ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Plant Breeding
Volume 16 - 2025 | doi: 10.3389/fpls.2025.1670684
Genetic diversity analysis of phenotypic and agronomic traits in oat germplasm resources
Provisionally accepted
Zhao Yan1Fang Jiaqi2
René Gislum3Zhao Baowen2Zhong Zhiming4Lei Yingxia2Yan Donghai5He Ruzhi6
Chen Youjun2
Qingping Zhou2
Hui Wang2*- 1Other
- 2Southwest Minzu University, Chengdu, China
- 3Aarhus Universitet, Aarhus, Denmark
- 4Chinese Academy of Sciences, Beijing, China
- 5Grassland Technology Research and Extension Center of Sichuan Province, Chengdu, China
- 6Gansu PRT Gricultural Science and Technology Co., Ltd., Zhangye, China
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The evaluation of genetic diversity in germplasm resources is fundamental to crop breeding. A total of 183 oat germplasm resources were evaluated through field trials at Xinjin District and Shandan County, located in southern and northern China, respectively. Phenotypic and agronomic traits were assessed, including six qualitative and sixteen quantitative characteristics. Results revealed significant variation in two qualitative traits, panicle attitude and grain color, based on the basic statistical analysis using SPSS. Among the sixteen quantitative traits, coefficient of variation ranged from 4.92% to 48.02% with the second internode thickness exhibiting the highest genetic diversity index. Correlation analysis of sixteen quantitative traits was performed using R Studio, and the results indicated significant positive relationships between grain weight and several ear characteristics, including spikelet number, ear length, layer numbers, and grain numbers per ear. Principal component analysis categorized the sixteen quantitative phenotypic traits into five independent factors. The structural equation modeling using SPSS-AMOS indicated that ear characteristics showed strong direct contributions to grain weight, establishing it as a key indicator for future breeding efforts. The multiple correspondence analysis by R Studio suggested that a total of nineteen oat germplasm resources showed the grain and biomass production potential across both experimental regions.
Keywords: Avena sativa, Resource evaluation, Principal Component Analysis, Structural Equation Modeling, quantitative trait
Received: 22 Jul 2025; Accepted: 14 Aug 2025.
Copyright: © 2025 Yan, Jiaqi, Gislum, Baowen, Zhiming, Yingxia, Donghai, Ruzhi, Youjun, Zhou and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Hui Wang, Southwest Minzu University, Chengdu, China
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