Xiangwei Hu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Xiangwei Hu has a total of 11 co-authors. Here are the top co-authors by number of shared publications:
- Hui Wang
Crop Research Institute of Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi 830002, China
2 shared publications - Jun Liu
Crop Research Institute, Academy of Agricultural Sciences of Xinjiang Uyghur Autonomous Region, Urumqi 830091, China
2 shared publications - Zaituniguli Kuerban
Crop Research Institute of Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi 830002, China
2 shared publications - Baiyi Yang
Crop Research Institute of Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi 830002, China
1 shared publication - Guojun Feng
Crop Research Institute of Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi 830002, China
1 shared publication - Guojun Feng
Institute of Crop, Xinjiang Academy of Agricultural Sciences, Urumuqi, China.
1 shared publication
Latest Publications
- Open Access
Phenotypic Diversity Analysis and Comprehensive Evaluation of Foxtail Millet Germplasm Resources Evaluated in Northern Xinjiang
Foxtail millet (Setaria italica L.) is an important functional food crop with high photosynthetic efficiency and drought tolerance, and it plays a significant role in arid and semi-arid agricultural systems. However, germplasm resources from Xinjiang remain inadequately characterized, limiting their use in breeding programs. This study systematically evaluated 203 foxtail millet germplasm accessions using 8 qualitative traits and 13 quantitative traits across two growing seasons (2023–2024) in northern Xinjiang. Phenotypic variation and diversity, trait correlations, and phenotypic grouping were analyzed using the Shannon–Weaver diversity index (H′ = −Σ pi ln pi), coefficient of variation (CV), Pearson correlation, principal component analysis (PCA), and hierarchical cluster analysis. Among qualitative traits, leaf posture during flowering exhibited the highest phenotypic diversity index (H′ = 1.072), whereas leaf sheath color showed the lowest (H′ = 0.359). Predominant phenotypes included green seedling leaf color (77.83%), semi-erect seedling leaf posture (57.14%), drooping leaf posture during flowering (50.74%), curved panicle neck (74.88%), spindle-shaped panicle (83.25%), and yellow grain color (84.73%). Among quantitative traits, grain weight per panicle (GWE; CV = 38.91%), single panicle weight (SEW; CV = 37.65%), and yield (CV = 37.31%) showed the highest variability. Yield was strongly and positively correlated with SEW (r = 0.925, p < 0.001) and GWE (r = 0.925, p < 0.001), and SEW and GWE were almost collinear (r = 0.996). PCA of 12 standardized traits (SEW excluded to avoid redundancy with GWE) extracted five components explaining 65.55% of total phenotypic variation. Hierarchical clustering of the unstandardized trait means (yield in kg·mu−1), in which yield contributed most strongly to group separation, divided the accessions into four groups: Group I (129 accessions, 63.55%) was intermediate (mean yield 3532 kg·ha−1); Group II (37 accessions, 18.23%) had the lowest yield (1650 kg·ha−1) and panicle weights; Group III (32 accessions, 15.76%) had high yield (5282 kg·ha−1); and Group IV (5 accessions, 2.46%), all breeding lines, had the highest yield (6814 kg·ha−1), the heaviest panicles, and the thickest stems. The evaluated foxtail millet germplasm showed substantial phenotypic diversity under irrigated conditions at a single site, providing candidate materials for yield improvement and for further evaluation of stress resistance and adaptation. Group III and Group IV accessions are candidate parents for high-yield breeding; however, this requires validation in multi-location trials because only one irrigated site was evaluated and lodging and drought responses were not measured. Entry-mean repeatability of accession means across the two seasons ranged from 72.1% to 99.99%, and these values are likely upper bounds because genotype × year interaction could not be separated from residual error. These findings provide a phenotypic baseline for germplasm utilization in Xinjiang foxtail millet improvement programs.
