Evaluation of drought resistance in Iris germanica L. based on subordination function and principal component analysis
DOI:
https://doi.org/10.9755/ejfa.2017.v29.i10.1260Keywords:
Cluster analysis; Drought resistance; Iris germanica; Principal component analysis; Subordination function analysisAbstract
Drought is one of the major environment stresses that have a wide range of impact on plants. In this study, seven physiological indexes including the content of soluble protein (SP), chlorophyll (Chl) and malondialdehyde (MDA), superoxide dismutase (SOD) and peroxidase (POD) activities, leaf relative water content (RWC), rate of water loss (RWL) from excised leaves were measured in leaves of Iris germanica before and after the drought treatment. It was found that the content of MDA and SP, POD and SOD activity increased, while RWL and RWC decreased in response to drought stress. Based on the subordinate function values of seven physiological indexes, seven single indexes were transformed into three principal components namely damage degree, active oxygen removal ability and moisture condition and the composite score (F value) of each iris variety was calculated by principal component analysis (PCA). Based on the F values, 10 iris cultivars could be divided into three groups by cluster analysis (CA): drought-resistance (2 varieties), medium drought-resistance (5 varieties), and low drought-resistance (3 varieties). Meanwhile, optimum regression equation was constructed. Therefore, this work provides a comprehensive and reliable method for evaluating drought resistance in the varieties of Iris germanica.
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