1. Late-Season Prediction of Wheat Grain Yield and Protein
K.W. Freeman, W.E. Thomason, E.V.Lukina,
G.V. Johnson, K.J. Wynn, J.B. Solie,
M.L. Stone, and W.R. Raun
Oklahoma State University
Department of Plant and Soil Sciences 1

2. Introduction
Pre-harvest prediction of wheat yield will assist producers
Provide more reliable field maps
Assist in pre-harvest marketing
Pre-harvest prediction of grain protein
Strong correlation between plant N and NDVI (Stone, 1996)
Determine whether or not to apply late-season N

3. Introduction
In order to describe the variability encountered in the field, soil, plant, and indirect measurements should be made at the meter or submeter level (Solie et al., 1999).
Field element size: area that provides the most precise measure of the available nutrient where the level of that nutrient changes with distance (Solie et al. 1996).
Willis (1999) defined yield maps as tools used by producers to look for general patterns and trends, and that yield monitor data could be corrected using remotely sensed data.

4. Objectives
To determine the relationship between spectral measurements taken from Feekes growth stages 9 to physiological maturity and grain yield and grain protein.

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

6. Materials and Methods Seven experimental sites: Experimental design:
Stillwater, Lahoma, Hennessey, Perkins and Haskell, OK
Experimental design:
4 experiments in long-term fertility trials, 2 anhydrous ammonia NUE trials and a Sewage Sludge loading experiment
2 x 2 m subplots placed in existing experiments with differing N rates
Spectral reflectance readings taken with photodiode-based sensor with interference filters for red at 671±6 and near infrared (NIR) at 780±6 nm wavelengths

7. Materials and Methods Experimental design (cont): Grain Production
Readings were taken at Feekes growth stages 9, 10.5,
11.2, and 11.4
Spectral indices were calculated for each subplot
at all growth stages
Grain Production
Harvest of 2 x 2 m area with a self-propelled
combine
Grain samples were ground to pass 120-mesh screen and analyzed for total N using Carlo-Erba 1500 dry combustion analyzer (Schepers et al., 1989)

8. Materials and Methods Formulas for Spectral Indices
NDVI = NIR ref – red ref / NIR ref + red ref
INSEY = NDVI (each date) / days from planting
RI = DM yield of highest yielding plots / DM yield of check
ISRI = Highest NDVI / NDVI from check

9. Feekes 9
6000
5000
y = x x 2 R 2
= 0.46
4000
Yield kg ha-1
3000
2000
1000
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9 1
NDVI

10. Feekes 9
R.I.<1.5
R.I.>1.5
6000
1000
2000
3000
4000
5000
6000
5000 2
y = x x 2
y = x x 2
4000 R 2
= 0.12 R
= 0.69
Yield kg ha-1
3000
2000
1000
0.2
0.4
0.6
0.8 1
0.2
0.4
0.6
0.8 1
NDVI
NDVI

11. Feekes 10.5
6000
5000
y = x 2 x R 2 =
4000
Yield kg ha-1
3000
2000
1000
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9 1
NDVI

12. Feekes 10.5 R.I.<1.5 R.I.>1.5 6000 6000 5000 5000 y = 2344x
4000
= 0.23
4000
y = 2188x 2 x R 2
= 0.72
Yield kg ha-1
3000
3000
2000
2000
1000
1000
0.2
0.4
0.6
0.8 1
0.2
0.4
0.6
0.8 1
NDVI
NDVI

13. NDVI and INSEY vs. Yield, Feekes 10.5
6000
6000
5000
5000
y = e
1.815x
y = e
365.08x R 2 =
4000
4000 R 2 =
Yield kg ha-1
3000
3000
2000
2000
1000
1000
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9 1
0.0005
0.001
0.0015
0.002
0.0025
0.003
0.0035
0.004
0.0045
0.005
NDVI
INSEY

14. Response Indices
Feekes 9 4 2
y = x x
3.5
Strong correlation between ISRI and RI determined at harvest
Accurately predict the crop’s ability to respond to N
RI can refine whether or not N should be applied, how much, and expected NUE R 2
= 0.98 3
2.5 RI 2
1.5 1
0.5
0.5 1
1.5 2
2.5 3
3.5 4
ISRI
Feekes 10.5 2 4
y = x x
3.5 R 2 3
= 0.93
2.5 RI 2
1.5 1
0.5 1 2 3 4 5
ISRI

15. Conclusion Grain yield was highly correlated with NDVI and INSEY
Grain yield could be accurately predicted using NDVI readings at Feekes growth stages 9 and 10.5
ISRI can accurately predict response to N
NDVI readings (Feekes 9 and 10.5) at locations with high RI (>1.5) showed higher correlation with grain yield than those with low RI (<1.5)