Evaluation of sunflower (Helianthus annuus L.) varieties using multivariate statistical analysis

Markova Ruzdik, Natalija and Karov, Ilija and Mitrev, Sasa and Gorgieva, Biljana and Kovacevik, Biljana and Arsov, Emilija (2015) Evaluation of sunflower (Helianthus annuus L.) varieties using multivariate statistical analysis. Helia, International Scientific Journal, 38 (63). pp. 175-187. ISSN 1018-1806 (In Press)

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Abstract

Collecting, evaluation and characterization of sunflower varieties is necessary and essential in sunflower breeding programs. The aim of this paper was to evaluate the productive possibilities of some sunflower varieties grown in Macedonia.
The experiment was carried out during the period 2013 and 2014 on the research fields of Faculty of Agriculture, "Goce Delchev” University in Ovche Pole locality, Republic of Macedonia. Total 20 sunflower varieties were used as experimental material and the experimental work was conducted in a randomized complete block system. During the vegetation symptoms of charcoal rot, sunflower rust and phoma black stem were observed in the field. The highest seed yield from all sunflower varieties was obtained for genotype NLK12M144 (3 344 kg/ha) and the lowest for variety NLK12S126 (2 244 kg/ha). Cluster analysis classified the sunflower varieties into four groups based on agronomic traits and seed yield. The largest number of genotypes were included in cluster I and III (7 genotypes) followed by cluster IV. Using principle component analysis were separate two main components with eigenvalue greater than one accounting for 72.99 % of the total variation. Only four genotypes had positively values to both main components (NLK12M144, NLK12S070, NLK12S125 and NLN12N011 DMR).
Key words: sunflower, seed yield, agronomic traits, principle component analysis, cluster analysis

Item Type: Article
Subjects: Agricultural Sciences > Agricultural biotechnology
Divisions: Faculty of Agriculture
Depositing User: Natalija Markova Ruzdik
Date Deposited: 09 Jun 2015 13:21
Last Modified: 23 Dec 2016 12:48
URI: https://eprints.ugd.edu.mk/id/eprint/13280

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