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      Secondary Metabolites, Osmolytes and Antioxidant Activity as the Main Attributes Enhanced by Biostimulants for Growth and Resilience of Lettuce to Drought Stress

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          Oxidative stress and some antioxidant systems in acid rain-treated bean plants

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            Improved procedures for clearing roots and staining parasitic and vesicular-arbuscular mycorrhizal fungi for rapid assessment of infection

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              Chlorophyll fluorescence: a probe of photosynthesis in vivo.

              The use of chlorophyll fluorescence to monitor photosynthetic performance in algae and plants is now widespread. This review examines how fluorescence parameters can be used to evaluate changes in photosystem II (PSII) photochemistry, linear electron flux, and CO(2) assimilation in vivo, and outlines the theoretical bases for the use of specific fluorescence parameters. Although fluorescence parameters can be measured easily, many potential problems may arise when they are applied to predict changes in photosynthetic performance. In particular, consideration is given to problems associated with accurate estimation of the PSII operating efficiency measured by fluorescence and its relationship with the rates of linear electron flux and CO(2) assimilation. The roles of photochemical and nonphotochemical quenching in the determination of changes in PSII operating efficiency are examined. Finally, applications of fluorescence imaging to studies of photosynthetic heterogeneity and the rapid screening of large numbers of plants for perturbations in photosynthesis and associated metabolism are considered.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Gesunde Pflanzen
                Gesunde Pflanzen
                Springer Science and Business Media LLC
                0367-4223
                1439-0345
                October 2023
                January 16 2023
                October 2023
                : 75
                : 5
                : 1737-1753
                Article
                10.1007/s10343-022-00827-8
                da2ee8c8-7e51-4ede-9172-c39faa1e1fcc
                © 2023

                https://www.springernature.com/gp/researchers/text-and-data-mining

                https://www.springernature.com/gp/researchers/text-and-data-mining

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