Developing a Graphical User Interface (GUI) to Predict the Contamination of GM Corn in Non-GM Corn

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dc.contributor.author Salish, Karthik
dc.contributor.author Mosher, Gretchen
dc.contributor.author Mosher, Gretchen
dc.contributor.author Ambrose, R. P. Kingsly
dc.contributor.department Agricultural and Biosystems Engineering
dc.date 2020-05-04T22:41:41.000
dc.date.accessioned 2020-06-29T22:37:05Z
dc.date.available 2020-06-29T22:37:05Z
dc.date.copyright Wed Jan 01 00:00:00 UTC 2020
dc.date.issued 2020-01-01
dc.description.abstract <p>The current rate of population growth necessitates the use of viable technologies like genetic modification to address estimated global food and feed requirements. However, in recent years, there has been an increase in resistance against the diffusion of genetic modification technology around the world. Many countries have adopted coexistence policies to allow a certain percentage of adventitious presence in non-genetically modified crops. However, the tolerance percentage for adventitious presence has been a bottleneck to free trade in some cases. It is a challenging task to fix a tolerance percentage considering the level of permeation of genetic modification technology in agriculture. This article introduces a software developed to serve as a decision-making tool to predict the probability distribution of genetically modified (GM) contamination in non-GM grain lot using user inputs such as final quantity of processed corn, overall tolerance level, and moisture content. The output from the software includes the mass of corn in each processing stage, the tolerance level and the probability distribution of potential GM contamination. The software predicted the probability of contamination with adventitious presence at tolerance levels of 5.0%, 3.0%, 1.0%, 0.9%, 0.5%, and 0.1% as 0.05, 0.07, 0.11, 0.12, 0.16, and 0.36, respectively. The predictions from the model were compared to a similar study wherein the effect of tolerance levels incurred in the costs of segregation was studied. The mean absolute percentage error for the predictions was found to be 3.07%. This software can be used as a tool in testing GM contamination in non-GM grain against a desired threshold levels in a grain elevator.</p>
dc.description.comments <p>This article is published as Salish, Karthik, Gretchen A. Mosher, and RP Kingsly Ambrose. "Developing a Graphical User Interface (GUI) to Predict the Contamination of GM Corn in Non-GM Corn." <em>Applied Engineering in Agriculture</em> 36, no. 1 (2020): 25-31. DOI: <a href="https://doi.org/10.13031/aea.13740" target="_blank">10.13031/aea.13740</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/abe_eng_pubs/1126/
dc.identifier.articleid 2410
dc.identifier.contextkey 17603538
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath abe_eng_pubs/1126
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/830
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/abe_eng_pubs/1126/2020_MosherGretchen_DevelopingGraphical.pdf|||Fri Jan 14 18:46:07 UTC 2022
dc.source.uri 10.13031/aea.13740
dc.subject.disciplines Agriculture
dc.subject.disciplines Bioresource and Agricultural Engineering
dc.subject.disciplines Food Science
dc.subject.keywords Corn
dc.subject.keywords Genetic modification
dc.subject.keywords Graphical User Interface (GUI)
dc.subject.keywords Threshold level
dc.title Developing a Graphical User Interface (GUI) to Predict the Contamination of GM Corn in Non-GM Corn
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication d4270080-adb0-4e32-aa5c-6bce7f39e6a8
relation.isOrgUnitOfPublication 8eb24241-0d92-4baf-ae75-08f716d30801
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