Screening Yield Monitor Data Improves Grain Yield Maps

2004 ◽  
Vol 96 (4) ◽  
pp. 1091-1102 ◽  
Author(s):  
G. C. Simbahan ◽  
A. Dobermann ◽  
J. L. Ping
Keyword(s):  
Grain Yield ◽  
Yield Monitor ◽  
Monitor Data

Spatial estimation methods for mapping corn silage and grain yield monitor data

2021 ◽  
Author(s):  
Jason B. Cho ◽  
Joseph Guinness ◽  
Tulsi P. Kharel ◽  
S. Sunoj ◽  
Dilip Kharel ◽  
...  
Keyword(s):  
Grain Yield ◽  
Corn Silage ◽  
Estimation Methods ◽  
Yield Monitor ◽  
Spatial Estimation ◽  
Monitor Data

scholarly journals Spatial analysis of yield monitor data: case studies of on-farm trials and farm management decision making

2008 ◽  
Vol 9 (5) ◽  
pp. 269-283 ◽  
Author(s):  
Terry W. Griffin ◽  
Craig L. Dobbins ◽  
Tony J. Vyn ◽  
Raymond J. G. M. Florax ◽  
James M. Lowenberg-DeBoer
Keyword(s):  
Decision Making ◽  
Spatial Analysis ◽  
Case Studies ◽  
Farm Management ◽  
Management Decision ◽  
Yield Monitor ◽  
Management Decision Making ◽  
On Farm ◽  
Monitor Data

Large-Scale Field Study of Impact-Based Yield Monitor Performance

2020 ◽  
Vol 36 (2) ◽  
pp. 197-204
Author(s):  
Robert P McNaull ◽  
M. J. Darr
Keyword(s):  
Grain Yield ◽  
Mass Flow ◽  
Precision Agriculture ◽  
Large Scale ◽  
Statistical Significance ◽  
Significant Shift ◽  
Evaluation Tool ◽  
Yield Monitor ◽  
Grain Moisture ◽  
The Impact

Abstract. The grain yield monitor is the most common evaluation tool for determining the productivity of grain cropping systems. Most evaluations of grain yield monitors have focused on lab scale tests of the sensor performance and its ability to be calibrated in field trials. This study focused on the performance of the impact-based grain yield monitor during a full corn harvest season with observations and conclusions drawn on the load-to-load variation, field level, and full season accuracy from data collected over five seasons and encompassing over 2,000 evaluation loads. The load variance expectation of the impact-based yield monitor was characterized and the yield difference requirements for statistical significance were developed to aid in yield monitor based evaluations of agronomic strip trials. Following manufacturer recommended calibrations, a single cropping season calibration in corn produced field mean errors of ±5% and a season mean error of 1%. Results showed statistically significant shift in the yield monitor accuracy for grain moisture content greater than 22.5% and a load accuracy dependency on the mean mass flow rate during the full harvest season calibration evaluation. Keywords: Combine harvesters, Mass flow, Precision agriculture, Real-time sensor, Yield map, Yield monitor.

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