Using Yield Monitors to Assess On-Farm Test Plots

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2011-08-01
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Taylor, Randal
Fulton, John
Darr, Matthew
Haag, Lucas
Staggenborg, Scott
Mullenix, Daniel
McNaull, Robert
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Darr, Matthew
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Agricultural and Biosystems Engineering

Since 1905, the Department of Agricultural Engineering, now the Department of Agricultural and Biosystems Engineering (ABE), has been a leader in providing engineering solutions to agricultural problems in the United States and the world. The department’s original mission was to mechanize agriculture. That mission has evolved to encompass a global view of the entire food production system–the wise management of natural resources in the production, processing, storage, handling, and use of food fiber and other biological products.

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In 1905 Agricultural Engineering was recognized as a subdivision of the Department of Agronomy, and in 1907 it was recognized as a unique department. It was renamed the Department of Agricultural and Biosystems Engineering in 1990. The department merged with the Department of Industrial Education and Technology in 2004.

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1905–present

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  • Department of Agricultural Engineering (1907–1990)

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Agricultural and Biosystems Engineering
Abstract

Farmer test plots have become a staple for production agriculture. These plots can range from simple side-by-side demonstration plots to a replicated research study. The rush of harvest often creates a challenge for harvesting these plots. Yield monitor data were collected from field scale plots in multiple states to assess ability to measure on-farm research. Grain mass was also measured for each plot with a weigh wagon or certified scale. The variability of yield monitor error (standard deviation) was not correlated with the magnitude of the error (mean). Thus calibration in and of itself will likely not result in more consistent yield monitor error. Determining if treatments or observations from non-replicated studies are different will be challenging. Depending on the chosen probability level, this data indicate that distinguishing a 3 to 9 percent difference was possible. Statistical analysis of replicated trials results in similar conclusions with reference and yield monitor data. Mass flow rate is one factor impacting yield monitor error.

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This is an ASABE Meeting Presentation, Paper No. 1110690.

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Sat Jan 01 00:00:00 UTC 2011