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History of Predicting Yield Potential

History of Predicting Yield Potential. TEAM VRT Oklahoma State University. Outline. Yield Goals and Potential Yield Soil Test vs. Sensor Based Sufficiency: Mobile vs. Immobile Nutrients Bray’s mobility concept How to generate nutrient recommendations What should we learn from soil testing

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History of Predicting Yield Potential

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  1. History of Predicting Yield Potential TEAM VRT Oklahoma State University

  2. Outline • Yield Goals and Potential Yield • Soil Test vs. Sensor Based • Sufficiency: Mobile vs. Immobile Nutrients • Bray’s mobility concept • How to generate nutrient recommendations • What should we learn from soil testing • Subsoil nutrient availability • Soil Testing: Correlation/Calibration/Recommendation • Models for Interpretation of Response • Interfering agronomic factors

  3. Yield Goal/Potential Yield • Yield Goal: yield per acre you hope to grow (Dahnke et al., 1988) • Potential yield: highest possible yield obtainable with ideal management, FOR specific soil and weather conditions • Maximum Yield: grain yield achievable when all manageable growth factors (nutrients, insects, disease, and weeds) are nonlimiting and the environment is ideal

  4. Yield Goals in the Literature • Yield per acre you hope to grow (Dahnke et al. (1988). • Highest yield attained in the last 4-5 years and that is usually 30-33% higher than avg. yield (J. Goos, 1998). • Aim for a 10-20% increase over the recent average (Rehm and Schmitt, 1989). • Yield goal should be based on how much water is available (stored soil water to 1.5m, Black and Bauer, 1988). • When Yield Goals are used it explicitly places the risk of predicting the environment (good or bad) on the producer.

  5. Value of Using Yield Goals • Nutrient removal can be reliably estimated for a given yield level in specific crops. • Selected Yield Goal defines the risk the producer is willing to take. • Yield Goal can define the limits in terms of economic inputs when considering herbicides, insecticides, etc.

  6. Importance of Predicting Potential Yield • Seasonal N need directly related to observed yield. • NUE decreases with increasing N rate. • Known Potential Yield = Known N Input = Highest NUE.

  7. YieldGoal Yield Goal +30% Grain yield Average Yield Bound by Environment and Management Max Yield YPMAX PotentialYieldYP0 Potential Yield with N, YPN

  8. Predicting N Needs • Use of Yield Goals. • Based on past season yields. • May take into account current-year preplant conditions of available moisture and residual N. • Seldom is adjusted for midseason conditions to alter N inputs. • Use of Potential Yield. • Reliability of predicting final yield (and N requirement) from existing soil and crop conditions should increase as harvest approaches.

  9. Spatial Variability and Yield Potential • Significant soil variability at distances less than 30 m apart (Lengnick, 1997) • In order to describe the variability encountered in field experiments, soil, plant and indirect measures should be made at the 1m or submeter resolution • Significant differences in soil test P, organic C, and pH were found at distances <0.30m (OSU)

  10. Crop Response/Models to Predict Yield (N need) • CERES (Crop-Environment Resource Synthesis) crop response model was not useful in predicting wheat grain yield (Moulin and Beckie, 1993) • Complicated. • Total N uptake at Feekes growth stage 5 was found to be a good predictor of yield (Reeves et al., 1993) • Worked some, but not all years.

  11. History of Predicting Potential Yield • 1. SF45 = (NDVI4 + NDVI5)/days from F4 to F5 • INSEY (in-season-estimated-yield) • GDD = (Tmin + Tmax)/2 – 4.4°C • 2. EY = (NDVI4 + NDVI5)/GDD from F4 to F5 • 3. INSEY = (NDVI)/days from planting to sensing • 4. INSEY = (NDVI)/days from planting to sensing where (GDD>0)

  12. 100 lb N/ac 45 bu/ac, 2.5% N in the grain 75 lb N/ac N uptake, lb/ac 50 lb N /ac days with GDD>0? October February June 0 120 240 days INSEY: Rate of N uptake over 120 days, > ½ of the total growing days and should be a good predictor of grain yield

  13. Adjusting Yield Potential October 1 Benchmark Planting Date Planting Date F5 Date F4 Date Adj. Index 42+20=62 29+6=35 Perkins 42 20 143 185 Tipton 29 6 116 145

  14. SF45 = (NDVI4 + NDVI5)/days from F4 to F5  growth YIELD POTENTIAL NDVI  growth NDVI min F4 F5 Maturity Feekes growth stage

  15. Total N Uptake 40 20 50 50 Feekes 4 Feekes 5 Grain Yield

  16. 6000 Perkins, N*P 5000 Perkins, S*N Tipton, S*N 4000 Grain Yield 3000 2000 y = 1E+06x2 - 12974x + 951.24 R2 = 0.89 1000 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 NDVI F4+NDVI F5/days from F4 to F5

  17. INSEY = (NDVI + NDVI )/GDD T1 to T2 INSEY = (NDVI + NDVI )/GDD T1 to T2 T1 T2 T1 T2 14 14 12 12 10 10 8 8 Above ground dry Above ground dry S S NDVI NDVI 6 6 T1 T2 T1 T2 4 4 weight weight GDD GDD 2 2 0 500 1000 1500 2000 2500 0 500 1000 1500 2000 2500 0 0 Cumulative growing degree days Cumulative growing degree days Rickman, R.W., Sue E. Waldman and Betty Klepper. 1996. Rickman, R.W., Sue E. Waldman and Betty Klepper. 1996. MODWht3: A development - driven wheat growth simulation. MODWht3: A development - driven wheat growth simulation. Agron J. 88:176 - 185. Agron J. 88:176 - 185.

