Green analytical assay for the viability assessment of single maize seeds using double-threshold strategy for catalase activity and malondialdehyde content
文献类型： 外文期刊
作者： An, Ting 1 ; Fan, Yaoyao 1 ; Tian, Xi 1 ; Wang, Qingyan 1 ; Wang, Zheli 1 ; Fan, Shuxiang 1 ; Huang, Wenqian 1 ;
作者机构： 1.Beijing Acad Agr & Forestry Sci, Intelligent Equipment Res Ctr, Beijing 100097, Peoples R China
2.Southwest Univ, Coll Engn & Technol, Chongqing 400715, Peoples R China
关键词： Hyperspectral imaging; CAT activity; MDA content; Data fusion; Seed viability
期刊名称：FOOD CHEMISTRY （ 影响因子：8.5； 五年影响因子：8.2 ）
ISSN： 0308-8146
年卷期： 2024 年 455 卷
页码：
收录情况： SCI
摘要： The development of nondestructive technology for the detection of seed viability is challenging. In this study, to establish a green and effective method for the viability assessment of single maize seeds, a two-stage seed viability detection method was proposed. The catalase (CAT) activity and malondialdehyde (MDA) content were selected as the most key biochemical components affecting maize seed viability, and regression prediction models were developed based on their hyperspectral information and a data fusion strategy. Qualitative discrimination models for seed viability evaluation were constructed based on the predicted response values of the selected key biochemical components. The results showed that the double components thresholds strategy achieved the highest discrimination accuracy (92.9%), providing a crucial approach for the rapid and environmentally friendly detection of seed viability.
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