A comprehensive model for predicting the development of defense system of Capparis spinosa L.: a novel approach to assess the physiological indices

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Abstract

Capparis spinosa L. (caper) is a halophytic plant that grows in semi-arid or arid environments. The current study used an integrated experimental and computational approach to investigate the network of inter-correlated effective variables on the activity of antioxidant enzymes, proline, and photosynthetic pigments in stressed caper. To investigate the possible relationships among intercorrelated variables and understand the possible mechanisms, predictive regression modelling, principal component analysis (PCA), Pearson's correlation, and path analysis were implemented. PCA successfully discerned different salt ratio- and drought-specific effects in data in the current study, and treatments with higher growth indices are easily recognizable. Different salt ratios did not have a significant effect on the activity of four antioxidant enzymes, proline and photosynthesis pigments content of caper. While at the mean level, the activity of four antioxidant enzymes of SOD, POD, CAT, and APX significantly increased under drought stress by 54.0%, 71.2%, 79.4%, and 117.6%, respectively, compared to 100% FC. The drought stress also significantly increased the content of carotemoid (29.3%) and proline (by 117.7%). Predictive equation models with highly significant R2 were developed for the estimation of antioxidant enzyme activity and proline content (> 0.94) as well as pigments (> 0.58) were developed. Path analysis studies revealed that proline is the most important regressor in four antioxidant enzyme activities, while leaf tissue density was the most effective variable in the case of chlorophylls. Furthermore, the network of intercorrelated variables demonstrated a close relationship between caper's antioxidant defence system, pigments, and morphological parameters under stress conditions. The findings of this study will be a useful guide to caper producers as well as plant ecophysiological researchers.

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APA

Afzali, S. F., Sadeghi, H., & Taban, A. (2023). A comprehensive model for predicting the development of defense system of Capparis spinosa L.: a novel approach to assess the physiological indices. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-39683-5

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