FIGURE 11.

Multivariate data analysis. An integrated comparative (A) Bi-plot based principal component analysis (PCA) with first two principal components and (B) heat map showing the differential response of transgenic lines (L7, L11, and L14) and control plants (WT and VC) under normal and stress (NaCl and osmotic) condition. PCA is a multivariate analysis method by which correlation between variables was studied among multidimensional datasets. Plants grown under varying stress were selected as observations, whereas different morphological and physio-biochemical measurements were taken as variables. Observation and variable data set were used to generate Pearson’s correlation matrix, and PCA was analyzed.