Applied use of growing degree days to refine optimum times for nitrogen stress sensing in winter wheat

Abstract

AbstractVariable influence of the environment on early‐season plant growth leads to similarly variable yield levels from year to year. This study was conducted to determine the ideal point in the growing season when normalized difference vegetation index (NDVI) sensor readings were highly correlated with grain yield. For each site‐year, NDVI readings were collected at least seven times from December through April. Readings were collected from two long‐term experiments where an N response was expected in plots that historically received different N rates. The number of days from planting to sensing where growing degree days (GDD) were more than 0 (GDD > 0) was tabulated by site‐year for all dates when NDVI data were collected. The r2 was computed for NDVI versus final grain yield at all sensing dates and plotted against the respective GDD > 0 when readings were taken. Linear plateau models were used to determine the point when the r2 peaked. Averaged over 3 yr (2016–2018), the optimum GDD > 0 needed to predict grain yield using NDVI in both long‐term trials was between 97 and 112. Use of the GDD > 0 as a numeric metric to delineate the best time and date to collect NDVI readings and predict yield potential can then be used to formulate accurate midseason fertilizer N rates. Adhering to quantitative GDD > 0 data is much more reliable than using subjective morphological scales. These critical GDD values can be reported on a day‐to‐day, by‐location basis (mesonet.org) for in‐season producer use.