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 • Subsoil nutrient availability • Soil Testing: Correlation/Calibration/Recommendation • Models for Interpretation of Response • Interfering agronomic factors
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
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.
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.
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.
YieldGoal Yield Goal +30% Grain yield Average Yield Bound by Environment and Management Max Yield YPMAX PotentialYieldYP0 Potential Yield with N, YPN
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.
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)
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.
Growth Stages in Cereals Stem Extension Ripening Stage Heading Tillering
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
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
SF45 = (NDVI4 + NDVI5)/days from F4 to F5 growth YIELD POTENTIAL NDVI growth NDVI min F4 F5 Maturity Feekes growth stage
Total N Uptake 40 20 50 50 Feekes 4 Feekes 5 Grain Yield
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.
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
Normalized Difference Vegetation Index (NDVI) Reasonably good predictor of final grain yield
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
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
NDVI at F5 In-SeasonEstimatedYield (INSEY)1 = days from planting to F5 Hard Red Winter Wheat (Oklahoma)Soft White Winter Wheat (Virginia)
In-SeasonEstimatedYield (INSEY)2 NDVI at F5 = days from planting to F5, GDD>0 GDD = ((Tmin + Tmax)/2)-4.4°C Units: N uptake, kg ha-1 day-1 where GDD>0
Need for GDD • Is growth possible on all days (October to May)? • Days where average temp did not exceed 4.4°C (40°F) • Count only those days where growth was possible • What if GDD was high, but moisture was limiting? • Under irrigation, use cumulative GDD
Oklahoma Mesonet Discuss Mission I.
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
In-SeasonEstimatedYield (INSEY)2 NDVI at F5 = days from planting to F5, GDD>0 Hard Red Winter Wheat (Oklahoma)Soft White Winter Wheat (Virginia)
Winter Wheat24 locations in Oklahoma1998-2001 Spring Wheat4 locations in Ciudad Obregon, MX2001 Soft White Winter Wheat7 locations in Virginia, 2001
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?
Post-maturity yield loss 12 10 8 6 4 2 0 Above ground dry weight Harvest Cumulative growing degree days
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+
12 10 8 6 4 2 0 RainfallDiseaseFrost Above ground dry weight Harvest Cumulative growing degree days
NEXT Section…… ???? Predicting the Increase in Yield due to Applied N N uptake, lb/ac 40 N 0 N October February June