Hydrotime Model Parameters Estimate Seed Vigor and Predict Seedling Emergence Performance of <i>Astragalus sinicus</i> under Various Environmental Conditions
Seed vigor is an important aspect of seed quality. High-vigor seeds show rapid and uniform germination and emerge well, especially under adverse environmental conditions. Here, we determined hydrotime model parameters by incubating seeds at different water potentials (0.0, −0.2, −0.4, −0.6, and −0.8...
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| Format: | Article |
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MDPI AG
2023-05-01
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| Series: | Plants |
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| Online Access: | https://www.mdpi.com/2223-7747/12/9/1876 |
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| author | Qibo Tao Dali Chen Mengjie Bai Yaqi Zhang Ruizhen Zhang Xiaofei Chen Xiaotong Sun Tianxiu Niu Yuting Nie Shangzhi Zhong Juan Sun |
| author_facet | Qibo Tao Dali Chen Mengjie Bai Yaqi Zhang Ruizhen Zhang Xiaofei Chen Xiaotong Sun Tianxiu Niu Yuting Nie Shangzhi Zhong Juan Sun |
| author_sort | Qibo Tao |
| collection | DOAJ |
| description | Seed vigor is an important aspect of seed quality. High-vigor seeds show rapid and uniform germination and emerge well, especially under adverse environmental conditions. Here, we determined hydrotime model parameters by incubating seeds at different water potentials (0.0, −0.2, −0.4, −0.6, and −0.8 MPa) in the laboratory, for 12 seed lots of Chinese milk vetch (<i>Astragalus sinicus</i>) (CMV), a globally important legume used as forage, green manure, and a rotation crop. Pot experiments were conducted to investigate the seedling emergence performance of 12 CMV seed lots under control, water stress, salinity stress, deep sowing, and cold stress conditions. Meanwhile, the field emergence performance was evaluated on two sowing dates in June and October 2022. Correlation and regression analyses were implemented to explore the relationships between hydrotime model parameters and seedling emergence performance under various environmental conditions. The seed germination percentage did not differ significantly between seed lots when seeds were incubated at 0.0 MPa, whereas it did differ significantly between seed lots at water potentials of −0.2, −0.4, and −0.6 MPa. The emergence percentage, seedling dry weight, and simplified vigor index also differed significantly between the 12 seed lots under various environmental conditions. <i>Ψ</i><sub>b(50)</sub> showed a significant correlation with germination and emergence performance under various environmental conditions; however, little correlation was observed between <i>θ</i><sub>H</sub> or <i>σ</i><sub>φb</sub> and germination and emergence. These results indicate that <i>Ψ</i><sub>b(50)</sub> can be used to estimate seed vigor and predict seedling emergence performance under diverse environmental conditions for CMV and similar forage legumes. This study will enable seed researchers, plant breeders, and government program directors to target higher seed vigor more effectively for forage legumes. |
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| institution | Directory Open Access Journal |
| issn | 2223-7747 |
| language | English |
| last_indexed | 2024-03-11T04:10:16Z |
| publishDate | 2023-05-01 |
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| spelling | doaj.art-9be75b385a09462ab9c04be3c7aafae72023-11-17T23:32:56ZengMDPI AGPlants2223-77472023-05-01129187610.3390/plants12091876Hydrotime Model Parameters Estimate Seed Vigor and Predict Seedling Emergence Performance of <i>Astragalus sinicus</i> under Various Environmental ConditionsQibo Tao0Dali Chen1Mengjie Bai2Yaqi Zhang3Ruizhen Zhang4Xiaofei Chen5Xiaotong Sun6Tianxiu Niu7Yuting Nie8Shangzhi Zhong9Juan Sun10Key Laboratory of National Forestry and Grassland Administration on Grassland Resources and Ecology in the Yellow River Delta, Qingdao Key Laboratory of Specialty Plant Germplasm Innovation and Utilization in Saline Soils of Coastal Beach, College of Grassland Science, Qingdao Agricultural University, Qingdao 266109, ChinaState Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, ChinaState Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, ChinaKey Laboratory of National Forestry and Grassland Administration on Grassland Resources and Ecology in the Yellow River Delta, Qingdao Key Laboratory of Specialty Plant Germplasm Innovation and Utilization in Saline Soils of Coastal Beach, College of Grassland Science, Qingdao Agricultural University, Qingdao 266109, ChinaCollege of Animal Science and Technology, Qingdao Agricultural University, Qingdao 266109, ChinaKey Laboratory of National Forestry and Grassland Administration on Grassland Resources and Ecology in the Yellow River Delta, Qingdao Key Laboratory of Specialty Plant Germplasm Innovation and Utilization in Saline Soils of Coastal Beach, College of Grassland Science, Qingdao Agricultural University, Qingdao 266109, ChinaCollege of Animal Science and Technology, Qingdao Agricultural University, Qingdao 266109, ChinaKey Laboratory