  18. 9 experiments (NDVI F4 + NDVI F5/GDD from F4 to F5

  19. 6 experiments (NDVI F4 + NDVI F5/GDD from F4 to F5

  20. Field Experiments, 1998-2000. _____________________________________________________________________________________________ Experiment Location Year Date Planting Harvest Variety Planting to Sensed date date sensing, D/M/Y D/M/Y D/M/Y days S*N§ Perkins, OK 1998 6/4/98 21/10/97 15/6/98 Tonkawa 167 S*N§ Tipton, OK 1998 26/2/98 7/10/97 3/6/98 Tonkawa 142 N*P¶ Perkins, OK 1998 2/4/98 21/10/97 15/6/98 Tonkawa 163 N*P¶ Perkins, OK 1999 4/3/99 12/10/98 9/6/99 Tonkawa 143 Experiment 222 Stillwater, OK 1999 24/2/99 13/10/98 15/6/99 Tonkawa 134 Experiment 301 Efaw, OK 1999 24/3/99 15/10/98 15/6/99 Tonkawa 160 Efaw AA Efaw, OK 1999 24/3/99 9/11/98 15/6/99 Tonkawa 135 Experiment 502 Lahoma, OK 1999 5/3/99 9/10/98 30/6/99 Tonkawa 147 Experiment 801 Haskell, OK 1999 23/3/99 16/10/98 6/7/99 2163 158 N*P Perkins, OK 2000 8/2/00 8/10/99 30/5/00 Custer 123 Experiment 222 Stillwater, OK 2000 6/3/00 7/10/99 6/7/00 Custer 151 Experiment 301 Efaw, OK 2000 6/3/00 7/10/99 2/6/00 Custer 151 Efaw AA Efaw, OK 2000 6/3/00 7/10/99 7/7/00 Custer 151 Experiment 801 Haskell, OK 2000 14/3/00 8/10/99 2/6/00 2137 158 Experiment 502 Lahoma, OK 2000 13/3/00 12/10/99 13/6/00 Custer 153 Hennessey AA Hennessey, OK 2000 13/3/00 7/10/99 7/6/00 Custer 158

  21. Normalized Difference Vegetation Index (NDVI) = NIR ref – red ref / NIR ref + red ref (up – down) excellent predictor of plant N uptake Units: N uptake, kg ha-1

  22. 100 lb N/ac 45 bu/ac, 2.5% N in the grain 75 lb N/ac N uptake, lb/ac 50 lb N /ac days with GDD>0? October February June 0 120 240 days INSEY: Rate of N uptake over 120 days, > ½ of the total growing days and should be a good predictor of grain yield

  23. Normalized Difference Vegetation Index (NDVI) Reasonably good predictor of final grain yield

  24. T1 + NDVI NDVIT2 EstimatedYield (EY) = GDD from T1 to T2 +Good predictor of final grain yield- Requires two sensor readings +GDD y = 0.4554e344.12x R2 = 0.62

  25. NDVI at F5 In-SeasonEstimatedYield (INSEY)1 = days from planting to F5 +Good predictor of final grain yield+Requires only one sensor reading Units: N uptake, kg ha-1 day-1

  26. NDVI at F5 In-SeasonEstimatedYield (INSEY)1 = days from planting to F5 Hard Red Winter Wheat (Oklahoma)Soft White Winter Wheat (Virginia)

  27. In-SeasonEstimatedYield (INSEY)2 NDVI at F5 = days from planting to F5, GDD>0 +Good predictor of final grain yield+Requires only one sensor reading+Appears to work over different regions Units: N uptake, kg ha-1 day-1 where GDD>0

  28. In-SeasonEstimatedYield (INSEY)2 NDVI at F5 = days from planting to F5, GDD>0 Hard Red Winter Wheat (Oklahoma)Soft White Winter Wheat (Virginia)

  29. Soft White Winter Wheat7 locations in Virginia, 2001

  30. Can We Predict Yield with No Additional N Applied? YP0 • Can We Predict The Yield Increase If We Apply N in a Given Year? YPN • Can We Predict if Harvested Yield will be Less than Predicted Yield? YP?

  31. Post-maturity yield loss 12 10 8 6 4 2 0 Above ground dry weight Harvest Cumulative growing degree days

  32. VEGETATIVE REPRODUCTIVE R-NH2 NO3 NH4 R-NH2 Total N moistureheat Total N NH3 Safetyvalve amino NH NO NO 3 3 2 acids nitrate reductase nitrite reductase • NO3- + 2e (nitrate reductase) NO2- + 6e (nitrite reductase) NH4+

  33. 12 10 8 6 4 2 0 RainfallDiseaseFrost Above ground dry weight Harvest Cumulative growing degree days

  34. NEXT Section…… ???? Predicting the Increase in Yield due to Applied N N uptake, lb/ac 40 N 0 N October February June

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