Effects of drought stress on photosynthesis and chlorophyll fluorescence images of soybean (Glycine max) seedlings

文献类型： 外文期刊

第一作者： Wang, Wensen

作者： Wang, Wensen;Ji, Jianwei;Wang, Wensen;Wang, Cheng;Pan, Dayu;Zhang, Yakun;Luo, Bin;Wang, Wensen;Wang, Cheng;Pan, Dayu;Zhang, Yakun;Luo, Bin;Wang, Cheng;Pan, Dayu;Zhang, Yakun;Luo, Bin

作者机构：

关键词： soybean seedling; drought stress; photosynthetic parameters; chlorophyll fluorescence parameters; chlorophyll fluorescence images

期刊名称：INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING （ 影响因子：2.032； 五年影响因子：2.137 ）

ISSN： 1934-6344

年卷期： 2018 年 11 卷 2 期

页码：

收录情况： SCI

摘要： The main purpose of this research is to provide a theoretical foundation for the screening of drought-resistant soybean varieties and to establish an efficient method to detect the PSII actual photochemical quantum yields efficiently. Three soybean varieties were compared in this experiment after 15 d when they were planted in a greenhouse. These varieties were then exposed to light drought stress (LD) and serious drought stress (SD) conditions. With five times' measurement, chlorophyll fluorescence and soil-plant analysis development considered as the main basis for this study. Several parameters in SD conditions significantly reduced, such as net photosynthetic rates (Pn), stomatal conductance (Gs), PSII primary light energy conversion efficiency (Fv/FM), PSII actual photochemical quantum yields [Y(II)], photochemical quenching coefficient (qP) and non-photochemical quenching coefficient (qN). The soybeans in the seedling stage adapted to the inhibitory effect of drought stress on photosynthesis through stomatal limitation. Under serious drought stress, non-stomatal limitation damaged the plant photosynthetic system. The amplitudes of Pn and Y(II) of drought-resistant Qihuang 35 were lower than those of the two other varieties. Based on the data of this study, a new method had been developed to detect Y (II) which reflected the photosynthetic capacity of plant, R=0.85989, u=0.048803 when using multiple linear regression, and R=0.84285, u=0.054739 when using partial least square regression.

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