Evaluation of Sunflower (Helianthus annuus L.) Hybrids Using Multivariate Statistical Analysis

Abstract

Evaluation and characterization of sunflower hybrids using morphological, physiological and biochemical data are necessary and essential in sunflower breeding programs. The aim of this paper was to evaluate the productive possibilities of some sunflower hybrids grown in Macedonian environmental conditions. The experiment was carried out during the period 2013 and 2014 on the research field of the Faculty of Agriculture, “Goce Delchev” University – Shtip, in Ovche Pole locality, Republic of Macedonia. Total 20 sunflower hybrids were used as an experimental material. The trial was arranged as randomized complete block design (RCBD) with three replications. The average content of oil and oleic acid were 45.6 and 65.2%, respectively. The highest seed yield from all sunflower hybrids was obtained for the hybrid NLK12M144 (3,344 kg ha–1) and the lowest for hybrid NLK12S126 (2,244 kg ha–1). Cluster analysis classified the sunflower hybrids into four groups based on agronomic traits and seed yield. Most of the hybrids were included in cluster I and III (7 hybrids) followed by cluster IV. Using principal component analysis two main components have been extracted, with eigenvalue greater than one. They account for 72.99% of the variability in the original data. Only four hybrids had positive values for both main components (NLK12M144, NLK12S070, NLK12S125 and NLN12N011 DMR). The results from this study can be used to identify the best sunflower hybrids grown under Macedonian environmental conditions and to select the superior hybrids for future exploitation.

Molecular markers-based DNA fingerprinting coupled with morphological diversity analysis for prediction of heterotic grouping in sunflower (Helianthus annuus L.)

“…Analyzing genetic diversity through multivariate statistics involved the use of cluster analysis, and principal component analysis for grouping genotypes based on the similarities and differences among them (Peeters and Martinelli, 1989 ; Nasreen et al, 2011 ). According to Mohammadi and Prasanna ( 2003 ), many researchers have previously successfully utilized these multivariate techniques for diversity analysis in different crops such as barley (Ruzdik et al, 2015 ), wheat (Cross, 1992 ), sorghum (Hailu et al, 2006 ), and sunflower (Ayana and Bekele, 1999 ). Results of cluster analysis grouped CMS and restorer lines separately.…”

Quality variation of fruits of species of the genus Lycium in Ukraine: A comparative morphological analysis

“…Cluster analysis has been used for evaluation of genetic diversity in many crops such as Cornus mas L. (Jaćimović et al, 2015), Helianthus annuus L. (Ruzdik et al, 2015), Aronia mitschurinii A. K. Skvortsov & Maitul. (Vinogradova et al, 2017), Ziziphus jujuba Mill.…”

Evaluation and selection of promising sunflower germplasm under early winter planting conditions

“…Likewise, Ruždik et al (2015), based on agronomic parameters, had classified 20 sunflower varieties into four groups in their study in Republic of Macedonia. Classifying thirteen sunflower genotypes in Libya by UPGMA procedure, on morphological basis, Mahmoud et al (2012) had found two major groups.…”