Cornell Adapt-N Training Webinar: Cloud Computing Technology for Precision Nitrogen Management in Corn 4/3/2014 Presenters: Bianca Moebius-Clune, Greg Levow, & Harold van Es 10:30-11:00am ET/ 9:30-10:00CT: connect to Webinar at host sites, local introductions 11:00ET/10:00CT: Start of Webinar presentations-will be recorded for later reference Adapt-N.cals.cornell.edu
2014 Cornell Adapt-N Training Webinar: Cloud Computing Technology for Precision Nitrogen Management in Corn 1. N Concerns & Challenges - Why Adapt-N? 2. On-Farm Trial Results, 2011-2013 3. What s New for 2014? 4. Inner Workings of the Adapt-N Tool 5. Becoming an Expert User of Adapt-N 6. Complementary Technologies and Future Road Map for Adapt-N
2. On-Farm Trial Results, 2011-2013
Years A and B had equivalent amounts of rainfall during the whole growing season, but distributed as follows: Year May-June Precip (in) July-Aug Precip (in) Optimum N (lb/ac) A) 6.8 14.4? B) 10.2 10.9? Honeoye silt loam; cultivar: mid-maturity, planted at 30,000 plants/ac Poll #1: How did the Optimum N rates compare? a) Optimum N rates are the same because total rainfall was the same b) Optimum N rate was higher in year A c) Optimum N rate was higher in year B 4
Simulated Scenarios (PNM model) show: Total precipitation over the season matters less than how much rain falls when! Two years with the same total precipitation during the growing seasons: c) Optimum N rate was higher in year B Year May-June Precip (in) July-Aug Precip (in) Optimum N (lb/ac) A) 6.8 14.4 90 B) 10.2 10.9 160 5
2011 2013 Results: Adapt-N On-Farm Trials and tool improvement over time This grower saved ~ $30,000 in 2012 Thanks to all contributors of data and feedback for tool improvement: MGT Envirotec IA; Cornell Cooperative Extension; WNY Crop Management Association; Miner Institute; Willsboro Research Farm; Champlain Valley Agronomics; Cook s Consulting; Crop-Tech Consulting; GK Concepts Consulting; IPM Institute; AgFlex/BMP Challenge; many growers and others who have contributed.
IA: normal to wet spring NY: very dry spring Departure from Normal: June, 2011
IA: extremely dry spring and summer NY: normal spring Departure from Normal May 14 - June 12, 2012
2013: A very different year! May 2013 Departure from Normal IA: very wet spring, drought from June June 2013 NY: very wet spring
Question: Does Adapt-N work? Agronomic: Can Adapt-N improve N recommendations at sidedress time? Economic: Can Adapt-N save growers money in comparison to their current practices? Environmental: Can Adapt-N decrease excess N inputs and thus losses to the environment? Yes Yes Yes What improvements can we make to the model and interface based on the data and user feedback?
Approach: Strip Trials Can Adapt-N do better than current practice? 2+ N treatments: Grower-N rate: current practice (various methods) Adapt-N recommended N rate Sometimes: Zero, mid-range, high or low N rate Response trials from some states in 2013 (Next Level of Question: How precise is Adapt-N?) Spatially balanced design* with 4 replications Some varied # reps (1-7) and designs Many simple side-by-sides in 2013 volunteer trials in other states *van Es et al. 2007. Spatially-Balanced Complete Block designs for field experiments. Geoderma 140: 346 352; Some trials were more or less replicated with some varied layouts. C1 A1 A2 C2 A3 C3 C4 A4
2011-13: NY and IA, 104 Strip Trials Agronomic, Economic & Environmental Performance NY: 2011 (14), 2012 (42), 2013 (12) Grain (Corn-Corn, Soy-Corn) Silage IA: 2011 (9), 2012 (19), 2013 (9) All Grain N Management IA: Fall anhydrous ammonia Fall/Spring manure Spring fertilizer N IA: more early N appl. N Treatments Adapt-N vs. Grower N 1-7 reps Some additional rates
Overall Adapt-N Performance 2011-2012, IA and NY Treatment comparison (Adapt-N) (Grower-N) Iowa New York Grand Mean (n=28) (n=56) (n=84) N fertilizer input (lb ac -1 ) -32-66 -54 Total N loss during season (lb ac -1 ) -2-52 -39 Yield (bu ac -1 ) 0-3 -1 Profit ($ ac -1 ) +$20 +$31 +$27 Trials with greater profit 75% 80% 79%* *Overall performance with updated tool and optimal use: ~ 88% Moebius-Clune, et al. 2013. Adapt-N Uses Models and Weather Data to Improve Nitrogen Management for Corn. Better Crops. Vol 97:7-9. 2013.
