Use of Canonical Correlation Analysis for Determination of Relationships Between Plant Characters and Yield Components in Winter Squash (Cucurbita Maxima Duch.) Populations

Abstract

Canonical correlation analysis is one of the most popular multivariate analysis techniques. In this study, a canonical correlation analysis (CCA) was used to estimate relationships between plant characters [X set - fruit length (FL), fruit diameter (FD), flesh thickness (FT), fiber weight per fruit (FW), length of seed cavity (LSC), skin thickness (ST), vine length (VL), brunch number per plant (BN), leaf length (LL), leaf width (LW), female flowering time (50%) (FFT), and time to maturity (TM)], and yield components [Y set- total fruit weight per plant (FW/P), average fruit weight (AFW) and number of fruits per plant (FN/P)] of 117 winter squash (Cucurbita maxima Duch.) in populations collected from the Black Sea Region of Turkey. In this study, three canonical correlation coefficients (CCCs) were estimated, and the first two of them were significant (0.903 and 0.571, p<0.001) with respect to the likelihood ratio test while third CCC was no significant (0.340, p>0.218). The findings obtained from the CCA indicate that FW/P had the largest contribution for the explanatory capacity of canonical variables estimated from yield components of 117 Turkish winter squash (Cucurbita maxima Duch.) populations when compared with other yield components. FD and FL had largest contribution for the explanatory capacity of canonical variables estimated from plant characters when compared with the other characters. The obtained results show that FD and FL should be used with the aim of increasing yield per plant in winter squash (Cucurbita maxima Duch.) populations in this study.