AI Article Synopsis
- - This study focused on enhancing the traceability of rice-producing areas to meet the growing need for reliable food quality and safety verification methods.
- - Researchers measured specific carbon isotopes in fatty acids, starch, and bulk rice, using PCA, PLS-DA, and VIP value analysis to differentiate rice from six different regions.
- - The results showed that the δC values of starch, along with certain fatty acids, were particularly effective in identifying rice origins, with starch δC being the most significant factor for improving traceability precision.
Article Abstract
This study aimed to improve the traceability of rice-producing areas to address the increasing demand for accurate methods to confirm food quality and safety. Compound-specific δC of fatty acids, δC of starch and bulk of rice were measured. PCA, PLS-DA and VIP value analysis of the obtained data were performed to track the source of rice from the six regions. The PLS-DA model established with bulk δC, starch δC, and fatty acid δC, which clearly separated the rice from six regions. The VIP graph showed the value of starch, C18:0 and C18:2 δC values (VIP > 1) were important to distinguish the origin of rice. Also, according to loading plots the contribution of starch δC was the largest. The findings indicate that the introduction of starch δC improves the precision of rice traceability and provides an effective method for identifying rice origin.
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| http://dx.doi.org/10.1016/j.foodchem.2024.139819 | DOI Listing |
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