1. History of Predicting Yield Potential
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. Potential Yield with N, YPN
Max Yield YPMAX
Average Yield
+30%
Yield Goal
Grain yield
Potential Yield YP0
Potential Yield with N, YPN
Bound by Environment and Management

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. Yield Goals Average of the last 3 or 5 years + 20% versus observed yield

12. 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)

13. 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.

14. Growth Stages in Cereals
Stem Extension
Ripening
Stage
Heading
Tillering

15. and should be a good predictor of grain yield
50 lb N /ac
100 lb N/ac
75 lb N/ac
N uptake lb/ac
45 bu/ac, 2.5% N in the grain
INSEY: Rate of N uptake over 120 days, > ½ of the total growing days
and should be a good predictor of grain yield

16. Adjusting Yield Potential
October 1
Benchmark Planting Date
Planting Date
F4 Date
F5 Date
Adj. Index
42+20=62
29+6=35
Perkins 42
Tipton 29

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

18. INSEY INSEY = (NDVI = (NDVI + NDVI + NDVI )/GDD T1 to T214 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 2 2
GDD
GDD
500
500
1000
1000
1500
1500
2000
2000
2500
2500
Cumulative growing degree days
Cumulative growing degree days
Rickman, R.W., Sue E. Waldman and Betty Klepper
Rickman, R.W., Sue E. Waldman and Betty Klepper
MODWht3: A development
MODWht3: A development - -
driven wheat growth simulation.
driven wheat growth simulation.
Agron J. 88:176
Agron J. 88:176 - -
185.
185.

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

20. 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

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

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

23. NDVI at F5 = days from planting to F5
In-Season Estimated Yield (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

24. NDVI at F5 = days from planting to F5
In-Season Estimated Yield (INSEY)1 =
days from planting to F5
Hard Red Winter Wheat (Oklahoma) Soft White Winter Wheat (Virginia)

25. NDVI at F5 = In-Season Estimated Yield (INSEY)2
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

26. 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

28. NDVI at F5 = In-Season Estimated Yield (INSEY)2
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

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

30. Winter Wheat 24 locations in Oklahoma 1998-2001
Spring Wheat 4 locations in Ciudad Obregon, MX 2001
Soft White Winter Wheat 7 locations in Virginia, 2001

31. INSEY vs Grain Yield (24 locations in Oklahoma, 1998-2001)

32. 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?

33. Post-maturity yield loss12 10 8 6 4 2
Above ground dry weight
Harvest
Cumulative growing degree days

34. VEGETATIVE REPRODUCTIVE R-NH2 NO3 NH4 R-NH2 moisture heat NH3
Total N
moisture heat
Total N
NH3
Safety valve
amino NO NO NH 3 2 3
acids
nitrate reductase
nitrite reductase
NO3- + 2e (nitrate reductase) NO2- + 6e (nitrite reductase) NH4+

35. Rainfall Disease Frost12 10 8 6 4 2
Rainfall Disease Frost
Above ground dry weight
Harvest
Cumulative growing degree days

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