Journal
FOOD QUALITY AND SAFETY
Volume 6, Issue -, Pages -Publisher
OXFORD UNIV PRESS
DOI: 10.1093/fqsafe/fyac052
Keywords
Walnut; chemical marker; geographical origin; Random Forest method; discriminant model
Categories
Funding
- Fundamental Research Funds of Chinese Academy of Forestry (CAF) [CAFYBB2017QC002, CAFYBB2019QD002]
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This study conducted a new method for geographical origin identification of walnuts based on the nutritional quality of walnuts from China. Through analyzing walnut samples from different regions, a discriminant model for geographical origin with a high correct classification rate was established. The study also analyzed the quantitative quality differences of walnuts from different regions and identified important chemical markers for geographical origin discriminant analysis.
Place of origin has an important influence on walnut quality and commercial value, which results in the requirement of rapid geographical traceability method. Thus, a method for geographical origin identification of walnuts on the basis of nutritional quality of walnuts from China was conducted. The concentrations of 43 phytochemical components were analyzed in walnut samples from five different walnut-producing regions of China. Based on 14 chemical markers selected by the Random Forest method from these phytochemical components, a new discriminant model for geographical origin was built, with the corresponding correct classification rate of 99.3%. In addition, the quantitative quality differences of walnuts from five regions were analyzed, with values of 0.17-1.43. Moreover, the top three chemical markers for the geographical origin discriminant analysis were Mo, V, and stearic acid, with contribution rates of 26.8%, 18.9%, and 10.9%, respectively. This study provides a potentially viable method for application in food authentication.
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