DETERMINING THE RELATIVE CONTRIBUTION OF YIELD COMPONENTS IN FABA BEAN USING SOME STATISTICAL METHODS | ||||
Journal of Plant Production | ||||
Article 6, Volume 33, Issue 10, October 2008, Page 7063-7070 PDF (599.72 K) | ||||
Document Type: Original Article | ||||
DOI: 10.21608/jpp.2008.171223 | ||||
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Authors | ||||
S. M. Salama; A. M. S. A. El-Taweel; S. S. Awaad | ||||
Lab of Des. and Stat. Anal. Res., Field Crop Institute, A.R.C., Giza – Egypt | ||||
Abstract | ||||
This investigation was carried out at the Agricultural Research Station of Tag El-Ezz, Dakahlia Governorate during 2006/2007 and 2007/2008 seasons to evaluate the performance of eight genotypes of faba bean namely; Sakha 1, Sakha 2, Nubaria 1, Giza 3, Giza 843, Giza 674, Giza 617 and Giza 2. Also, to investigate the relationship between seed yield/plant and its factors using some multivariate techniques namley; correlation, stepwise, multiple liner regression and factor analysis. The results showed that the studied characters were significantly affected by the tested faba bean varieties. Giza 2 was the earliest one concerning number of days to 50% flowering followed by Nubaria 1 and Sakha 2. Sakha 1 variety gave the highest values for number of branches/plant, plant hight, number of pods/main stem and number of seeds/pod followed by Giza 3 and Giza 716. Giza 3 recorded the highest weight of pods, 100 seed ands seed yield/plant followed by Sakha 1 and Giza 716. Multiple linear regression and stepwise analysis agreed upon the number of branches/plant, number of pods/main stem, weight of pods/plant and 100-seed weight as major contributions to seed yield variation. Factor analysis grouped the studied variables in two major factors which altogether accounted for 81.31 of the total variation. The first factor includes number of pods/main stem, number of seeds/pod, weight of pods/plant and 100-seed weight. The second factor included the remaining variables. Factor analysis technique was more efficient than the other techniques. It provides more information about cluster of intercorrelated variables. | ||||
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