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

• Published in: International journal of agricultural and biological engineering 2018, Vol.11 (2), p.196-201
• Main Authors: Wang, Wensen, Wang, Cheng, Pan, Dayu, Zhang, Yakun, Luo, Bin, Ji, Jianwei
• Format: Article
• Language: English
• Subjects: Chlorophyll; Conductance; Crop yield; Drought; Energy conversion; Energy conversion efficiency; Fluorescence; Glycine max; Photochemicals; Photosynthesis; Photosystem II; Plant growth; Quenching; Regression analysis; Resistance; Seedlings; Seeds; Soil analysis; Soybeans; Stomata; Stomatal conductance; Stress; Stresses
• ISSN: 1934-6344; 1934-6352
• DOI: 10.25165/j.ijabe.20181102.3390

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.