Identification of Walnut from Different Regions of China by Statistical Methods Based on the Determination of Multi-element Contents / 基于多元素含量的统计学方法鉴别我国不同产地核桃

• Published in: Forest research (Beijing) Vol. 30; no. 5; p. 779
• Main Authors: 任传义, 程军勇, 陈振超, 倪张林, 汤富彬
• Format: Journal Article
• Language: Chinese
• Published: Beijing Chinese Academy of Forestry 01.01.2017
• Subjects: Discriminant analysis; Principal components analysis; Trace elements; Variance analysis; China
• ISSN: 1001-1498
• DOI: 10.13275/j.cnki.lykxyj.2017.05.011

[Objective] To identify the walnut from major producing provinces in China and provide some basic data and theoretical basis for the protection of geographical indication.[Method] The contents of 35 elements in 128 walnut samples from eight major producing provinces of China were determined by inductively coupled plasma mass spectrometry (ICP-MS), the discriminant model was established by one-way analysis of variance, principal component analysis (PCA) and linear discriminant analysis (LDA) to identify walnut from different areas.[Result] It was found that the contents of Fe, Zn, Cu and Ni were the most abundant nutrient elements in walnut, and the contents of heavy metal (Pb, Cd and As) and rare earth elements were in relatively low level. One-way analysis of variance indicated that there were significant differences in the elemental composition of walnut samples from different regions (P<.05). The PCA showed that Fe, Ti, Rb, B, Ba, Cu, Zn, Ba, Mo, Al, Pb and rare earth elements were inferred to be the chara