Evaluation of Sensor-Based Technologies in Montana Wheat Production Systems.

Great demand for up-to-date information on crop-specific and site-specific fertilizer use is strongly apparent among Montana wheat producers. Precision agriculture tools such as sensor-based technologies enable us to accurately access crop’s nutrient status and account for spatial and temporal variability. This enables adjusting fertilizer application rates according to site-specific conditions which results in more efficient, profitable, and sustainable crop production. The GreenSeeker 505 and GreenSeeker Handheld remote sensors were evaluated for accuracy of spring wheat and winter wheat yield potential prediction mid-season. Three sensor-based algorithms developed for topdress fertilizer recommendations in spring wheat were assessed. The NDVI’s obtained with the GreenSeeker 505 and the GreenSeeker Handheld were strongly correlated at all site-years for both spring and winter wheat. The NDVI’s explained from 39 to 97% (average of 91%) of variation in spring wheat grain yield, depending on site-year. At some site-years, in winter wheat, treatments that had higher crop reflectance values earlier in the season had yielded less than those with initially lower NDVI’s. This could be explained by the fact that due to warm fall and relatively mild first part of winter, treatments that received higher N rates produced high volume of biomass earlier in the season, using greater amounts of N, leaving less N available for grain development. Furthermore, the more developed, taller, more vigorous plants had higher NDVI’s, compared to those that received lower N rates, but later in the season, they were requiring more moisture to optimize their yield potential. Thus, NDVI values id not always increase with increased N rate applied, grain yield did not always increase proportionately as N rate increased, and plots with higher NDVI did not always produce higher yields. Additionally, significant differences in crop reflectance values were observed for six winter wheat Montana varieties evaluated. Overall, both sensors performed well and were useful in predicting spring and winter wheat grain yield potential mid-season. Algorithms developed in other regions do not provide the topdress N rates appropriate for Montana spring wheat varieties and growing conditions, emphasizing the need for developing algorithms based on Montana-derived data.