Iowa Farmer reduces N rates in wet year Drainage: no tile drainage, saturated through early May to June in some problem areas Sidedress N Adapt-N VRN: 30-80 lb N/ac Grower target: 80 lb N/ac strips Multiple side-by side queries for yield response within management units Yield
Iowa Farmer reduces N rates in wet year Grower: 80 lb N/ac Adapt-N: 57 lb N/ac (-23lb/ac) Side-by-side comparisons Adapt-N: 211 bu/ac Grower: 214 bu/ac Δ Profit: -$5/ac Sidedress N Model inputs: Rooting Depth 34-38 OM 3.5%, Expected Yld 200 bu/ac Yield
Iowa Farmer reduces N rates in wet year Grower: 82 lb N/ac Adapt-N: 56 lb N/ac (-26lb/ac) Side-by-side comparisons Adapt-N: 183 bu/ac Grower: 186 bu/ac Δ Profit: $0/ac Sidedress N Model inputs: Rooting Depth 34-38, OM 3.5%, Expected Yld 200 bu/ac Yield
Iowa Farmer reduces N rates in wet year West Side: Former long-term sod. Good soil health. Elevation Drainage: no tile drainage, saturated through early May Sidedress N Adapt-N VRN: 45-70 lb N/ac Grower target: 80 lb N/ac strips Yield Multiple side-by side queries for yield response within management units
Iowa Farmer reduces N rates in wet year Elevation Drainage: no tile drainage, saturated through early May. Sidedress N Adapt-N: 56 lb N/ac Grower: 77 lb N/ac Yield Side-by-side comparisons Adapt-N: 172 bu/ac Grower: 179 bu/ac Sidedressed too early (V4). Mid season model updated rec 65lb/ac. Rooting Depth overestimate. Rec for 22-26 : 80lb/ac Model inputs: Rooting Depth >38 default, OM 3.5%, Expected Yld 200bu Δ Profit: -$22/ac was preventable
Iowa Farmer reduces N rates in wet year West Side: Former long-term sod. Good soil health Elevation Drainage: no tile drainage, saturated through early May. Sidedress N Adapt-N: 45 lb N/ac Grower: 80 lb N/ac Yield Side-by-side comparisons Adapt-N: 206 bu/ac Grower: 202 bu/ac Δ Profit: $38/ac Model inputs: Rooting Depth >38, OM 4%, Expected Yld 200bu
Iowa Farmer reduces N rates in wet year West Side: Former long-term sod. Good soil health Elevation Sidedress N Yield Lessons: Adapt-N: 45 lb N/ac - Adapt-N accounts for soil Grower: health 80 benefits. lb N/ac - Even after a wet spring, rates were reduced in some areas - No net profit loss ($3/ac gain on average) Model inputs: Rooting Depth >38, OM 4%, Expected Yld 200bu
IA 2013: Yield and Fertilizer Applied Yield Corn (bu/ac) Grain Yield (bu/ac) 250 200 150 100 50 0 Grower-N Adapt-N 57 58 59 61 62 63 64a 64b 65a June drought following wet May and early June impacted yields (especially 61, 62) 200 Total Total Fertilizer N N applied (lb/ac) 150 100 50 0 57 58 59 61 62 63 64a 64b 65a
Preliminary 2013 Results - Iowa Treatment comparison (Adapt-N) - (Grower-N) Trial Applied N (lb/ac) Yield (bu/ac) Profit Gain ($/ac) 57-40 -4 $0 58-40 -4 $1 59-30 3 $30 61-23 -4 -$6 62 12 0 -$6 63 30 14 $57 64a -35 4 $38 64b -26-3 $0 65b -23-3 -$5 Average -19 1 $12 67% of trials with same or increased profits Losses were minor N rate reductions despite wet spring! Drainage issues in several trials being addressed in model.
