Evaluation of Precision Sensors and Nitrogen Algorithms in Wheat.

Crop sensor-based systems with developed algorithms for making mid-season fertilizer nitrogen (N) recommendations are commercially available to producers in some parts of the world. Although there is growing interest in these technologies by grain producers in Montana, use is limited by the lack of local research under Montana’s semiarid conditions. A field study was carried out at two locations in 2011, three locations in 2012, and two locations in 2013 in North West Montana: the two dryland sites at the Western Triangle Agricultural Research Center (WTARC) and the Martin farm (Martin) near Conrad, MT, and one irrigated site at the Western Agricultural Research Center (WARC) near Corvallis, MT. The spring wheat variety Choteau was grown at all sites. The objectives of this research were: 1) to evaluate two optical sensors – GreenSeeker © (model 505) and Pocket Sensor (a prototype GreenSeeker Handheld Crop Sensor), 2) to assess whether the algorithms developed in other regions can be successfully utilized under Montana conditions, and 3) determine whether sensor-based recommendations need to be adjusted depending on what N fertilizer source - liquid urea ammonium nitrate (UAN), or granular urea - is used. The experimental design included ten treatments, an unfertilized check treatment (0 kg N ha^-1), a non-limiting N-rich reference treatment (247 kg N ha^-1 ), and four preplant N application treatment rates of 22, 45, 67, and 90 kg N ha^-1 applied as broadcasted granular urea. The preplant N application treatments were repeated twice, once for in-crop application of UAN and another for granular urea.  Individual plot size was 1.5 m x 7.6 m and each treatment was replicated 4 times. Wheat crop reflectance measurements – Normalized Difference Vegetative Index (NDVI) from each plot were collected at Feekes 5 growth stage. The Feekes 5, early jointing (beginning of stem elongation, prior to first visible node) has been identified in a course of multiple field studies as the most appropriate sensing time for wheat because it provides reliable prediction of both N uptake and biomass. The two GreenSeeker crop sensors (Trimble Navigation Ltd., Sunnyvale, CA) were used to collect the NDVI measurements. According to treatment structure topdress N fertilizer was applied as broadcast urea, or as surface applied UAN (using a backpack sprayer with a fan nozzle). Topdress N recommendations were generated using algorithms experimentally developed for spring wheat: 1. Spring Wheat (Canada),

2. Spring Wheat (US/Canada/Mexico), and 3. Generalized Algorithm. The algorithms are available at: http://www.soiltesting.okstate.edu/SBNRC/SBNRC.php. Generalized algorithms did not prescribe any topdress N fertilizer to be applied at any of the experimental sites in both growing seasons. The topdress rates prescribed by the Spring Wheat (US/Canada/Mexico) algorithm ranged from of 0 kg N ha^-1 to 111 kg N ha^-1 depending on the NDVI values measured. The prescribed N rates were applied to experimental plots, and harvested grain yields were measured at crop maturity. A strong linear relationship was observed between NDVI values obtained with GreenSeeker and with Pocket Sensor (R²=0.82). GreenSeeker and Pocket Sensor NDVI readings predicted 70% and 81% of variation in spring wheat grain yields respectively across site-years (R² = 0.70 and 0.81). In all three growing season, the rates generated by the USA/Canada/Mexico Algorithm were not appropriate for grain yield optimization. Results indicated that both sensors performed well and were useful in predicting mid-season spring wheat grain yield potential. In addition, algorithms developed in other regions did not provide the appropriate topdress N rates for Montana spring wheat varieties and growing conditions. Lastly, because there were no substantial differences in grain yields associated with topdress fertilizer N source (urea vs. UAN) at any of 7 site-years, fertilizer rates do not need to be adjusted based on N fertilizer source, urea or UAN. Currently, additional research is being conducted state-wide in Montana to develop improved sensor-based N optimization algorithms for both spring wheat and winter wheat varieties for Montana growing conditions.