Daily NDVI-Derived Phenology Metrics Improve in-Season Predictions of Biomass, Grain, Protein, and Nitrogen Accumulation in Spring Wheat.

This study examines the utility of high frequency (5 minute sampling interval) Normalized Difference Vegetation Index (NDVI) data to monitor spring wheat phenology over two complete growing seasons. Using NDVI at solar noon, four phenological periods were derived from the data using a non-parametric regression locally weighted smoothing parameter (loess) to account for day to day variability, and piecewise linear regression to determine inflection points in the seasonal NDVI curve. The NDVI derived phenological metrics (i.e. the change in NDVI per day, and duration (in days) of each phenological period) were compared against daily NDVI values throughout the season to predict harvest metrics including biomass, grain yield, grain protein concentration, and N accumulation. Daily NDVI data were generally poor predictors of harvest metrics early in the growing season (except for grain N accumulation, R² > 0.60 during tillering), and reached maximum predictive power at the onset of heading, and the middle of ripening for biomass and yield (R² ~0.50 & ~ 0.25 during heading, respectively, and R² ~ 0.50 during early ripening). Conversely, using both simple and multiple regression analysis, we found that harvest metrics were better described using the rate and duration of NDVI derived phenological periods. Simple regressions between NDVI derived phenological metrics revealed several physiologically and management relevant correlations including strong, statistically-significant (p<0.05) relationships between the rate of tillering & stem extension and total biomass (R² = 0.63 & 0.54, respectively), the duration of heading and yield (R² = 0.67), the rate of ripening and grain protein concentration (R² = 0.45), and the duration of ripening and grain N content (R² = 0.43), for example. Using multiple regression analysis, 83% of the variance in yield, 67% in protein concentration, 87% in total biomass, and 80% in grain N was explained by two to three NDVI derived phenological metrics.