Donald & Sons Farm Implements Adapt-N Rates, Saves Money and Environmental Impact over three years Over 900 acres of corn in Central NY Most fields yield over 200bu/ac in normal year Grower practice until 2011: starter plus 200-260 lb VRN/ac 2011: one successful trial no yield loss from reduction by 140lbN/ac. 2012: Adoption with checks sidedressed fields with VRN Adapt-N rates, strips of old rates 2013: Improved adoption and implements rescue application sidedressed fields with VRN Adapt-N rates only, alert feature recommended rescue applications after late spring losses from excessive rain
Donald & Sons Farm Implements Adapt-N Rates, Saves Money and Environmental Impact over three years 2012: Sidedressed fields with VRN Adapt-N rates, left check or replicated strips of old rates Average old rate 234 lbs/ac at sidedress Average Adapt-N rate 147 lbs/ac at sidedress Management Zones Trial Design Sidedress rates Yield
Section A Fertilizer N (lb/ac) Yield (bu/ac) Profit Gain ($/ac) Grower-N 188 215a Adapt-N 118 (-70) 213a $56 A B ZeroS-N 22 129 (-69) Section B Fertilizer N (lb/ac) Yield (bu/ac) Profit Gain ($/ac) Grower-N 224 198a Adapt-N 138 (-86) 197a $42
Section A Section B Fertilizer N (lb/ac) Fertilizer N (lb/ac) Yield (bu/ac) Grower-N 258 225a Adapt-N 120 (-138) 204a* -$42 Yield (bu/ac) Grower-N 278 201a Adapt-N 168 (-110) 198a $47 Profit Gain ($/ac) (exceeds exp. yield) * p=0.12 Profit Gain ($/ac) A B Section C Fertilizer N (lb/ac) Yield (bu/ac) Profit Gain ($/ac) Grower-N 216 209a Adapt-N 129 (-87) 211a $69 ZeroS-N 22 138 (-73)
2012 Whole Farm Implementation Results Economic & Agronomic: Adapt-N succeeded in 83% of trials. Every identified case of yield loss associated with underestimated yield potential input in Adapt-N Savings averaged $43/ac Total farm savings with normal spring: over $30,000 Environmental: N rate reduced by 87 lb N/ac (non-area-weighted average) Almost 67,000 lb N saved large environmental benefit. Moebius-Clune, B., M. Carlson, D. Moebius-Clune, H. van Es, J. Melkonian and K. Severson. 2013. Case Study Part II: Central NY Farm Applies Adapt-N Rates on Whole Farm, Saves Money and Environmental Impact. What s Cropping Up?
2013 Rescue applications with high clearance equipment Growing Season Rainfall First sidedress Cumulative Total N Losses from Root Zone Rescue application By 7/14 Adapt-N recommended an additional 50lb/ac Analysis still in progress
Western NY: Branton Farm Implements 2013 Rescue N applications, rethinks N strategy Growing Season Rainfall Preplant application Rescue sidedress Standard practice: preplant N placed deep in zone-built slot, plus starter (170lb/ac total) By 7/15 Adapt-N recommended an additional ~ 40-120 lb/ac on several fields. Cumulative Total N Losses from Root Zone Rescue N (lb/ac) Yield (bu/ac) Profit Gain ($/ac) 60 42 $170 60 58 $252 60 25 $85 Planning to reduce preplant applications.
NY 2013: Yield and Fertilizer Applied 250 200 Yield 150 (bu/ac equiv) 100 50 0 5 8 9 12 15 18 22 23 24 25 27 Total Fertilizer Total N applied N (lb applied N/ac) (lb/ac) 250 200 150 100 50 0 Grower-N Adapt-N 5 8 9 12 15 18 22 23 24 25 27
Preliminary 2013 Results New York Trial Δ Applied N (lb/ac) Treatment comparison (Adapt-N) (Grower-N) Δ Yield (bu/ac equiv) Δ Profit Gain ($/ac) 5 19 4 $14 8-60 -12 -$28 9 40 30 $132 12 30 23 $98 15 20 23 $104 18-30 12 $75 22* -50-8 -$17 23 60 42 $170 24 60 58 $252 25 60 25 $85 27 70 31 $144 Average 20 21 $94 82% of trials increased profits * Manured field, high variability between 2 replicates. Causes of yield loss may be spreading unevenness and manure records. Drainage issues.
