化学计量学
可靠性(半导体)
传感器融合
计算机科学
质量(理念)
认证(法律)
过程(计算)
领域(数学)
生化工程
质量评定
化学
食品质量
数据挖掘
人工智能
机器学习
可靠性工程
食品科学
评价方法
工程类
数学
计算机安全
物理
认识论
量子力学
纯数学
操作系统
哲学
功率(物理)
作者
Eva Borràs,Joan Ferré,Ricard Boqué,Montserrat Mestres,Laura Aceña,Olga Busto
标识
DOI:10.1016/j.aca.2015.04.042
摘要
The ever increasing interest of consumers for safety, authenticity and quality of food commodities has driven the attention towards the analytical techniques used for analyzing these commodities. In recent years, rapid and reliable sensor, spectroscopic and chromatographic techniques have emerged that, together with multivariate and multiway chemometrics, have improved the whole control process by reducing the time of analysis and providing more informative results. In this progression of more and better information, the combination (fusion) of outputs of different instrumental techniques has emerged as a means for increasing the reliability of classification or prediction of foodstuff specifications as compared to using a single analytical technique. Although promising results have been obtained in food and beverage authentication and quality assessment, the combination of data from several techniques is not straightforward and represents an important challenge for chemometricians. This review provides a general overview of data fusion strategies that have been used in the field of food and beverage authentication and quality assessment.
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