Both methods worked reliably in drilled grain crops and were accurate to within 4 in. or better. Measurement of corn plant population at harvest using combine-mounted sensors was successfully accomplished at the field scale. Population differences helped to explain differences in yield seen across fields. Population information was also used as an input to a computer model constructed to investigate the dynamics of grain flow in a combine. Data from the non-contact EM sensing approach was compared to data obtained with another commercial conductivity sensor which operates in contact with the soil.
Preliminary results indicate that similar information can be obtained with both methods.
Nonparametric statistical methods and advanced neural network techniques were investigated for relating spatial yield variations to variations in yield-controlling parameters such as soil fertility and topography. Nonlinear response curves obtained for yield as a function of each of the input variables generally agreed with observed yield limitations, and were useful for studying the interactions between multiple critical factors and crop yields. Remote Sensing of Nitrogen Need in Corn. The goal of this project was to relate corn spectral properties to nitrogen fertilizer needed by the crop. Crop canopy spectral properties were measured at several sites around Missouri with aerial photographs using three different types of film and also with an in-field spectral radiometer.