Rapid identification of fragrant rice using starch flavor compound via NIR spectroscopy coupled with GC-MS and Badh2 genotyping

文献类型： 外文期刊

第一作者： Xie, Li-Hong

作者： Xie, Li-Hong;Shao, Gao-Neng;Sheng, Zhong-Hua;Hu, Shi-Kai;Wei, Xiang-Jin;Jiao, Gui-Ai;Tang, Shao-Qing;Hu, Pei-Song

作者机构：

期刊名称：INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES （ 影响因子：8.5； 五年影响因子：8.7 ）

ISSN： 0141-8130

年卷期： 2024 年 281 卷

页码：

收录情况： SCI

摘要： The identification of fragrant rice varieties using near-infrared reflectance spectroscopy (NIRS) models has attracted extensive attention from regulatory authorities worldwide. In this study, 138 fragrant and 54 nonfragrant rice varieties were planted in the same region and distinguished using sensory evaluation, gas chromatography-mass spectrometry analysis, and betaine aldehyde dehydrogenase 2 ( Badh2 ) genotyping. Then, the 2-acetyl-1-pyrroline (2-AP) content was assessed based on partial least-squares discriminant (PLS-DA) models generated after 2nd individually or combined with SNV/MSC/smoothing preprocessing successfully classified fragrant rice both in the calibration and predictive sets. Moreover, design of experiments (DoE)-based preprocessing selection was employed as an effective strategy to optimize the calibration models compared with the one variable at a time (OVAT) method. Further, Badh2 genotype sample screening assisted with identifying authentic fragrant rice and guaranteed the NIRS model's prediction accuracy in identifying fragrant rice. In conclusion, the high throughput PLS-DA multivariate method coupled with NIRS data was applied to identify fragrant rice varieties in routine monitoring and was effective, accurate, and rapid.

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