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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 2
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 Protinus TM, OMEX Primer, Alpine Seed Nutrition, Jumpstart ) 3. Soil Enhancers Best Environmenal Technologies TM 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) 3
What about practices? Many practices are also promoted and/or adopted, again often with limited supporting 3 rd party data Examples in Agriculture variable rate fertilizer fungicide timing (ie: with herbicide) canola harvest management varietal blends for disease management intercropping row spacing 4
The Origi of Yield Busters Initiated by IHARF Board of Directors February 2010 in respoe to two main concer: 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 3 rd party research supporting their efficacy Researchers saw the project as an effective mea 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 questio which they would like to see addressed All ideas put forward coidered with final selectio based on what was: 1. Important to producers 2. Practical and relatively straight forward to evaluate 3. Has not / is not already been exteively tested in W. Canada 5
Field Trials - 2010 Two separate trials initated for 2010 growing season with funding provided by IHARF and Viterra and in-kind contributio from Western Ag Labs, BASF and Western Applied Research Corporation (WARC) 1. Micronutrient Seed Dressings on Various Crops 2. Fungicide Applicatio on Flax 6
Field Trials - 2011 Secured additional funding from ADOPT & initiated a 3 rd trial in 2011 AGRICULTURAL DEMONTRATION OF PRACTICES & TECHNOLOGIES 1. Evaluating Various Fungicide Applicatio on Canola In-kind contributio from BASF, Bayer CropScience & Syngenta 7
MicroNutrient Seed Dressings on Various Crops Locatio 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 8
Emergence Rate (All Crops) Indian Head 2010 250 200 Untreated Treated Plant Deity (plants m -2 ) 150 100 50 0 : not significant * : 0.05 < P <= 0.10 ** : 0.01 < P <= 0.05 *** : P <= 0.01 0 5 10 15 20 25 Days From Planting 9
Emergence Rate (All Crops) Indian Head 2011 140 120 Untreated Treated Plant Deity (plants m -2 ) 100 80 60 40 20 0 : not significant * : 0.05 < P <= 0.10 ** : 0.01 < P <= 0.05 *** : P <= 0.01 0 5 10 15 20 25 Days From Planting 10
Emergence Rate (All Crops) Scott 2011 120 Plant Deity (plants m -2 ) 100 80 60 40 20 0 Untreated Treated : not significant * : 0.05 < P <= 0.10 ** : 0.01 < P <= 0.05 *** : P <= 0.01 0 5 10 15 20 25 Days From Planting 11
Emergence Rate (All Crops) Swift Current 2011 140 120 Untreated Treated Plant Deity (plants m -2 ) 100 80 60 40 20 0 : not significant * : 0.05 < P <= 0.10 ** : 0.01 < P <= 0.05 *** : P <= 0.01 0 5 10 15 20 Days From Planting 12
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 Grain Yield (kg ha -1 ) 5000 4000 3000 2000 1000 Untreated Treated 0 Wheat Canola Lentil Field Pea All Crops Crop Type 13
Seed Dressing Effects on Grain Yield Indian Head 2010 Treated vs Untreated* Wheat: P = 0.860 Canola: P = 0.720 Lentil: P = 0.288 Pea: n/a All: P = 0.482 *Results presented are from contrasts comparing yield with treated seed directly to untreated yields for each crop Grain Yield (kg ha -1 ) 5000 4000 3000 2000 1000 Untreated Treated 0 Wheat Canola Lentil Pea All Crops Crop Type 14
Seed Dressing Effects on Grain Yield Scott 2010 Treated vs Untreated* Wheat: P = 0.275 Canola: P = 0.725 Lentil: P = 0.607 Pea: P = 0.783 All: P = 0.927 *Results presented are from contrasts comparing yield with treated seed directly to untreated yields for each crop Grain Yield (kg ha -1 ) 5000 4000 3000 2000 1000 Untreated Treated 20.1 0 Wheat Canola Lentil Field Pea All Crops Crop Type 15
Seed Dressing Effects on Grain Yield Swift Current 2010 Treated vs Untreated* Wheat: P = 0.150 Canola: P = 0.567 Lentil: P = 0.947 Pea: P = 0.597 All: P = 0.973 *Results presented are from contrasts comparing yield with treated seed directly to untreated yields for each crop Grain Yield (kg ha -1 ) 5000 4000 3000 2000 1000 Untreated Treated 20.1 0 Wheat Canola Lentil Field Pea All Crops Crop Type 16
Seed Dressing Effects on Grain Yield Canora 2011 Treated vs Untreated* Wheat: P = 0.819 Canola: P = 0.195 Lentil: P = 0.257 Pea: P = 0.661 All: P = 0.574 *Results presented are from contrasts comparing yield with treated seed directly to untreated yields for each crop Grain Yield (kg ha -1 ) 5000 4000 3000 2000 1000 Untreated Primer 0 Wheat Canola Lentil Field Pea All Crops Crop Type 17
