On-combine yield monitors are widely used in precision agriculture for locating areas within fields where yields are reduced. However, the crop yield variability may be better interpreted by utilizing grain protein maps to reveal the factors limiting yield. The objective of this study was to develop an on-combine multi-sensor system for obtaining site-specific measurements of grain yield, grain protein concentration, and straw yield at the same spatial resolution as grain yield. The methodology is based on a mass flow yield monitor, in-line near-infrared spectrometer, and light detection and ranging (LiDAR) instrument. The LiDAR sensor is used to indirectly estimate straw yield through the measurement of crop height. Neighborhoods within the individual grain yield and protein maps obtained by the yield monitor and the protein sensor are correlated to identify areas within fields where grain yield was limited by nitrogen stress or water stress. In addition, scatter plots of grain yield and straw yield, and deviations from the observed maximum slope, are used to identify specific regions of environmental stress. Multi-sensor data are acquired at coincident locations and thus, it is not necessary to interpolate data to a common estimation grid to enable their fusion. The on-combine, multi-sensor system is illustrated with results from farm fields in eastern Oregon, USA.
Precision Agriculture – Springer Journals
Published: Mar 28, 2015
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