文献类型： 外文期刊
作者： Wadood, Syed Abdul 1 ; Li, Chunlin 1 ; Nie, Jing 1 ; Rogers, Karyne M. 2 ; Mei, Hanyi 1 ; Zhang, Yongzhi 1 ; Shah, ImranUllah 3 ; Qamar, Aiza 3 ; Yuan, Yuwei 1 ;
作者机构： 1.Zhejiang Acad Agr Sci, Inst Agroprod Safety & Nutr, State Key Lab Managing Biot & Chem Threats Qual &, Hangzhou 310021, Peoples R China
2.Zhejiang Acad Agr Sci, Inst Agroprod Safety & Nutr, Key Lab Informat Traceabil Agr Prod, Minist Agr & Rural Affairs China, Hangzhou 310021, Peoples R China
3.Univ Home Econ, Dept Nutr & Hlth Promot, Lahore, Pakistan
4.Natl Isotope Ctr, GNS Sci, 30 Gracefield Rd, Lower Hutt 5040, New Zealand
关键词： Basmati rice; Cultivar authenticity; Stable isotopes; IRMS; Geographical origin; Fraud; Traceability; Pakistan
期刊名称：FOOD CONTROL （ 影响因子：6.0； 五年影响因子：5.8 ）
ISSN： 0956-7135
年卷期： 2024 年 157 卷
页码：
收录情况： SCI
摘要： Basmati rice is a popular, high-value aromatic rice which is an easy target for fraudulent activities such as mislabeling and substitution with non-basmati cultivars. Bulk isotope ratio mass spectrometry (IRMS) combined with multivariate analysis was employed to develop a model to identify the geographical origin of rice and authenticate different rice cultivars from Pakistan. ANOVA showed significant statistical differences for 313C, 315N, 32H and 318O isotopes amongst different basmati and non-basmati rice cultivars. 32H and 318O values showed a larger variation between basmati and non-basmati rice cultivars. Multivariate ANOVA showed a significant influence on rice from different regions, cultivars and their stable isotopic values. Regional effects contributed the highest variation for both 313C and 315N isotopes (56.6 % and 42.7 %), whereas cultivar type largely contributed to differences in 32H and 318O values. Finally, supervised classification models (LDA and PLS-DA) were constructed to assess origin classification ability. The PLS-DA model achieved a higher origin classification accuracy in both training and validation sets (76.7 % and 70.0 %, respectively). In conclusion, isotopic fingerprints along with multivariate statistical analysis showed good potential to characterize rice according to cultivar type and production region. This study provides valuable insights to authenticate Pakistan basmati rice from other non-basmati cultivars, and will be instrumental in developing new tools for industry and regulatory agencies to control fraudulent labeling of basmati rice.
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