Overall Adapt-N Performance 2011-2013, IA and NY Treatment comparison (Adapt-N) (Grower-N) Iowa New York Grand Mean (n=37) (n=67) (n=104) N fertilizer input (lb ac -1 ) -29-42 -37 Yield (bu ac -1 ) 0 4 2 Profit ($ ac -1 ) +$18 +$49 +$38 Trials with greater profit 73% 81% 78%* *Overall performance with updated tool and optimal use: ~ 80-90% Moebius-Clune, et al. 2013. Adapt-N Uses Models and Weather Data to Improve Nitrogen Management for Corn. Better Crops. Vol 97:7-9. 2013.
5 min BREAK Poll #2: Do you sidedress? On average how much of your total N do you/your clients apply as sidedress? (check all that apply) a) Yes, I sidedress b) No, I apply all my nitrogen early c) I sidedress <25% of total d) I sidedress 25-50% of total e) I sidedress 50-75% of total f) I sidedress >75% of total
2013: Preliminary Look at Trial Results in new States Courtesy of batchgeo.com Over 100 trials, analysis is ongoing. Many different types: A vs. G: side by side (no rep), 2 reps, 3+ reps; some included zero-n N response trials (4-6 rates, 3 reps)
2013 Trials in new states Pennsylvania (10 side-by-sides, silage) Maryland (8 side-by-sides, 6 grain, 2 silage) Illinois (56 side-by-sides by mgmt unit in 16 fields) Indiana and Ohio (16 4-rate response trials) Wisconsin (5 6-rate response trials)
PA: Good model inputs are critical to Adapt-N performance 2 dairy farms, 10 side-by-side (A vs. G) non-replicated trials manure analysis estimated, manure not incorporated based on NY soils info default OM and rooting depth Poor Adapt-N performance explained by model inputs: ΔN: -30lb/ac ΔYield: -3.8 T/ac (-31 bu/ac equiv) ΔProfit: -$173/ac Adapt-N rates were clearly too low WHY? The model was using poor inputs
Sidedress N (lb/ac) Yield (bu/ac equiv) PA: Good model inputs are critical to Adapt-N performance 350 300 250 200 150 100 50 Δyield (A-G): -31 bu/ac equivalent expected yield Improved for 2014: OM defaults adjusted Rooting depth defaults adjusted Interface will warn user if OM defaults are used PA soils in database 0 88 89 90 91 92 93 94 95 96 97 120 100 80 60 40 20 0 Grower-N Adapt-N New Adapt-N Rec Adjusted Adapt-N rec 88 89 90 91 92 93 94 95 96 97 Resulting N Recs: Adapt-N rate increased by 50lb/ac 20lb/ac above Grower rate Further improvements with measured values Users should use representative measured values for OM and manure analyses
Sidedress N (lb/ac) Yield (bu/ac equiv) MD: In extreme growing seasons an adaptive approach will improve results 240 220 200 180 FV FV heavy soils poor drainage expected yield Improved for 2014: Rooting depth defaults adjusted MD soils in database 160 140 120 100 Δyield (A-G): -2 bu/ac 98 99 100 101 102 103 104 105 Grower-N Adapt-N Lessons: Adaptive approach: reevaluate expected yield at sidedress time 100 80 60 40 20 0 98 99 100 101 102 103 104 105 High variability results from no replication, extreme weather & small treatment differences FV = artifact of field variability
IN, OH, and WI: N Response Trials Preliminary Analysis METHODS: 1. ANOVA to answer Are there yield differences between treatments? 2. Tukey test to answer Which treatments differ? 3. In the following graphs, error bars are one standard deviation. 4. Yields marked with same letter are statistically not different, those marked with different letters are different.
