Agricultural and Biosystems Engineering Publications

Campus Units

Agricultural and Biosystems Engineering

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

2021

Journal or Book Title

Applied Engineering in Agriculture

Research Focus Area(s)

Biological and Process Engineering and Technology

DOI

10.13031/aea.14534

Abstract

A better ability to understand and use geographic variations in protein and oil is one way to maximize the value potential of soybeans for handlers and processors. An Iowa cooperative had been sourcing soybeans for processing from nearby elevator locations and wanted to know whether this strategy was maximizing the net processing value of the soybeans. Random and systematic errors from testing and measurement instruments also impact marketing decisions and were investigated as part of this project. During the Fall 2018 soybean harvest, soybean samples were collected from 32 country elevator locations belonging to one Iowa-based cooperative which has its own soybean processing plant. Samples were analyzed using near-infrared spectroscopy (NIR), and protein and oil content data were entered into an Estimated Processing Value (EPV) model to determine value differences of soybeans among elevator locations. Results showed substantial variability among locations that represented a $0.23/bushel EPV spread. No significant variation was found in soybean quality over the harvest season, suggesting that marketing decisions can be made at the beginning of the season. To determine the incidence of random errors, a simulated Excel-based model was used with three test cases. The introduction of random error lowered value gaps between locations, which made the discrimination of high-value locations from average or low-value locations difficult. Although protein and oil measurement with the NIR instrument was feasible even on busy harvest season days, the validity of marketing decisions using these data depended highly on the error involved in sample analysis. Future studies should identify specific sources of error and attempt to eliminate them. Specifically, one of the largest sources of error in a commodity-based market system is in the measuring units. The ability to isolate and quantify measurement error will improve the capability of the commodity-based soybean market system to focus trade decisions on end use traits, maximizing soybean value and providing incentive for improvement.

Comments

This is a manuscript of an article published as Barr, Bennett E., Charles R. Hurburgh, and Gretchen A. Mosher. "Maximizing Processing Value with Selective Handling Strategies: An Analysis of Soybeans Received at Iowa Elevators." Applied Engineering in Agriculture (2021). DOI: 10.13031/aea.14534. Posted with permission.

Copyright Owner

American Society of Agricultural and Biological Engineers

Language

en

File Format

application/pdf

Published Version

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