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

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

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.

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

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

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

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)

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

Feekes 9 6000 5000 y = 2188.5x + 778.72x + 711.53 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

Feekes 9 R.I.<1.5 R.I.>1.5 6000 1000 2000 3000 4000 5000 6000 5000 2 y = -2530.4x + 8204.1x - 2054.1 2 y = 1628.6x + 1731.1x + 443.84 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

Feekes 10.5 6000 5000 y = 5379.6x 2 - 2310.5x + 1504.5 R 2 = 0.5943 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

Feekes 10.5 R.I.<1.5 R.I.>1.5 6000 6000 5000 5000 y = 2344x 4000 = 0.23 4000 y = 2188x 2 + 1336.7x + 708.19 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

NDVI and INSEY vs. Yield, Feekes 10.5 6000 6000 5000 5000 y = 700.86e 1.815x y = 696.59e 365.08x R 2 = 0.6039 4000 4000 R 2 = 0.6009 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

Response Indices Feekes 9 4 2 y = -0.0403x + 1.1861x - 0.0877 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 = -0.1467x + 1.5816x - 0.4018 3.5 R 2 3 = 0.93 2.5 RI 2 1.5 1 0.5 1 2 3 4 5 ISRI

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)