Lessons from Indiana and Ohio Key factors driving under-recommendation when it occurred: 38 B AB A A 47 Model: B AB A A 1) Root-zone overestimates in wet spring 2) Drainage - model improvements in progress 49 50 B A A A C B AB A Grower Practice: 1) Early sidedressing followed by additional rain 2) Exceeding expected yield Reasons are clear and fixable
IN & OH Successes: Recommendations close to optimum 40 41 B AB A A B A A A 42 54 A A A A A A A A
IN & OH Conclusions B AB AB A 53 52 B AB AB A 1. Adapt-N rates near or above optimum in 9/16 trials, below optimum in 7/16 2. Adapt-N rates on average 50lb/ac below current grower rates (0-100lb/ac less) 3. Estimated appropriate rates on average about 40lb/ac below current reported grower rates (0-90lb/ac less) 4. 2013 data collected informs improved model precision for more consistently economical recommendations
Yield (bu/ac) Yield (bu/ac) Yield (bu/ac) Yield (bu/ac) Wisconsin Successes: Recommendations close to optimum 240 200 160 120 80 40 0 106 A A A A A A 0 50 100 150 200 250 200 180 160 140 120 100 80 60 40 20 0 108 B AB AB A AB A 0 50 100 150 200 250 Total N applied (lb N/ac) Total N applied (lb N/ac) AVG Yld Adapt-N rec. AVG Yld Adapt-N rec. 250 109 300 110 200 250 150 100 A A A A A A 200 150 100 50 0 0 50 100 150 200 250 Total N applied (lb N/ac) 50 0 C BC AB AB A A 0 50 100 150 200 250 Total N applied (lb N/ac) AVG Yld Adapt-N rec. AVG Yld Adapt-N rec.
Yield (bu/ac) Wisconsin Conclusions 1. Adapt-N rates near or above optimum in 5/5 trials 2. Adapt-N rates on average 32lb N/ac below reported grower rates (-80 to +40) 200 180 160 140 120 100 80 60 40 20 0 107 B AB A A A A 0 50 100 150 200 250 Total N applied (lb N/ac) AVG Yld Adapt-N rec.
Illinois Crop-Tech Consulting Data Collected 56 side-by-side comparisons in 16 fields comparing: Adapt-N rate recs vs. Crop-Tech adaptive variable N rate recs Comparing measured to simulated data: Rainfall Data Growth Stage Reports Multiple 1 and 2 foot Nitrate samples throughout the growing season Slides modified from: Ken and Katie Ferrie, Crop-Tech Consulting
Rainfall in % of Over or Under Estimated 0 is the farmer reported rain totals. Bars are indicators for percentage above or below the farmer reported number Adapt-N showed rainfall to be. 60 45 18% of the time below lab results 6% of the time above lab results 30 15 76% of the time with in range 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17-15 -30-45 -60 Notes: If Adapt-N reading was +/- 15% of the farmer reported rain, considered it to be within Range. Measured and simulated precip were closer on farms where good weather stations were used. Slides modified from: Ken and Katie Ferrie, Crop-Tech Consulting
Vegetative Stage Vegetative Stage Vegatative Stage Growth Stages 25 20 15 10 5 0 15 10 5 6/2/2013 6/17/2013 8/7/2013 8/26/2013 8/30/2013 9/11/2013 0 25 20 5/28 6/7 6/20 7/15 7/22 8/5 8/22 9/2 9/16 25 20 15 10 5 Best accuracy in early season (when it matters most for sidedress recommendations). Farmer Reported Adapt-N 0 Slides modified from: Ken and Katie Ferrie, Crop-Tech Consulting
Nitrate in PPM Nitrate in PPM Nitrates 30 25 20 15 10 5 0 6/5/2013 6/21/2013 7/21/2013 8/26/2013 25 W/I Range: 100% 20 15 10 W/I Range: 83% -5 to -10 ppm Off: 17% 5 0 6/3/2013 6/21/2013 7/9/2013 7/24/2013 8/6/2013 8/21/2013 Slides modified from: Ken and Katie Ferrie, Crop-Tech Consulting
Nitrate in PPM Nitrate in PPM Nitrates 30 40 25 20 35 30 25 15 20 10 5 15 10 5 0 0 W/I Range: 86% -5 to -10 ppm Off: 14% W/I Range: 0% -5 to -10 ppm Off: 57% -10 to -15 ppm Off: 29% -15 to -20 ppm Off: 33.3% Slides modified from: Ken and Katie Ferrie, Crop-Tech Consulting
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94 97 100 103 106 109 112 115 118 121 124 127 130 133 Nitrates (in ppm) in the 1 st Foot 0 is the lab reported nitrate. Bars are indicators for how far above or below the lab number Adapt-N showed nitrates to be. 20.00 15.00 24% of the time below lab results 15% of the time above lab results 10.00 61% of the time with in range 5.00 0.00-5.00-10.00-15.00-20.00-25.00 Some discrepancies likely explained by nitrate movement into second foot valuable data, analysis continues -30.00-35.00 Notes: If Adapt-N reading was +/- 5ppm of the lab result considered it to be within Range Slides modified from: Ken and Katie Ferrie, Crop-Tech Consulting
Illinois Lessons: 1. Adapt-N rates averaged ~ 60lb/ac below current CTC rates (20-90lb/ac less) caused average yield loss of 12 bu/ac (6-34 bu/ac) improved N use efficiency, but adjustments needed 2. Reasons for under-recommendation are fairly clear, mostly related to N dynamics in high-organic matter soils that are poorly drained, and fixable
Illinois Lessons: The Adaptive Approach is Very Powerful 1. Crop-Tech Consulting (Ken and Katie Ferrie) is hard to beat!! Intensive soil sampling and monitoring, and fieldspecific, data-informed recommendations do much of what Adapt-N does Field-history and agronomic expertise 2. Adapt-N compares more favorably to average IL grower practice characterized by: Fall or spring preplant applications Unlikely to sidedress No in-season 2ft nitrate sampling and adaptation Current changes being made to model, using data collected in Illinois in 2013, will be critical to improving model precision and more consistently economical recommendations.
