| Scope and method of study. Efficient use of agricultural inputs is still problematic in food production. Nitrogen fertilizer requirements depend on the potential N uptake by the crop and that is related to yield potential. The objectives of this study were to estimate various climatological inputs such as air temperature, soil type and moisture with an in-season estimated yield (INSEY) index to predict grain yield, and to determine if topdress N fertilization rates could be adjusted using in-season estimates of wheat grain yield potential. Spectral measurements in red (671 +/- 6 nm) and near infrared ((NIR) 780 +/- 6 nm) bandwidths were collected from 36 winter wheat experiments over 4 growing seasons, 1998, 1999, 2000, and 2001, in Oklahoma. Different combinations of sensor readings, growing degree-days (GDD) and number of days from planting to sensing were considered in order to find the best yield predicting function. Topdress N rates for thirteen experiments were determined using a nitrogen fertilization optimization algorithm (NFOA).;Findings and conclusions. The best estimation of grain yield was achieved using an INSEY index with only two input variables, NDVI collected once, anywhere from Feekes growth stage 4 to 6, and number of days from planting to sensing with GDD above zero. Relationship between this index and winter wheat grain yield for 23 locations over 4 years had a regression coefficient of 0.55. The INSEY index proved to be a reliable predictor of potential yield and could be used for adjustment of in-season N fertilization. Considering that different climatological conditions affect crop growth and development and may vary widely from year to year at the same location, on-the-go sensing and mid-season fertilizer application should be the best way to correct nutrient deficiencies in order to obtain the best achievable yield. |
