Olga Walsh, 9546 Old Shelby road, Montana State University, Conrad, MT and Malvern Westcott, 580 Quast Lane, Montana State University, Corvallis, MT
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. Remote sensing is a precision agriculture technique that quantitatively measures vegetation indices such as the Normalized Difference Vegetation Index (NDVI). The major objectives of this study are: 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 Western Triangle Agricultural Research Center (WTARC) (near Conrad, MT) and in a cooperating producer’s field (Lindsey Martin, Pendroy, Teton County, MT), and one irrigated study at Western Agricultural Research Center (WARC) (near Corvallis, MT) were established using the spring wheat variety Choteau. At each location, a total of 9 treatments were arranged in a Randomized Complete Block Design with 4 replications. At planting, six N rates of 0 (the unfertilized check plot), 20, 40, 60, 80, and 220 (the non-limiting N-rich reference) lb N ac-1 were applied as urea. The NDVI measurements from each treatment were collected at Feekes 5 growth stage. Topdress N rates (applied as urea, broadcasted or as UAN, foliar sprayed) were applied as prescribed by the algorithms experimentally developed for spring wheat. Grain yield, grain protein content, and N use efficiency (NUE) data were analyzed to determine whether there were statistically significant differences depending on what sensor was used to make fertilizer N recommendations. Many of the new precision sensing technologies currently on the market are very expensive and represent a costly investment for crop producers that wish to adopt them. 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.