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基于含硫化合物,辅以稳定同位素和生物元素对中国大蒜进行化学计量生源分类。

Chemometric origin classification of Chinese garlic using sulfur-containing compounds, assisted by stable isotopes and bioelements.

机构信息

State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Hangzhou 310021, China; Institute of Agro-Products Safety and Nutrition, Zhejiang Academy of Agricultural Sciences, Key Laboratory of Information Traceability for Agricultural Products, Ministry of Agriculture and Rural Affairs of China, Hangzhou 310021, China.

Institute of Quality Standard and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Key Laboratory of Agri-food Quality and Safety, Ministry of Agriculture and Rural Affairs, Beijing 100081, China.

出版信息

Food Chem. 2022 Nov 15;394:133557. doi: 10.1016/j.foodchem.2022.133557. Epub 2022 Jun 22.

Abstract

Geographical origin discrimination of agro-products is essential to guarantee food safety and fair trade. Garlic samples cultivated in six provinces or major production regions in China were characterized for stable isotopes (δC, δH, δO, δN, and δS), bioelemental contents (% C, % N and % S), and sulfur-containing compounds (8 organosulfur components and 2 amino acids). Results showed that many of the 18 analyzed garlic variables had significant differences among production regions. Some sulfur-containing compounds found in garlic from different provinces had a strong correlation with sulfur isotopes, suggesting garlic sulfur isotopes were also affected by geographical origin. Two supervised pattern recognition models (PLS-DA and k-NN) were developed using stable isotopes, elemental contents, and sulfur-containing compounds, and had a discrimination accuracy of 93.4 % and 87.8 %, respectively. Chemometric classification models using multi-isotopes, elements and sulfur-containing compounds provides a useful method to authenticate Chinese garlic origins.

摘要

农产品的地理来源鉴别对于保证食品安全和公平贸易至关重要。本研究对中国 6 个省份或主要生产地区种植的大蒜样本进行了稳定同位素(δC、δH、δO、δN 和 δS)、生物元素含量(% C、% N 和% S)和含硫化合物(8 种有机硫成分和 2 种氨基酸)分析。结果表明,18 种分析的大蒜变量在生产地区之间存在显著差异。不同省份大蒜中的一些含硫化合物与硫同位素具有很强的相关性,表明大蒜的硫同位素也受到地理来源的影响。使用稳定同位素、元素和含硫化合物分别建立了两种有监督的模式识别模型(PLS-DA 和 k-NN),其判别准确率分别为 93.4%和 87.8%。使用多同位素、元素和含硫化合物的化学计量分类模型为鉴别中国大蒜产地提供了一种有用的方法。

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