title: Identification of the geographical origins of pomelos using multielement fingerprinting.
abstract: 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.
authors.affiliation: College of Food Science, Sichuan Agricultural Univ, Sichuan, 86-625014, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Yan
authors.forename: Ji
authors.initials: J
authors.lastname: Liu
authors.forename: Yabo
authors.initials: Y
authors.lastname: Xiong
authors.forename: Wen
authors.initials: W
authors.lastname: Qin
authors.forename: Cheng
authors.initials: C
authors.lastname: Tang
mesh_terms: D002118:Calcium / Q000032:analysis; D002681:China; D002957:Citrus / Q000737:chemistry*; D016002:Discriminant Analysis; D005843:Geography; D011188:Potassium / Q000032:analysis; D025341:Principal Component Analysis; D012964:Sodium / Q000032:analysis; D012987:Soil / Q000737:chemistry*; D013054:Spectrophotometry, Atomic
chemical_list: D012987:Soil; D012964:Sodium; D011188:Potassium; D002118:Calcium
keywords: geographical origins; multielement fingerprinting; multivariate statistics; pomelo