GMOtrack: Generator of Cost-Effective GMO Testing Strategies

可追溯性 风险分析(工程) 商业化 食品安全 业务 生物技术 计算机科学 生化工程 工程类 营销 医学 生物 软件工程 病理
作者
Petra Kralj Novak,Kristina Gruden,Dany Morisset,Nada Lavrač,Dejan Štebih,Ana Rotter,Jana Žel
出处
期刊:Journal of AOAC International [Oxford University Press]
卷期号:92 (6): 1739-1746 被引量:29
标识
DOI:10.1093/jaoac/92.6.1739
摘要

Abstract Commercialization of numerous genetically modified organisms (GMOs) has already been approved worldwide, and several additional GMOs are in the approval process. Many countries have adopted legislation to deal with GMO-related issues such as food safety, environmental concerns, and consumers' right of choice, making GMO traceability a necessity. The growing extent of GMO testing makes it important to study optimal GMO detection and identification strategies. This paper formally defines the problem of routine laboratory-level GMO tracking as a cost optimization problem, thus proposing a shift from the same strategy for all samples to sample-centered GMO testing strategies. An algorithm (GMOtrack) for finding optimal two-phase (screeningidentification) testing strategies is proposed. The advantages of cost optimization with increasing GMO presence on the market are demonstrated, showing that optimization approaches to analytic GMO traceability can result in major cost reductions. The optimal testing strategies are laboratory-dependent, as the costs depend on prior probabilities of local GMO presence, which are exemplified on food and feed samples. The proposed GMOtrack approach, publicly available under the terms of the General Public License, can be extended to other domains where complex testing is involved, such as safety and quality assurance in the food supply chain.
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