Grouping Phonological and Morphological Characteristics of Chickpea Genotypes (Cicer Arietinum L.) Ardabil region using cluster analysis and detection function

Journal Title: International Journal of Farming and Allied Sciences - Year 2013, Vol 2, Issue 23

Abstract

In order to evaluate physiological traits, yield and its components in chickpea genotypes with fall planting rainfed agriculture and natural resources research station during the test was done in the years 2011-2012. Tested in a randomized complete block design with three replications was conducted in 12 chickpea genotypes resistant to cold. Phenological traits, morphological, and grain weight, grain yield and biomass were investigated. After standardizing the data, cluster analysis was performed using Euclidean distance and the square of the distance factor WARD and 12 genotypes were placed in 3 groups. Detection function was used to select the best place to cut the dendrogram. The first group contains the digits 1, 6 and 12 that the percentage of emergence, empty pods, filled pods, number of branches, biomass and grain yield is high yielding varieties, including green fabric as well as most of the cultivars. The second group includes the numbers 2, 3, 4, 5 and 9, and the number of days to flowering, plant height and days to maturity were more valuable and ranked among the varieties of late flowering and late. The third group contains the digits 7, 8, 10 and 11 respectively that seed weight and number of main branches were of great value in the first place. The figures also showed that a low yield can be crossed to improve the yield of cultivars with higher yield figures for the first group. Therefore, among the three groups, the first group of numbers 1, 6 and 12 presented as suitable for the selection of new varieties in terms of yield.

Authors and Affiliations

Helal Motavassel

Keywords

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  • EP ID EP32450
  • DOI -
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How To Cite

Helal Motavassel (2013). Grouping Phonological and Morphological Characteristics of Chickpea Genotypes (Cicer Arietinum L.) Ardabil region using cluster analysis and detection function. International Journal of Farming and Allied Sciences, 2(23), -. https://europub.co.uk/articles/-A-32450