Soil and terrain properties that predict differences in local ideal seeding rate for soybean

Abstract

AbstractThe agronomic optimum seeding rate (AOSR) of soybean [Glycine max (L.) Merr.] varies based on environment. Understanding where AOSR varies within a field is useful for farmers utilizing variable rate seeding technology. An AOSR representing an area smaller than a whole field is referred to as local ideal seeding rate (LISR). The objective of this study was to identify soil and terrain properties that were most predictive of differences in LISR. Seeding rate trials were established at four fields in 2017 and three fields in 2018. Yield data were used to estimate LISR 33–68 times per field. Soil properties were estimated at the same scale as LISR using 0.2‐ha grid samples and terrain properties were calculated from 0.76‐m digital elevation model developed using light detection and ranging data. Random forest analysis was performed to identify which soil and terrain properties were predictive of LISR within each site‐year. At all site‐years, terrain properties were generally more predictive of LISR compared to soil properties. Valley depth and general curvature were in the top‐five most predictive properties at four of seven site‐years. Moving from the lowest valley to the highest ridge was associated with an increase in LISR of 76,000 seeds ha−1. Moving from the lowest relative slope position to the highest relative slope position was associated with a 38,000 seeds ha−1 increase in LISR. Terrain properties may be appealing to farmers because they relate to LISR, are publicly available data, and stable over time.