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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #124905


item Drummond, Scott
item Sudduth, Kenneth - Ken

Submitted to: American Society of Agricultural Engineers Meetings Papers
Publication Type: Other
Publication Acceptance Date: 6/30/2001
Publication Date: N/A
Citation: N/A

Interpretive Summary: Grain yield mapping is a key process in precision farming, and many farmers are beginning to rely on yield maps to interpret field variability and make crop management decisions. During harvesting, after the grain is cut, it must travel through the combine mechanism for several seconds before it reaches the grain flow sensor. This delay time must be determined and accounted for to maintain the accuracy of the yield map making process. Current methods of estimating delay time require considerable effort, provide marginal results, or both. In this research, we applied two data analysis methods, geostatistics and data segmentation, to provide objective estimates of yield monitoring system delay time. Both methods performed well, generally estimating delay time to within 1 second of the more laborious current methods. Use of these methods could allow development of more accurate yield maps by providing improved delay time estimates, either ron a field-by-field basis, or for smaller within-field areas. This has th potential to benefit both agricultural advisors and the farmers who use yield maps in the decision-making process.

Technical Abstract: Knowledge of the combine delay time from cutting the crop to grain flow sensing is required for accurate spatial location of grain yield data. Geostatistical and data segmentation methods were developed to estimate yield monitoring system delay time with objective criteria. The developed methods were validated with ideal data, and with mapped RTK-GPS elevation and EC data having known delay times. Results from these new methods were within 1 second of the known delay times. Both methods were applied to mass flow and moisture content measurements collected with a commercial yield monitoring system. The methods successfully estimated delay time, compared with results achieved by a visual method. Both the geostatistical and the segmentation method grain yield delay times were within 1 s of visual results in 10 of 12 cases. Grain flow and grain moisture content exhibited different delay times at different locations within the test field. Thus, it may be appropriate to apply delay time corrections to homogeneous sub-field areas instead of on a whole-field basis.