Modeling Soybean Emergence with Proximal Sensing.

Obtaining accurate field estimates of soybean [Glycine max (L.) Merr.] plant populations are critical in making replant decisions during the optimal planting timeframe. Correlations between plant biomass and canopy reflectance could potentially be used to predict early season plant populations. A 14 seeding density-by-2 variety-by-2 row spacing factorial experiment was replicated temporally in both conventional tillage and an untilled field in 2016 to assess whether measurements of canopy reflectance could discriminate between varied soybean plant populations. The planting densities ranged from 4 to 52 seeds m -2 to represent low to high population levels. Two varieties (AG2433 and P28T08R) and two row spacing (38 and 76 cm) represented the remaining factors. Canopy reflectance was measured on sampling dates approximately representing the VE, VC, V1, V2 and V3 growth stages. Reflectance was collected with a tractor-mounted spectrometer equipped to measure both canopy reflectance and ambient solar radiation in the 350-1000 nm range. Stands were counted at the VC-V1 growth stage to quantify established plant populations. Vegetation indices such as normalized difference vegetative index (NDVI) will be used to build a model that will attempt to predict the actual plant population based on the vegetation index value.