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Profiling the ionome of rice and its use in discriminating geographical origins at the regional scale, China

Journal of Environmental Sciences 2013年第1期25卷 144-154页

作者： Gang Li Luis Nunes Yijie Wang Paul N. Williams Maozhong Zheng Qiufang Zhang Yongguan Zhu Key Laboratory of Urban Environment and Health Institute of Urban EnvironmentChinese Academy of Sciences Geosystems Center University of Algarve Lancaster Environment Centre Lancaster University Research Center for Eco-Environmental Sciences Chinese Academy of Sciences

Element profile was investigated for their use to trace the geographical origin of rice （Oryza sativa L.） samples. The concentrations of 13 elements （calcium （Ca）, potassium （K）, magnesium （Mg）, phosphorus （P）, boron （B）, manganese （Mn）, iron （Fe）, nickel （Ni）, copper （Cu）, arsenic （As）, selenium （Se）, molybdenum （Mo）, and cadmium （Cd）） were determined in the rice samples by inductively coupled plasma optical emission and mass spectrometry. Most of the essential elements for human health in rice were within normal ranges except for Mo and Se. Mo concentrations were twice as high as those in rice from Vietnam and Spain. Meanwhile, Se concentrations were three times lower in the whole province compared to the Chinese average level of 0.088 mg/kg. About 12% of the rice samples failed the Chinese national food safety standard of 0.2 mg/kg for Cd. Combined with the multi-elemental profile in rice, the principal component analysis （PCA）, discriminant function analysis （DFA） and fibonacci index analysis （FIA） were applied to discriminate geographical origins of the samples. Results indicated that the FIA method could achieve a more effective geographical origin classification compared with PCA and DFA, due to its efficiency in making the grouping even when the elemental variability was so high that PCA and DFA showed little discriminatory power. Furthermore, some elements were identified as the most powerful indicators of geographical origin： Ca, Ni, Fe and Cd. This suggests that the newly established methodology of FIA based on the ionome profile can be applied to determine the geographical origin of rice.

关键词： ionome rice grain geographical origin principal component analysis fibonacci index analysis

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