期刊
JOURNAL OF FOOD COMPOSITION AND ANALYSIS
卷 92, 期 -, 页码 -出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jfca.2020.103577
关键词
PGI jujube; Food composition analysis; OPLS-DA modeling; Food safety; Food integrity
资金
- Tianshan Engineering Training Project, Xinjiang Uygur Autonomous Region
- Xinjiang Uygur Autonomous Region Tianshan Cedar Plan [2017XS07]
- High-tech Research and Development Program of Science and Technology Department of Xinjiang Uygur Autonomous Region [201517106]
- Key Laboratory of Xinjiang Uygur Autonomous Region [2015KL023, 2019D04013]
- Xinjiang Academy of Agricultural Sciences [XJZDY-001]
- Agricultural Science and Technology Innovation Platform Project from Xinjiang Academy of Agricultural Sciences [XJNKYPT-2017-003]
- State Key Laboratory for Quality and Safety of Agro-products [2010DS700124-ZZ1908]
Jujube is widely grown in Xinjiang province, China, including two high-value PGI products, Charkhlik Hui jujube and Khotan Jun jujube. Origin mislabeling and substitution of PGI jujube by inferior products seriously harms their reputation and has potential food safety risks. In this study, stable isotope (delta C-13, delta N-15, delta H-2, delta O-18) and elemental (Na, Mg, Al, P, K, Ca, Ti, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Sr, Mo, Cd, Sb, Ba, Pb) compositions of jujube from five different regions across Xinjiang province were analyzed by orthogonal partial least squares-discriminant analysis (OPLS-DA) to verify the geographical origin of jujube and authenticate PGI products. A total of 167 Hui jujube and 156 Jun jujube samples, together with their associated soils were collected annually from 2013 to 2018. The regional, varietal and inter-annual differences of stable isotope and elemental compositions of jujube and their correlation with soil values were analyzed using one-way ANOVA and multivariate statistics. The discriminant accuracies of OPLS-DA modeling for both Hui and Jun jujube samples collected in 2016 were higher than 90 %. Over a longer five-year (from 2013 to 2018), the discriminant accuracies decreased slightly, but were still acceptable at 85 % and 75 % for the two varieties. The most important variables for discrimination models were Na, Al, Ba, and delta C-13 for Hui jujube, delta O-18 and delta N-15 for Jun jujube, respectively. The study show that this strategy holds good promise as a tool to combat mislabeling and fraudulent conduct and has the ability to protect PGI jujube produced in Xinjiang province.
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