Orange, mandarin, and hybrid classification using multivariate statistics based on carotenoid profiles
Orange, mandarin, and hybrid classification using multivariate statistics based on carotenoid profiles
复制标题
DOI：
10.1021/jf000866o
复制
发表时间：
2001-03-01
影响因子：
6.1
通讯作者：
Hofsommer, HJ
中科院分区：
文献类型：
--
作者：
Goodner, KL;Rouseff, RL;Hofsommer, HJ
进行了一项研究，以区分柑橘类胡萝卜素的基础上，从皂化新鲜果汁中发现的12个类胡萝卜素的HPLC测定得到的配置文件。对普通话、橙子和各种杂交品种进行了分析，以确定它们的类胡萝卜素谱。使用主成分分析（PCA）、典型判别分析（CDA）和马氏距离分析所得峰面积。这些被用来开发模型fdr分类果汁到适当的群体。32个样本进行了分析，以确定分类技术。柑橘汁和橙子汁的主成分分析结果表明，杂种柑橘汁和橙子汁的主成分分析结果表明，杂种柑橘汁和橙子汁的主成分分析结果表明，杂种柑橘汁和橙子汁的主成分CDA导致三个不同的组，只有少数的杂种在橙子组。
A study was undertaken to differentiate citrus on the basis of a carotenoid profile obtained from the HPLC determination of 12 carotenoids found in saponified fresh juice. Mandarin, orange, and; various hybrid varieties were analyzed to determine their carotenoid profiles. The resulting peak areas were analyzed using principal component analysis (PCA), canonical discriminate analysis (CDA), and Mahalanobis distances. These were used to develop models fdr classifying the juices into appropriate groups. Thirty-two samples were analyzed to determine classification techniques. Mandarin and orange juices were quite distinct, with the hybrids scattered throughout the mandarin and orange clusters using PCA. CDA resulted in three distinct groups with only a few of the hybrids in the orange grouping.