Asto

und

Se

ed

Yie

ld (

kg

/ha

)

0

500

1000

1500

2000

2500

3000

3500

41

a a a aa a

43 4345

4144



December 13, 2011

30

Top Research Priorities 2011 Rank Research Topic # of

Votes Rank Research Topic # of

Votes

#1 Fungicide application (more crops)

12 #7 Effects of elemental S on P2O5 availability

6

#2 Foliar (micro) nutrient products

11 #8 Nutritional / growth regulator products as ‘safeners’ for sensitive herbicide / crop combinations

5

#3 In-crop nutrition (micro and/or macro-nutrient products

7 #9 Intercropping research (various aspects)

4

#4 Effects of ESN on canola yield (seed place vs side band)

7 #10 MES P/S fertilizer vs ammonium sulphate blends

3

#5 Row-spacing research (canola, pulses)

7 #11 Variety blends of wheat and/or canola (high disease pressure)

3

#6 Fungicides at herbicide timing

6 #12 Pod sealants for preserving grain quality (cereals and pulses)

3



December 13, 2011

31

How many site-years are enough?

Site-Year

IH-09 IH-10 SC-09 SC-10 ME-09 ME-10 SW-09 SW-10 ALL

Gra

in Y

ield

(k

g/h

a)

0

1000

2000

3000

4000

SWATHED

STRAIGHT-CUT96%

110%82%

112%

78% 92%

119%

101%

98%



December 13, 2011

32

What is the probability of response?

Site-Year

IH-09 IH-10 SC-09 SC-10 ME-09 ME-10 SW-09 SW-10 ALL

Gra

in Y

ield

(kg

/ha

)

0

1000

2000

3000

4000

UNTREATED

POD SEALANT #1

POD SEALANT #2ns

ns

ns

ns

ns

**

ns

ns

ns

Contrast - Treated vs Untreated ns: not significant * P = 0.05-0.10 ** P = 0.01-0.05 *** P < 0.01



December 13, 2011

33

Small Plots vs Field-Scale

• Pros & cons to each

• Best approach varies with subject matter & objectives



December 13, 2011

34

Small Plot Research Advantages

• Relatively easy to control spatial variabilty

• Suitable for studies with large numbers of treatments (ie: variety trials, multiple factors)

• Lower risk / cost associated with failure

• Intensive data collection and monitoring of treatments is feasible

Disadvantages

• Specialized equipment required

• Edge effects

• Largely limited to established research farms



December 13, 2011

35

Field-Scale Research Advantages

• Utilize commercial equipment

• Implemented by growers on their own farms

• Edge effects generally not an issue

• Lower cost

• Easier than ever with GPS and GIS

Disadvantages

• Difficult to manage spatial variability

• Not practical for large number of treatments

• Higher risk if treatment results in yield loss

• Certain types of data collection not practical



December 13, 2011

36

Why statistical evaluation?

4649 49

5249

46

53 53 55

62

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

Pass #

Yie

ld (

bu

s/a

c)

• Naturally occurring variability – what is the probability that observed differences are due to chance?

NO TREATMENTS APPLIED



December 13, 2011

37

Plot Size and Replication

Source: Wuest et al. 1994. J. Prod. Agric. 7:211-215



December 13, 2011

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Take Home Messages • Yield-Busters can not possibly address every

agronomic question brought bring forward but it is a small step in the right direction

• Data from multiple years & locations is always desirable

• Probability of response is arguably just as important as average overall response

• Statistical analyses is critical for interpretation – naturally occurring variability is inherent in field trials & can be misleading if not accounted for

• BUYER BEWARE – Not unreasonable to request response data & to be critical of testimonials and non-replicated field trials



December 13, 2011

39

Acknowledgements

AGRICULTURAL DEMONTRATION OF PRACTICES & TECHNOLOGIES

East

Central

Research

Farm



December 13, 2011

40

Chris Holzapfel

Indian Head Agricultural Research Foundation

Email: [email protected]

Website: www.iharf.ca

Phone: (306) 695-4200
mailto:[email protected]://www.iharf.ca/

Sorting Agronomic Fact from Fiction Manitoba Agronomists ......December 13, 2011 12 Emergence Rate...

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