Most Important 2013 Grower Lesson: It pays to wait with N application until sidedress IL Grower: Preplant lb N/ac: 90 (A) vs 220 (G) Sidedress lb N/ac: 90 (A) vs 30 (G) A: 65lb less N, but 2 more bu/ac in yield $41/ac NY Grower: Preplant & Starter lb N/ac: 176, placed deep, no plan to go back on (G) Sidedress lb N/ac: 60 (A) vs 0 (G) A: 60lb more N, 25-50 bu/ac yield increase $168/ac
Bottom Line: What are Adapt-N s Benefits? 2011-12: profit in ~80% of cases; average profit increase by $31/ac (NY) and $20/ac (IA) Applied N reduced in >90% of trials, on average by 54 lb/ac. Model was improved. 2013: reduced yield loss from low N, added profits of over $100/ac in many cases, maintained high N use efficiencies successfully in NY and IA despite extreme wet conditions. 2014 calibration and informed tool use will improve functionality in additional states Results provide incentive for sidedressing majority of N Adapt-N can provide both economic and environmental benefits.
1. N Concerns & Challenges - Why Adapt-N? 2. On-Farm Trial Results, 2011-2013 3. What s New for 2014? 4. Inner Workings of the Adapt-N Tool 5. Becoming an Expert User of Adapt-N 6. Complementary Technologies and Future Road Map for Adapt-N Download the next section of the webinar here: http://adapt-n.cals.cornell.edu/webinars/index.html
For more information Adapt-N, Cornell University: More information on the team, development of the tool, current research, publications, additional webinars, a blog, etc. are provided at http://adapt-n.cals.cornell.edu/ Adapt-N tool access: The new Adapt-N interface is provided through a publicprivate partnership between Cornell University and Agronomic Technology Corporation. http://www.adapt-n.com/
Acknowledgements Thanks to our Collaborators Thanks to all contributors of data and feedback for tool improvement: MGT Envirotec IA; Cornell Cooperative Extension; WNY Crop Management Association; Miner Institute; Willsboro Research Farm; Champlain Valley Agronomics; Cook's Consulting; Crop-Tech Consulting; GK Concepts Consulting; IPM Institute; AgFlex; and others who have contributed. Also, we would like to thank the many scientists whose work provided the foundations on which the Adapt-N tool is based. In particular: Jeff Wagenet, John Hutson. Thomas Sinclair, and Russell Muchow, and Jean Sogbedji for their work on the two dynamic simulation models that were combined to create the Precision Nitrogen Management Model at the core of Adapt-N. Thanks to our funders Funding and resources for the beta-testing and development Adapt-N have been provided by: Cornell University Department of Crop and Soil Sciences, Earth and Atmospheric Sciences, College of Agriculture and Life Sciences, Cornell Cooperative Extension, Hatch and Smith Lever Funds, New York Farm Viability Institute, USDA-NRCS Conservation Innovation Grants program, USDA-NIFA Agriculture and Food Research Initiative, USDA-NIFA Special Grant on Computational Agriculture (Rep. Maurice Hinchey), Northern NY Agricultural Development Program, MGT Envirotec, International Plant Nutrition Institute, Walton Family Foundation, McKnight Foundation, Northeast Sustainable Agriculture Research and Education (NE-SARE)