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- W3200244295 abstract "A good understanding of the genetic basis of plant photosynthetic responses to different environments will help unlock the tight interrelationship between plant physiology and genetics. Technological advances for measuring chlorophyll fluorescence of plant offer opportunities to gain information about differences in the efficiency of photochemistry of differentiate levels of organisms across the tree of life. Little knowledge is available on the natural variation of leaf Chlorophyll fluorescence in 27 wild Cynodon dactylon (L.) Pers. (common Bermuda grass) from different longitudes and latitudes in China. In this study, chlorophyll fluorescence parameters were detected and combined with genetic variation using field experiments. The amplitudes of the fluorescence parameters ofwild Bermuda grass at high latitude were slightly lower than other populations, which suggests that the photosynthetic efficiency and potential of populations at high latitude were higher than other populations. Significant differences in the fluorescence parameters were shown among genotypes at different latitudes, while there was no obvious difference between genetic groups of longitude. Our study identified the distribution pattern of chlorophyll fluorescence parameters in leaf, and their correlations with genetic variation along longitudinal and latitudinal gradients. The germplasm and the associated genetic information analyzed in this study could be utilized in breeding. Integrating these genetic studies with fluorescence-derived photosynthetic parameters supports an evolution explanation for the differentiation of chlorophyll fluorescence and promotes the understanding and prediction of biodiversity change." @default.
- W3200244295 created "2021-09-27" @default.
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- W3200244295 date "2021-07-26" @default.
- W3200244295 modified "2023-09-24" @default.
- W3200244295 title "Association of leaf Chlorophyll fluorescence with genetic variation in bermudagrass along longitudinal and latitudinal gradients" @default.
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- W3200244295 doi "https://doi.org/10.1109/agro-geoinformatics50104.2021.9530298" @default.
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