of National Forestry and Grassland Administration on Grassland Resources and Ecology in the Yellow River Delta, Qingdao Key Laboratory of Specialty Plant Germplasm Innovation and Utilization in Saline Soils of Coastal Beach, College of Grassland Science, Qingdao Agricultural University, Qingdao 266109, ChinaKey Laboratory of National Forestry and Grassland Administration on Grassland Resources and Ecology in the Yellow River Delta, Qingdao Key Laboratory of Specialty Plant Germplasm Innovation and Utilization in Saline Soils of Coastal Beach, College of Grassland Science, Qingdao Agricultural University, Qingdao 266109, ChinaKey Laboratory of National Forestry and Grassland Administration on Grassland Resources and Ecology in the Yellow River Delta, Qingdao Key Laboratory of Specialty Plant Germplasm Innovation and Utilization in Saline Soils of Coastal Beach, College of Grassland Science, Qingdao Agricultural University, Qingdao 266109, ChinaKey Laboratory of National Forestry and Grassland Administration on Grassland Resources and Ecology in the Yellow River Delta, Qingdao Key Laboratory of Specialty Plant Germplasm Innovation and Utilization in Saline Soils of Coastal Beach, College of Grassland Science, Qingdao Agricultural University, Qingdao 266109, ChinaSeed vigor is an important aspect of seed quality. High-vigor seeds show rapid and uniform germination and emerge well, especially under adverse environmental conditions. Here, we determined hydrotime model parameters by incubating seeds at different water potentials (0.0, −0.2, −0.4, −0.6, and −0.8 MPa) in the laboratory, for 12 seed lots of Chinese milk vetch (<i>Astragalus sinicus</i>) (CMV), a globally important legume used as forage, green manure, and a rotation crop. Pot experiments were conducted to investigate the seedling emergence performance of 12 CMV seed lots under control, water stress, salinity stress, deep sowing, and cold stress conditions. Meanwhile, the field emergence performance was evaluated on two sowing dates in June and October 2022. Correlation and regression analyses were implemented to explore the relationships between hydrotime model parameters and seedling emergence performance under various environmental conditions. The seed germination percentage did not differ significantly between seed lots when seeds were incubated at 0.0 MPa, whereas it did differ significantly between seed lots at water potentials of −0.2, −0.4, and −0.6 MPa. The emergence percentage, seedling dry weight, and simplified vigor index also differed significantly between the 12 seed lots under various environmental conditions. <i>Ψ</i><sub>b(50)</sub> showed a significant correlation with germination and emergence performance under various environmental conditions; however, little correlation was observed between <i>θ</i><sub>H</sub> or <i>σ</i><sub>φb</sub> and germination and emergence. These results indicate that <i>Ψ</i><sub>b(50)</sub> can be used to estimate seed vigor and predict seedling emergence performance under diverse environmental conditions for CMV and similar forage legumes. This study will enable seed researchers, plant breeders, and government program directors to target higher seed vigor more effectively for forage legumes.https://www.mdpi.com/2223-7747/12/9/1876<i>Astragalus sinicus</i>base water potentialcorrelation analysishydrotime model parametersregression analysisseed germination |
| spellingShingle | Qibo Tao Dali Chen Mengjie Bai Yaqi Zhang Ruizhen Zhang Xiaofei Chen Xiaotong Sun Tianxiu Niu Yuting Nie Shangzhi Zhong Juan Sun Hydrotime Model Parameters Estimate Seed Vigor and Predict Seedling Emergence Performance of <i>Astragalus sinicus</i> under Various Environmental Conditions Plants <i>Astragalus sinicus</i> base water potential correlation analysis hydrotime model parameters regression analysis seed germination |
| title | Hydrotime Model Parameters Estimate Seed Vigor and Predict Seedling Emergence Performance of <i>Astragalus sinicus</i> under Various Environmental Conditions |
| title_full | Hydrotime Model Parameters Estimate Seed Vigor and Predict Seedling Emergence Performance of <i>Astragalus sinicus</i> under Various Environmental Conditions |
| title_fullStr | Hydrotime Model Parameters Estimate Seed Vigor and Predict Seedling Emergence Performance of <i>Astragalus sinicus</i> under Various Environmental Conditions |
| title_full_unstemmed | Hydrotime Model Parameters Estimate Seed Vigor and Predict Seedling Emergence Performance of <i>Astragalus sinicus</i> under Various Environmental Conditions |
| title_short | Hydrotime Model Parameters Estimate Seed Vigor and Predict Seedling Emergence Performance of <i>Astragalus sinicus</i> under Various Environmental Conditions |
| title_sort | hydrotime model parameters estimate seed vigor and predict seedling emergence performance of i astragalus sinicus i under various environmental conditions |
| topic | <i>Astragalus sinicus</i> base water potential correlation analysis hydrotime model parameters regression analysis seed germination |
| url | https://www.mdpi.com/2223-7747/12/9/1876 |
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