提高农业食品供应链可追溯性的指纹和快速方法的进展

D. Cozzolino, H. Smyth, Y. Sultanbawa
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引用次数: 0

摘要

由于消费者需求的变化、与食品安全和质量相关的复杂食品标准的发展、技术的进步(如大数据、机器学习)以及食品产业结构的变化,农业食品供应和价值链市场变得越来越复杂。然而,最近与食品真实性、掺假、欺诈、错误标签、可追溯性和来源有关的问题给消费者、食品行业和全球监管机构带来了新的担忧。传感技术与数据分析相结合,正在决定食品成分和食品评估和监测方式的范式转变。本章讨论了利用数据分析和传感技术来解决食品供应和价值链中与食品真实性、掺假、欺诈、可追溯性和来源相关的问题。特别地,本章将重点介绍基于振动光谱与数据分析相结合的快速分析方法的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advances in fingerprint and rapid methods for improved traceability in agri-food supply chains
Agri-food supply and value chain markets have become increasingly complex due to the changes in consumers demands, the development of complex food standards associated with food safety and quality, advances in technology (e.g. big data, machine learning), and changes in the food industry structure. However, recent issues related to food authenticity, adulteration, fraud, mislabelling, traceability and provenance have added a new dimension to consumers’ concerns, and food industry and regulatory bodies worldwide. The incorporation of sensing technologies combined with data analytics, are determining a paradigm shift in the way food ingredients and foods are both evaluated and monitored. This chapter discusses the utilisation of data analytics and sensing technologies to address issues related with food authenticity, adulteration, fraud, traceability and provenance in the food supply and value chains. In particular, this chapter will focus on the use of rapid analytical methods based in vibrational spectroscopy in combination with data analytics.
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