Evaluating the physiological and biochemical responses of melon plants to NaCl salinity stress using supervised and unsupervised statistical analysis

Abstract

Salinity is a major environmental issue affecting plant production, particularly in the Middle East. Multivariate data analysis including principal component analysis (PCA), hierarchical clustering analysis (HCA), and orthogonal projections to latent structures discriminant analysis (OPLS-DA) are powerful statistical modeling tools that can extract important information from large complex datasets and explain the relationship between different variables. The combined use of supervised and unsupervised statistical analysis thus provides a valuable understanding of tendencies (PCA) and sample grouping (OPLS-DA). In the current study, PCA, HCA, and OPLS-DA as well as analysis of variance were used to assess the physiological and biochemical response of three melon genotypes (Ghobadlu, Suski-e-Sabz, and Galia F1) to NaCl concentrations (0, 50, and 100 mM) after 15 and 30 days of treatment in a greenhouse. PCA results and loading plots showed that axis 1 principal component 1 was negatively correlated with intrinsic water use efficiency, instantaneous water use efficiency, abscisic acid, and flavonol content at 15 and 30 days of treatment. In other words, these parameters increased under salinity conditions in the studied genotypes, which could be of interest as a stress tolerance indicator at both sampling dates. These findings are in accordance with the mean comparison results of traits in three melon genotypes under NaCl concentrations. In addition, the HCA heatmap showed that all measured parameters can be grouped into two distinct clusters at the two time points. Further, supervised analysis with OPLS-DA easily discriminates samples according to genotype and salinity. In conclusion, multivariate and univariate statistics can be useful for revealing patterns and thus selecting melon genotypes with high salt tolerance that can be used in breeding programs. Genotypes Galia F1 and Ghobadlu were more tolerant of salinity than Suski-e-Sabz, as both had a better performance in stomatal and non-stomatal parameters at the two sampling dates.