| Screening and evaluation for drought resistance of cotton varieties |
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| DOI：10.7606/j.issn.1000-7601.2017.01.36 |
| Key Words: cotton drought resistance screening evaluation |
| Author Name | Affiliation | | LI Zhong-wang | Biotechnology Institute, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China | | CHEN Yu-liang | Biotechnology Institute, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China | | LUO Jun-jie | Biotechnology Institute, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China | | SHI You-tai | Biotechnology Institute, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China | | FENG Ke-yun | Institute of Crop Sciences, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China | | CHEN Zi-xuan | Biotechnology Institute, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu 730070, China |
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| Abstract: |
| In order to screen the drought resistance of germplasm resources and develop cotton drought resistance evaluation system, 76 different cotton varieties (lines) were planted under drought stress and normal irrigation in Dunhuang City, Gansu province, where the annual rainfall is less than 40 mm. Drought resistance of 76 varieties (lines) was evaluated by the investigation on 10 agronomic traits and yield index which is closely related to drought resistance of cotton, in combination with the comprehensive drought resistant coefficient (CDC), comprehensive drought resistant index (CDI), membership function values (CDM) and drought resistance, drought resistance comprehensive evaluation values(D) four method. The evaluation results of the four methods were basically the same, and then clustering analysis was performed. The 76 varieties were divided into High Resistance (class I), Resistance(class Ⅱ), Middle (class Ⅲ), Sensitive (class IV) and High Sensitivity (class V) .The resulting 10 agronomic traits of drought resistance coefficient as the independent variable, four kinds of comprehensive evaluation of drought resistance of score values as the dependent variable, can be used to establish the regression equation using stepwise regression method for predict drought resistance of cotton, facilitating the simple and accurate evaluation of the drought resistance of breeding germplasms. |
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