Understanding the limitations of grain yield monitor technology to inform on‐farm research

Abstract Yield monitoring technology (YM) is a valuable tool to evaluate crop performance in on‐farm research (OFR). However, limited information exists on utilizing this technology to accurately inform OFR. The objectives of this study were to evaluate the ability of grain yield monitor mass flow sensors to detect changes in corn ( Zea mays L.) yield for different plot lengths, provide a recommended minimum plot length to utilize YM in OFR, and determine if differences in estimating yield existed between YMs. Six treatment lengths that varied in distance of intentional yield differences (7.6, 15.2, 30.5, 61.0, 121.9, and 243.8 m) were created by alternating high‐yield (202 kg N/ha application) and low‐yield (0 kg N/ha application) plots. A total of four grain YMs with impact‐style mass flow sensors were used within two commercially available combines. Yield comparisons were made between the plot combine and YMs to evaluate the accuracy of each technology for detecting the magnitude of yield change across lengths using analysis of variance and exponential regression curves. Results indicated that the mass flow sensors were not sensitive enough to detect quickly changing flow rates for alternating yield changes in small plot lengths. Minimum plot lengths ranged from 43 to 107 m depending on YM. Significant differences were observed between grain YMs from different manufacturers. Future work could evaluate the influence additional crops or smaller yield differences have on the optimum OFR plot length.

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Publication Details

Journal
Agronomy Journal
Published
2024-09-21
DOI
https://doi.org/10.1002/agj2.21695
Citations
4
Primary Topic
Soil Mechanics and Vehicle Dynamics
Type
article
Field-Weighted Citation Impact
1.04
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article

Understanding the limitations of grain yield monitor technology to inform on‐farm research

Alysa A. Gauci, Alexander J. Lindsey, S. A. Shearer, David Barker et al.
4 citations
Agronomy Journal
Soil Mechanics and Vehicle Dynamics
1.04
article

Understanding the limitations of grain yield monitor technology to inform on‐farm research

Alysa A. Gauci, Alexander J. Lindsey, S. A. Shearer, David Barker, Elizabeth Hawkins, John P. Fulton
article en
4 citations

Abstract

Abstract Yield monitoring technology (YM) is a valuable tool to evaluate crop performance in on‐farm research (OFR). However, limited information exists on utilizing this technology to accurately inform OFR. The objectives of this study were to evaluate the ability of grain yield monitor mass flow sensors to detect changes in corn ( Zea mays L.) yield for different plot lengths, provide a recommended minimum plot length to utilize YM in OFR, and determine if differences in estimating yield existed between YMs. Six treatment lengths that varied in distance of intentional yield differences (7.6, 15.2, 30.5, 61.0, 121.9, and 243.8 m) were created by alternating high‐yield (202 kg N/ha application) and low‐yield (0 kg N/ha application) plots. A total of four grain YMs with impact‐style mass flow sensors were used within two commercially available combines. Yield comparisons were made between the plot combine and YMs to evaluate the accuracy of each technology for detecting the magnitude of yield change across lengths using analysis of variance and exponential regression curves. Results indicated that the mass flow sensors were not sensitive enough to detect quickly changing flow rates for alternating yield changes in small plot lengths. Minimum plot lengths ranged from 43 to 107 m depending on YM. Significant differences were observed between grain YMs from different manufacturers. Future work could evaluate the influence additional crops or smaller yield differences have on the optimum OFR plot length.

Agronomy JournalVol. 116(6)
The Ohio State University (US), Auburn University (US), University of South Alabama (US)
Zero hunger
Openalex Percentile: Top 26%
Soil Mechanics and Vehicle Dynamics
1.04
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Understanding the limitations of grain yield monitor technology to inform on‐farm research — Alysa A. Gauci, Alexander J. Lindsey, et al. · Agronomy Journal (2024) | TGRS Research Map | TGRS