Seed Dressing Effects on Grain Yield Indian Head 2011 Treated vs Untreated* Wheat: P = 0.157 Canola: P = 0.467 Lentil: P = 0.809 Pea: P = 0.822 All: P = 0.638 *Results presented are from contrasts comparing yield with treated seed directly to untreated yields for each crop Grain Yield (kg ha -1 ) 5000 4000 3000 2000 1000 Untreated Treated 0 Wheat Canola Lentil Pea All Crops Crop Type 18
Seed Dressing Effects on Grain Yield Scott 2011 Treated vs Untreated* Wheat: P = 0.957 Canola: P = 0.277 Lentil: P = 0.634 Pea: P = 0.792 All: P = 0.650 *Results presented are from contrasts comparing yield with treated seed directly to untreated yields for each crop Grain Yield (kg ha -1 ) 5000 4000 3000 2000 1000 Untreated Treated 20.1 0 Wheat Canola Lentil Field Pea All Crops Crop Type 19
Seed Dressing Effects on Grain Yield Swift Current 2011 Treated vs Untreated* Wheat: P = 0.858 Canola: P = 0.429 Lentil: P = 0.164 Pea: P = 0.177 All: P = 0.984 *Results presented are from contrasts comparing yield with treated seed directly to untreated yields for each crop Grain Yield (kg ha -1 ) 5000 4000 3000 2000 1000 Untreated Treated 20.1 0 Wheat Canola Lentil Field Pea All Crops Crop Type 20
Flax Respoe to Fungicide Locatio: 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 21
Visible Respoe 22
Visible Respoe 23
Effects of Fungicide on Flax Yield Fungicide Treatment by Location 3000 Seed Yield (kg/ha) 2500 2000 1500 1000 *** *** ** Check Headline *** 500 0 CAN-10 CAN-11 IH-10 IH-11 SWC-10 SWC-11 ALL Location 24
Canola Respoe to Fungicide Locatio 1) Indian Head 2) Canora 3) Swift Current Treatments 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) Data Collected 1) Seed Yield 25
Canola Yield Canora 2011 3500 3000 Seed Yield (kg/ha) 2500 2000 1500 1000 a 32 a 31 a 32 a 37 a 33 a 37 500 0 Check Headline Lance Headline & Lance Proline Astound 26
Canola Yield Indian Head 2011 3500 Seed Yield (kg/ha) 3000 2500 2000 1500 1000 c 43 ab a ab 49 50 50 bc 45 ab 48 500 0 Check Headline Lance Headline & Lance Proline Astound 27
Canola Yield Swift Current 2011 3500 3000 a a a a a a Seed Yield (kg/ha) 2500 2000 1500 1000 47 47 47 48 45 47 500 0 Check Headline Lance Headline & Lance Proline Astound 28
Canola Yield All Sites 2011 3500 Seed Yield (kg/ha) 3000 2500 2000 1500 1000 a 41 a a a a 43 43 45 41 a 44 500 0 Check Headline Lance Headline & Lance Proline Astound 29
Top Research Priorities 2011 Rank Research Topic # of Votes #1 Fungicide application (more crops) Rank Research Topic # of Votes 12 #7 Effects of elemental S on P2O5 availability 6 #2 Foliar (micro) nutrient products #3 In-crop nutrition (micro and/or macro-nutrient products #4 Effects of ESN on canola yield (seed place vs side band) #5 Row-spacing research (canola, pulses) #6 Fungicides at herbicide timing 11 #8 Nutritional / growth regulator products as safeners for seitive herbicide / crop combinatio 7 #9 Intercropping research (various aspects) 7 #10 MES P/S fertilizer vs ammonium sulphate blends 7 #11 Variety blends of wheat and/or canola (high disease pressure) 6 #12 Pod sealants for preserving grain quality (cereals and pulses) 5 4 3 3 3 30
How many site-years are enough? 4000 96% 112% SWATHED STRAIGHT-CUT Grain Yield (kg/ha) 3000 2000 1000 82% 110% 78% 92% 119% 101% 98% 0 IH-09 IH-10 SC-09 SC-10 ME-09 ME-10 SW-09 SW-10 ALL Site-Year 31
What is the probability of respoe? 4000 UNTREATED POD SEALANT #1 POD SEALANT #2 Grain Yield (kg/ha) 3000 2000 1000 ** Contrast - Treated vs Untreated : not significant * P = 0.05-0.10 ** P = 0.01-0.05 *** P < 0.01 0 IH-09 IH-10 SC-09 SC-10 ME-09 ME-10 SW-09 SW-10 ALL Site-Year 32
Small Plots vs Field-Scale Pros & co to each Best approach varies with subject matter & objectives 33
Advantages Small Plot Research 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 Inteive data collection and monitoring of treatments is feasible Disadvantages Specialized equipment required Edge effects Largely limited to established research farms 34
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 35
Yield (bus/ac) Why statistical evaluation? Naturally occurring variability what is the probability that observed differences are due to chance? 70 60 50 62 46 49 49 52 53 53 55 49 46 40 30 20 NO TREATMENTS APPLIED 10 0 1 2 3 4 5 6 7 8 9 10 Pass # 36
Plot Size and Replication Source: Wuest et al. 1994. J. Prod. Agric. 7:211-215 37
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 & locatio is always desirable Probability of respoe is arguably just as important as average overall respoe 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 respoe data & to be critical of testimonials and non-replicated field trials 38
Acknowledgements East Central Research Farm AGRICULTURAL DEMONTRATION OF PRACTICES & TECHNOLOGIES 39
Chris Holzapfel Indian Head Agricultural Research Foundation Email: cholzapfel.iharf@sasktel.net Website: www.iharf.ca Phone: (306) 695-4200 40