Affiliation:
1. State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro‐Products Zhejiang Academy of Agricultural Sciences Hangzhou China
2. Institute of Agro‐Product Safety and Nutrition Zhejiang Academy of Agricultural Sciences Hangzhou China
3. Key Laboratory of Information Traceability for Agricultural Products Ministry of Agriculture and Rural Affairs of China Hangzhou China
4. National Isotope Centre, GNS Science Lower Hutt New Zealand
5. Institute of Digital Agriculture Zhejiang Academy of Agricultural Sciences Hangzhou China
6. Laboratory of Quality and Safety Risk Assessment for Tropical Products, Analysis and Test Centre, Chinese Academy of Tropical Agricultural Sciences Ministry of Agriculture Haikou China
Abstract
AbstractVerification of cowpea geographical origin has become more critical in recent times to guarantee food safety and enhance government management of potentially hazardous pesticide farming practices. Cowpea samples harvested in five major southern provinces in China were characterized by stable isotopes (δ13C, δ15N, δ2H, δ18O) and elemental contents (Ca, K, Mg, Na, P, Cu, Fe, Mn, Ni, Zn, Mo, C, N) using inductively coupled plasma mass spectrometry. A combined isotope and elemental approach reflected regional elemental differences from China's eastern seaboard that are uptaken by cowpea from the environment. Results showed that many of the isotope and elemental variables differed significantly among production regions, with Cu, Zn, δ18O, P, K, δ13C, Mo, Ca, and Mg identified as the most important classification variables of projection (VIP > 1). Stable isotopes and elemental contents were representative of regional and local climate, soil geology, and fertilization practices, respectively. The cowpea elemental contents analyzed in this study were all within the expected guideline range for Asian vegetables and posed no health concerns to consumers. Two regional models and one local model based on supervised pattern recognition method of Partial Least Squares‐Discriminant Analysis (PLS‐DA) were developed, and the overall discrimination accuracies ranged from 78.0% to 99.2%. These chemometric models provide a useful method to verify Chinese cowpea origins and improve food safety controls for consumers.