文献类型： 外文期刊
作者： Zhang, Jianyi 1 ; Nie, Jiyun 2 ; Zhang, Liangbin 3 ; Xu, Guofeng 1 ; Zheng, Haidong 1 ; Shen, Youming 1 ; Kuang, Lixue 1 ;
作者机构： 1.Chinese Acad Agr Sci, Qual Inspect & Test Ctr Fruit & Nursery Stocks, Res Inst Pomol, Lab Qual & Safety Risk Assessment Fruit,Minist Ag, Xingcheng, Peoples R China
2.Qingdao Agr Univ, Coll Hort, Qingdao Key Lab Modern Agr Qual & Safety Engn, Qingdao 266109, Peoples R China
3.Baotou Acad Agr & Anim Husb Sci, Inner Mongolia Acad Agr & Anim Husb Sci, Baotou, Peoples R China
关键词： Malus domestica; mineral elements; geographical verification; linear and nonlinear discriminant analysis; random forest analysis
期刊名称：JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE （ 影响因子：3.639； 五年影响因子：3.803 ）
ISSN： 0022-5142
年卷期： 2022 年 102 卷 1 期
页码：
收录情况： SCI
摘要： BACKGROUND Half of all apple production worldwide comes from China. However, the geographic authentication of Chinese apples has not been well studied. We highlight the multi-element-based geographical discrimination of apples from the southwest cold highlands (SCH) of China. 565 samples from the SCH (138) and others (427) were obtained, and the content of fifteen elements were applied to construct models for discrimination. RESULTS The SCH apples from 2017 to 2019 had higher concentrations of Mn, Zn, Cr, Cd, Se, Pb, and Fe, but lower concentrations of Na, B, Ni, and P. With sufficient training, linear discriminant analysis (LDA) discriminated the SCH, and the testing accuracy averaged 92.5% and 92.2%. Nonlinear discrimination models were more suitable than the linear models. Optimized random forest analysis was the model with the best fit, and with averaged training and testing it obtained a level of accuracy of 98.2% and 98.5%. CONCLUSION The multielement-based discrimination of SCH apples could aid further studies of geographical origins. (c) 2021 Society of Chemical Industry.
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