Open AccessPhenotypic Diversity Analysis and Comprehensive Evaluation of Foxtail Millet Germplasm Resources Evaluated in Northern Xinjiang
Foxtail millet (Setaria italica L.) is an important functional food crop with high photosynthetic efficiency and drought tolerance, and it plays a significant role in arid and semi-arid agricultural systems. However, germplasm resources from Xinjiang remain inadequately characterized, limiting their use in breeding programs. This study systematically evaluated 203 foxtail millet germplasm accessions using 8 qualitative traits and 13 quantitative traits across two growing seasons (2023–2024) in northern Xinjiang. Phenotypic variation and diversity, trait correlations, and phenotypic grouping were analyzed using the Shannon–Weaver diversity index (H′ = −Σ pi ln pi), coefficient of variation (CV), Pearson correlation, principal component analysis (PCA), and hierarchical cluster analysis. Among qualitative traits, leaf posture during flowering exhibited the highest phenotypic diversity index (H′ = 1.072), whereas leaf sheath color showed the lowest (H′ = 0.359). Predominant phenotypes included green seedling leaf color (77.83%), semi-erect seedling leaf posture (57.14%), drooping leaf posture during flowering (50.74%), curved panicle neck (74.88%), spindle-shaped panicle (83.25%), and yellow grain color (84.73%). Among quantitative traits, grain weight per panicle (GWE; CV = 38.91%), single panicle weight (SEW; CV = 37.65%), and yield (CV = 37.31%) showed the highest variability. Yield was strongly and positively correlated with SEW (r = 0.925, p < 0.001) and GWE (r = 0.925, p < 0.001), and SEW and GWE were almost collinear (r = 0.996). PCA of 12 standardized traits (SEW excluded to avoid redundancy with GWE) extracted five components explaining 65.55% of total phenotypic variation. Hierarchical clustering of the unstandardized trait means (yield in kg·mu−1), in which yield contributed most strongly to group separation, divided the accessions into four groups: Group I (129 accessions, 63.55%) was intermediate (mean yield 3532 kg·ha−1); Group II (37 accessions, 18.23%) had the lowest yield (1650 kg·ha−1) and panicle weights; Group III (32 accessions, 15.76%) had high yield (5282 kg·ha−1); and Group IV (5 accessions, 2.46%), all breeding lines, had the highest yield (6814 kg·ha−1), the heaviest panicles, and the thickest stems. The evaluated foxtail millet germplasm showed substantial phenotypic diversity under irrigated conditions at a single site, providing candidate materials for yield improvement and for further evaluation of stress resistance and adaptation. Group III and Group IV accessions are candidate parents for high-yield breeding; however, this requires validation in multi-location trials because only one irrigated site was evaluated and lodging and drought responses were not measured. Entry-mean repeatability of accession means across the two seasons ranged from 72.1% to 99.99%, and these values are likely upper bounds because genotype × year interaction could not be separated from residual error. These findings provide a phenotypic baseline for germplasm utilization in Xinjiang foxtail millet improvement programs.
- Open Access
Drought Tolerance Evaluation and Classification of Foxtail Millet Core Germplasms Using Comprehensive Tolerance Indices
Drought stress critically constrains agricultural productivity in arid and semi-arid regions, necessitating the development of drought-tolerant crop varieties for sustainable food security. This study evaluated drought tolerance in 222 foxtail millet (Setaria italica) germplasms from diverse Chinese agroecological zones from 2021–2023 at a specialized identification site in Xinjiang. Field experiments used a randomized complete block design comparing normal irrigation (3000 m3/ha) with drought stress (1800 m3/ha) across 12 morpho-agronomic traits including plant height, spike characteristics, biomass, and yield components. Drought stress significantly reduced all parameters, with yield exhibiting the highest sensitivity (drought tolerance coefficient = 0.58). Principal component analysis indicated that the first three components explained 82.70% of phenotypic variance, with yield-related parameters contributing the most to genotypic differentiation. Integrated evaluation using comprehensive drought tolerance coefficient (DTC), drought resistance index (DRI), and D-values classified germplasms into five categories: highly resistant (4.50%), resistant (11.71%), moderately resistant (57.21%), sensitive (16.22%), and highly sensitive (10.36%). Correlation and stepwise regression analyses identified five critical indicators: stem basal thickness, single plant biomass, spike weight, grain weight per spike, and yield. The predictive model demonstrated exceptional accuracy (R2 = 0.9998), enabling efficient screening using the targeted traits. The elite germplasms T125 (92) and Baogu 23 (135) consistently ranked as the most drought-tolerant across all methods. These findings establish a robust methodological framework for evaluating drought tolerance in foxtail millet and provide practical selection criteria for developing climate-resilient cultivars. The identified germplasms and evaluation indices significantly contribute to agricultural sustainability in water-limited environments, supporting food security in regions that are increasingly affected by climate-induced drought stress.
Open AccessDrought Tolerance Evaluation and Classification of Foxtail Millet Core Germplasms Using Comprehensive Tolerance Indices
Drought stress critically constrains agricultural productivity in arid and semi-arid regions, necessitating the development of drought-tolerant crop varieties for sustainable food security. This study evaluated drought tolerance in 222 foxtail millet (Setaria italica) germplasms from diverse Chinese agroecological zones from 2021–2023 at a specialized identification site in Xinjiang. Field experiments used a randomized complete block design comparing normal irrigation (3000 m3/ha) with drought stress (1800 m3/ha) across 12 morpho-agronomic traits including plant height, spike characteristics, biomass, and yield components. Drought stress significantly reduced all parameters, with yield exhibiting the highest sensitivity (drought tolerance coefficient = 0.58). Principal component analysis indicated that the first three components explained 82.70% of phenotypic variance, with yield-related parameters contributing the most to genotypic differentiation. Integrated evaluation using comprehensive drought tolerance coefficient (DTC), drought resistance index (DRI), and D-values classified germplasms into five categories: highly resistant (4.50%), resistant (11.71%), moderately resistant (57.21%), sensitive (16.22%), and highly sensitive (10.36%). Correlation and stepwise regression analyses identified five critical indicators: stem basal thickness, single plant biomass, spike weight, grain weight per spike, and yield. The predictive model demonstrated exceptional accuracy (R2 = 0.9998), enabling efficient screening using the targeted traits. The elite germplasms T125 (92) and Baogu 23 (135) consistently ranked as the most drought-tolerant across all methods. These findings establish a robust methodological framework for evaluating drought tolerance in foxtail millet and provide practical selection criteria for developing climate-resilient cultivars. The identified germplasms and evaluation indices significantly contribute to agricultural sustainability in water-limited environments, supporting food security in regions that are increasingly affected by climate-induced drought stress.