Geographical origin of Chinese apples based on multiple element analysis

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Abstract
BACKGROUND: Apples from different regions of China show different qualities and internal characteristics, and appeal to different customers. However, these aspects have not been studied in depth. We characterized the profiles of 14 elements in 317 apple samples collected from five regions of China. Principal component analysis (PCA), linear discriminant analysis (LDA), and back‐propagation artificial neural networks analysis (BP‐ANN) were used to build models for apple authentication.RESULTS: Fourteen elements were successfully identified in apple samples by performing graphite furnace atomic absorption spectrometry (GFAAS) and inductively coupled plasma atomic emission spectroscopy (ICP‐AES) analyses. Comparative analysis showed significantly different element profiles in samples from different regions. The first five principal components obtained by PCA accounted for 71.8% of the total variance. The LDA obtained 70.0% classification rates. The BP‐ANN obtained 82.7% classification rates.CONCLUSION: This study indicated the possibility that apples could be authenticated based on differences in their element profiles, and provided a basis for further geographical origin studies. © 2019 Society of Chemical Industry
Funding Information
  • Earmarked Fund for the China Agriculture Research System (CARS-27)
  • Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences (CAAS-ASTIP)
  • National Program for Quality and Safety Risk Assessment of Agricultural Products of China (GJFP2018003, GJFP2017003)

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