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Identification of the Geographical Origins of Pomelos Using Multielement Fingerprinting
Author(s) -
Yan Jing,
Liu Ji,
Xiong Yabo,
Qin Wen,
Tang Cheng
Publication year - 2015
Publication title -
journal of food science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 150
eISSN - 1750-3841
pISSN - 0022-1147
DOI - 10.1111/1750-3841.12746
Subject(s) - principal component analysis , linear discriminant analysis , analytical chemistry (journal) , mathematics , statistics , chemistry , chromatography
Eighty pomelo samples and 80 soil samples were examined using a multielement component test to predict the geographical origins of pomelos produced in 4 regions (Sichuan, Chongqing, Fujian, and Guangxi Provinces) of China. The concentrations of 8 elements were determined by atomic absorption spectrometry. Ca, K, and Na were the most abundant elements. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to reduce the dimensionality of the multielement data from 8 to 2 while retaining the highest possible variance. Using PCA and LDA, 69.66% and 91.30%, respectively, of the pomelo origins were classified correctly using multielement variables, along with 67.06% and 83.40% for soil multielement analysis. Results indicated that the LDA method was more effective for geographical origin classification than PCA. The results of the multielement component test demonstrated its capability to screen pomelo origins rapidly.