Arvanitoyannis Ioannis S, van Houwelingen-Koukaliaroglou Maria
Department of Agriculture, Crop and Animal Production, School of Technological Sciences, University of Thessaly, Fytoko Str., 38446 Nea Ionia Magnesias, Volos, Hellas, Greece.
Crit Rev Food Sci Nutr. 2003;43(2):173-218. doi: 10.1080/10408690390826482.
Multivariate analysis has been established as a very powerful and effective tool in classifying and grouping individual products. Principal Component Analysis, Canonical analysis, Cluster and Partial Least Squares were found to be indispensable for classifying food products according to variety and/or geographical origin. Meat and meat products were correctly classified for authentication purposes to various groups following instrumental and/or sensory analyses.
多变量分析已成为对单个产品进行分类和分组的一种非常强大且有效的工具。主成分分析、典型相关分析、聚类分析和偏最小二乘法被发现对于根据品种和/或地理来源对食品进行分类是必不可少的。在进行仪器分析和/或感官分析后，肉类和肉类产品被正确分类，以用于各种认证目的的分组。
