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Comprehensive quality assessment of 296 sweetpotato core germplasm in China: A quantitative and qualitative analysis

文献类型： 外文期刊

作者： Tang, Chaochen 1 ; Xu, Yi 3 ; Zhang, Rong 1 ; Mo, Xueying 1 ; Jiang, Bingzhi 1 ; Wang, Zhangying 1 ;

作者机构： 1.Guangdong Acad Agr Sci, Crops Res Inst, Guangzhou 510640, Peoples R China

2.Key Lab Crop Genet Improvement Guangdong Prov, Guangzhou 510640, Peoples R China

3.China Agr Univ, Coll Agron & Biotechnol, Beijing 100193, Peoples R China

关键词： Sweetpotato germplasm; Quality evaluation; Phenotypic diversity; Near-infrared spectroscopy; Random Forest algorithm; High-throughput screening

期刊名称：FOOD CHEMISTRY-X （ 影响因子：8.2； 五年影响因子：8.2 ）

ISSN： 2590-1575

年卷期： 2024 年 24 卷

页码：

收录情况： SCI

摘要： The potential for improving sweetpotato quality remains underutilized due to a lack of comprehensive quality data on germplasm resources. This study evaluated 296 core germplasms, revealing significant phenotypic diversity across 24 quality traits in both stem tips and roots. Landraces had higher sugar content in roots, while wild relatives showed increased total flavonoid and phenol contents. Accessions with red-orange flesh were rich in sugars and carotenoids, whereas those with purple flesh had higher dry matter, flavonoids, and phenols. The accessions were classified into three clusters: high sugars and carotenoids, high phenolic compounds, and high starch. A comprehensive quality scoring model identified SP286 and SP192 as superior for stem tips and roots, respectively. Near-infrared spectroscopy, combined with a random forest algorithm, enabled rapid screening of superior germplasm, achieving prediction accuracies of 97 % for stem tips and 98 % for roots. These findings offer valuable resources and high-throughput models for enhancing sweetpotato quality.

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