Study on the most important agronomical traits of 13 tomato cultivars through factor analysis

Journal Title: International Journal of Farming and Allied Sciences - Year 2013, Vol 2, Issue 17

Abstract

In order to classify tomato cultivars based on interested traits, an experiment was conducted on 13 genotypes in the form of randomized complete blocks (RCB) design, with three replications, in Karaj region during year 2012. Factor analysis led to selection of 4 factors with high Eigen values, which together accounted for 87.327% of initial data variance. Based on results from factor analysis, most of the traits had high communalities which indicates that right number of factors have been selected to optimally account for variation of the traits. First factor accounted for the highest proportion (39.619%) of data variation, wherein traits such as fruit length, fruit diameter, pith size and fruit number per vine had great coefficient. Therefore, this factor can be designated as the factor of yield components. Second factor accounted for 20.687% of the variations. Traits such as leaf width and leaflet size were effective on this factor; thus it can be designated to as factor effective on plant leaf. Third factor accounted for 14.022% of the variations. Traits such as length of internode and thickness of fruit wall were effective on this factor. Finally, fourth factor accounted for 12.998% of the variations, while traits such as leaf length and peduncle length were effective on this factor, thus it can be designated as height factor. Together, the four factors accounted for 87.327% of data variation. In general, these four factors evaluated one specific trait against the others.

Authors and Affiliations

Behzad Daneshvar ghorbani, Mohammad Zaefizadeh, Ali Akbar Jannat Abadi and Farrokh Karimi

Keywords

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  • EP ID EP32366
  • DOI -
  • Views 314
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How To Cite

Behzad Daneshvar ghorbani, Mohammad Zaefizadeh, Ali Akbar Jannat Abadi and Farrokh Karimi (2013). Study on the most important agronomical traits of 13 tomato cultivars through factor analysis. International Journal of Farming and Allied Sciences, 2(17), -. https://europub.co.uk/articles/-A-32366