Geographic, Soil, and Management Characteristics Impact Winter Cereal Performance.

Double cropping is both an economically and environmentally beneficial practice for dairy farmers in the northeastern United States. Double cropping can provide an additional, harvestable crop while reducing the risk of soil erosion and nutrient leaching over the winter months, and improving biodiversity and soil health. Winter-hardy winter cereals such as triticale (x Triticosecale Wittm.), winter wheat (Triticum aestivum L.), and cereal rye (Secale cereale L.) are good double crop options in New York, but they require nutrient management, especially for nitrogen (N), if they are to reach optimum yields in the spring. The most economic rate of N (MERN) applied at dormancy break in the spring will vary from location to location. Our objective here is to determine whether the MERN and yield at the MERN can be predicted by soil properties, management practices, and geographical information such as elevation and plant hardiness zone. From 2013-2016, 63 winter cereal N-rate trials were conducted in NY that included 5 rates of N (0, 34, 67, 101, and 135 kg N ha^-1) in 4 replications harvested at flag-leaf stage in May. Soil samples were taken at green-up in the spring prior to fertilization. Management practices such as artificial drainage, manure applications, seeding rates, planting dates, and the previous crop were recorded, and geospatial information including elevation, agroecological zone (measure of soil drainage characteristics and growing degree days), and plant hardiness zones were collected. The MERNs were determined with a quadratic plateau model, and classification trees were used to predict both MERN and the yield at the MERN using a range of site characteristics. The MERNs for the 63 sites ranged from 0-112 kg N ha^-1, averaging 71 kg N ha^-1 for sites with MERNs greater than 0, and yields at the MERN ranged from 1.0-6.9 Mg DM ha^-1 averaging 4.0 Mg DM ha^-1. A variety of soil, geographic, and management characteristics were selected for predicting both the MERN and the yield at the MERN.