Preliminary study on the geographical origin of Chinese 'Cuiguan' pears using integrated stable isotope and multi-element analyses
Tingting Zeng,
Tingting Fu,
Yongchuan Huang,
Wei Zhang,
Jiuping Gong,
Bingjing Ji,
Xiaoxia Yang,
Mingfeng Tang
Affiliations
Tingting Zeng
Institute of Agricultural Quality Standard and Testing Technology, Chongqing Academy of Agricultural Sciences, Chongqing 401329, People's Republic of China; Agricultural Product Quality and Safety Supervision, Inspection and Testing Center, Ministry of Agriculture and Rural Affairs, Chongqing, People's Republic of China
Tingting Fu
Institute of Agricultural Quality Standard and Testing Technology, Chongqing Academy of Agricultural Sciences, Chongqing 401329, People's Republic of China; Agricultural Product Quality and Safety Supervision, Inspection and Testing Center, Ministry of Agriculture and Rural Affairs, Chongqing, People's Republic of China
Yongchuan Huang
Institute of Agricultural Quality Standard and Testing Technology, Chongqing Academy of Agricultural Sciences, Chongqing 401329, People's Republic of China; Agricultural Product Quality and Safety Supervision, Inspection and Testing Center, Ministry of Agriculture and Rural Affairs, Chongqing, People's Republic of China
Wei Zhang
Institute of Agricultural Quality Standard and Testing Technology, Chongqing Academy of Agricultural Sciences, Chongqing 401329, People's Republic of China; Agricultural Product Quality and Safety Supervision, Inspection and Testing Center, Ministry of Agriculture and Rural Affairs, Chongqing, People's Republic of China
Jiuping Gong
Institute of Agricultural Quality Standard and Testing Technology, Chongqing Academy of Agricultural Sciences, Chongqing 401329, People's Republic of China; Agricultural Product Quality and Safety Supervision, Inspection and Testing Center, Ministry of Agriculture and Rural Affairs, Chongqing, People's Republic of China
Bingjing Ji
Institute of Agricultural Quality Standard and Testing Technology, Chongqing Academy of Agricultural Sciences, Chongqing 401329, People's Republic of China; Agricultural Product Quality and Safety Supervision, Inspection and Testing Center, Ministry of Agriculture and Rural Affairs, Chongqing, People's Republic of China
Xiaoxia Yang
Institute of Agricultural Quality Standard and Testing Technology, Chongqing Academy of Agricultural Sciences, Chongqing 401329, People's Republic of China; Agricultural Product Quality and Safety Supervision, Inspection and Testing Center, Ministry of Agriculture and Rural Affairs, Chongqing, People's Republic of China
Mingfeng Tang
Institute of Agricultural Quality Standard and Testing Technology, Chongqing Academy of Agricultural Sciences, Chongqing 401329, People's Republic of China; Agricultural Product Quality and Safety Supervision, Inspection and Testing Center, Ministry of Agriculture and Rural Affairs, Chongqing, People's Republic of China; Corresponding author. Institute of Agricultural Quality Standard and Testing Technology, Chongqing Academy of Agricultural Sciences, Chongqing 401329, People's Republic of China.
Distinguish the geographical origin of the pear is important due to the increasingly valued brand protection and reducing the potential food safety risks. In this study, the profiles of stable isotopes (δ13C, δ15N, δ2H, δ18O) and the contents of 16 elements in pear peer from four production areas were analyzed. The δ13C, δ15N, δ2H, δ18O and 12 elements were significantly different (p < 0.05) in the four production areas. Chemometrics analysis including principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and linear discriminant analysis (LDA) were exploited for geographical origin classification of samples. OPLS-DA analysis showed that crucial variables (δ13C, δ18O, δ2H, Ni, Cd, Ca, δ15N, Sr and Ga) are more relevant for the discrimination of the samples. OPLS-DA achieved pear origin accuracy rates of 87.76 % by combining stable isotope ratios and elemental contents. LDA had a higher accuracy rate than OPLS-DA, and the LDA analysis showed that the original discrimination rate reached to 100 %, while the cross-validated rate reached to 95.7 %. These studies indicated that this method could be used to assess the geographical discrimination of pear from different producing areas and could potentially control the fair trade of pear in fruit markets.