| Diversity analysis and comprehensive evaluation of agronomic traits and quality of foxtail millet germplasm resources |
|
View Fulltext View/Add Comment Download reader |
| |
| DOI：10.7606/j.issn.1000-7601.2025.05.01 |
| Key Words: foxtail millet germplasm resources agronomic traits quality diversity analysis comprehensive evaluation |
| Author Name | Affiliation | | REN Ruiyu | Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China | | LI Yawei | Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China | | DONG Kongjun | Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China | | HE Jihong | Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China | | LIU Tianpeng | Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China | | ZHANG Lei | Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China | | YANG Tianyu | Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China |
|
| Hits: 822 |
| Download times: 295 |
| Abstract: |
| In order to explore the excellent germplasm resources of foxtail millet, 126 foxtail millet germplasm accessions were selected from national and provincial resource banks and relevant domestic institutions. A two\|year agronomic trait investigation was conducted, and 100 accessions were selected for nutritional quality analysis. Various analytical methods were employed for research and comprehensive evaluation. The results showed that, in terms of agronomic traits, there was abundant variation among the millet germplasm accessions. The coefficient of variation for 16 traits ranged from 9.30% to 66.66%. The variation of main stem height was the smallest and the variation of seedling color was the largest. Correlation analysis revealed significant positive correlations between straw per plant mass and various factors such as spike mass per plant, community production, grain mass per plant (P<0.05). Cluster analysis divided the materials into five major groups, each with distinct characteristics. Group I was characterized by tall plants and large panicles, which could be used for screening forage millet. Group II, with the shortest peduncle, could be employed for selecting short\|statured millet suitable for mechanical harvesting. Group III had the lowest average main stem height and the highest average spike mass per plant, grain mass per plant, and community production, making it suitable for selecting short yet high\|yielding millet. Group IV had the largest thousand\|seed weight, ideal for grain breeding materials. Principal component analysis divided quantitative traits into four principal components, with a cumulative contribution rate of 77.493%. According to the comprehensive score (F value) calculated by the weight of contribution rates of each trait,the top 10 excellent materials, such as ‘60\|day hongjiugu’ and ‘Huangjiugu’, were selected. In the quality analysis, the coefficients of variation for the trace elements Fe and Se were relatively large, at 44.97% and 70.00%, respectively. There was a significant positive correlation between total starch content and amylopectin content (r=0.83), while starch content and crude protein content exhibited a negative correlation (r=-0.98). Principal component analysis divided nutritional quality into three principal components, with a cumulative contribution rate of 72.559%. A functional expression was constructed to comprehensively evaluate nutritional quality, and 10 resources, including ‘Jinuogu No.1’ with the highest score, could be used as excellent breeding materials. |
|
|
|