Butler Francis, Luijckx Niels Lucas, Marvin Hans J P, Bouzembrak Yamine, Mojtahed Vahid
UCD School of Biosystems and Food Engineering, University College Dublin, Belfield, Dublin 4, Ireland.
TNO, P.O. Box 80015, 3508, TA, Utrecht, the Netherlands.
Curr Res Food Sci. 2021 Apr 5;4:301-307. doi: 10.1016/j.crfs.2021.03.013. eCollection 2021.
Food fraud is of high concern to the food industry. A multitude of analytical technologies exist to detect fraud. However, this testing is often expensive. Available databases detailing fraud occurrences were systematically examined to determine how frequently analytical testing triggered fraud detection. A conceptual framework was developed for deciding when to implement analytical testing programmes for fraud and a framework to consider the economic costs of fraud and the benefits of its early detection. Factors associated with statistical sampling for fraud detection were considered. Choice of sampling location on the overall food-chain may influence the likelihood of fraud detection.
食品欺诈是食品行业高度关注的问题。有多种分析技术可用于检测欺诈行为。然而,这种检测通常成本高昂。对详细记录欺诈事件的现有数据库进行了系统审查,以确定分析检测触发欺诈发现的频率。开发了一个概念框架,用于决定何时实施欺诈分析检测计划,以及一个考虑欺诈经济成本及其早期发现益处的框架。还考虑了与欺诈检测统计抽样相关的因素。在整个食物链上采样位置的选择可能会影响欺诈检测的可能性。