Evaluation of Sensor-Based Technologies and Nitrogen Sources for Improved Recommendations for Dryland and Irrigated Spring Wheat Production.

Precision agriculture tools such as sensor-based technologies allow us to accurately access the 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 feasibility of various sensor-based systems must be evaluated before a recommendation can be made as to what system is more efficient and appropriate for Montana conditions. The major objectives of this study were: 1. To evaluate two sensors – GreenSeeker, and Pocket Sensor – for developing NDVI-based topdress fertilizer N recommendations for dryland and irrigated spring wheat production in Montana, and 2. To determine whether sensor-based recommendations have to be adjusted depending on what N fertilizer source (liquid urea ammonium nitrate (UAN), or granular urea) is used. Three experiments: two dryland studies – at WTARC and in a producer’s field (Pat Wheeler, Valier, Pondera County), and one irrigated study at WARC were established using the spring wheat variety Choteau. There were a total of 10 treatments, each replicated 4 times. The preplant N rates of 0, 20, 40, 60, and 80 lb N ac^-1 were applied as broadcasted urea. There were two reference treatments at each site – the unfertilized check plot (0 lb N ac^-1), and the non-limiting N-rich reference (220 lb N ac^-1). The NDVI readings from each treatment were collected at Feekes 5 growth stage. Topdress N rates (applied as urea, broadcasted or as UAN, foliar sprayed) were prescribed using NDVI values and six algorithms experimentally developed for spring wheat. Also, a new generalized algorithm was tested. Grain yield, protein content, and NUE data were analyzed to determine whether there were statistically significant differences depending on what sensor was used to make fertilizer N recommendations. There were no substantial differences in grain yields associated with topdress fertilizer N source (urea vs UAN) at any of 5 site-years. This indicated that topdress N fertilizer rates do not need to be adjusted based of fertilizer sources used, i.e. the same N rates should be prescribed whether urea or UAN is applied. GreenSeeker NDVI was able to predict 91 % of variation in spring wheat grain yields across site-years, while Pocket Sensor NDVI explained 96% of variation on yield. Spring Wheat (Canada) Algorithm and Generalized Algorithm did not prescribe any topdress N fertilizer to be applied at any of the 5 site-years. The recommended application rates generated by the Sensor-Based Nitrogen Optimization Algorithm (USA/Canada/Mexico) ranged from of 0 lb N ac^-1 at Martin in 2012 to 99 lb N ac^-1 at WARC at 2012, depending on the NDVI values. Sensor-based generated topdress N rates did not always optimize grain yields, some rates were excessive, and others were not adequate. Spring wheat is produced for its quality, represented by high grain protein content.  Evaluating NUE in spring wheat should take into an account both grain yield and protein content. Results underline the importance of currently undergoing development of sensor-based algorithms for Montana wheat varieties and growing conditions from the point of view of maximizing both yield and grain quality.