Chung Ill-Min, Kim Jae-Kwang, Prabakaran Mayakrishnan, Yang Jin-Hee, Kim Seung-Hyun
Department of Applied Bioscience, College of Life and Environmental Science, Konkuk University, Seoul, 143-701, Republic of Korea.
Division of Life Sciences, College of Life Sciences and Bioengineering, Incheon National University, Incheon, 406-772, Republic of Korea.
J Sci Food Agric. 2016 May;96(7):2433-9. doi: 10.1002/jsfa.7363. Epub 2015 Sep 21.
Although rice (Oryza sativa L.) is the third largest food crop, relatively fewer studies have been reported on rice geographical origin based on light element isotope ratios in comparison with other foods such as wine, beef, juice, oil and milk. Therefore this study tries to discriminate the geographical origin of the same rice cultivars grown in different Asian countries using the analysis of C, N, O and S stable isotope ratios and chemometrics.
The δ(15) NAIR , δ(18) OVSMOW and δ(34) SVCDT values of brown rice were more markedly influenced by geographical origin than was the δ(13) CVPDB value. In particular, the combination of δ(18) OVSMOW and δ(34) SVCDT more efficiently discriminated rice geographical origin than did the remaining combinations. Principal component analysis (PCA) revealed a clear discrimination between different rice geographical origins but not between rice genotypes. In particular, the first components of PCA discriminated rice cultivated in the Philippines from rice cultivated in China and Korea.
The present findings suggest that analysis of the light element isotope composition combined with chemometrics can be potentially applicable to discriminate rice geographical origin and also may provide a valuable insight into the control of improper or fraudulent labeling regarding the geographical origin of rice worldwide. © 2015 Society of Chemical Industry.
尽管水稻(Oryza sativa L.)是第三大粮食作物,但与葡萄酒、牛肉、果汁、油类和牛奶等其他食品相比,基于轻元素同位素比率对水稻地理起源的研究报道相对较少。因此,本研究试图通过分析碳、氮、氧和硫稳定同位素比率及化学计量学方法来鉴别在不同亚洲国家种植的同一水稻品种的地理起源。
糙米的δ(15)NAIR、δ(18)OVSMOW和δ(34)SVCDT值受地理起源的影响比δ(13)CVPDB值更显著。特别是,δ(18)OVSMOW和δ(34)SVCDT的组合比其他组合更有效地鉴别了水稻的地理起源。主成分分析(PCA)显示不同水稻地理起源之间有明显区分,但水稻基因型之间没有。特别是,PCA的第一成分区分了菲律宾种植的水稻与中国和韩国种植的水稻。
目前的研究结果表明,轻元素同位素组成分析结合化学计量学方法可能适用于鉴别水稻的地理起源,也可能为全球范围内控制水稻地理起源的不当或欺诈性标签提供有价值的见解。© 2015化学工业协会。