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Genetic variability and association of characters in linseed (Linum usitatissimum L.) plant grown in central Ethiopia region
Linseed is one of the most important oil seed crop in the central highlands of Ethiopia for which yield enhancement is the major breeding purposes and genotypic variability is important for selection in any breeding programs. However, shortage of improved varieties’ that provides optimum seed yield...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7376236/ https://www.ncbi.nlm.nih.gov/pubmed/32714046 http://dx.doi.org/10.1016/j.sjbs.2020.06.043 |
Sumario: | Linseed is one of the most important oil seed crop in the central highlands of Ethiopia for which yield enhancement is the major breeding purposes and genotypic variability is important for selection in any breeding programs. However, shortage of improved varieties’ that provides optimum seed yield is one of the major constraints of the crop. Therefore, this study was carried out to assess the genetic variability and association among quantitative traits of 36 linseed genotypes. The experiment was conducted in 2018 main cropping season by using simple lattice design. The analysis of variances reveled highly significant difference among the genotype for most of traits considered in present study. High phenotypic and genotypic coefficient of variation was recorded for tiller per plant, harvest index, oil yield (kg ha(−1)), and seed yield (ton ha-1) number of capsules per plant. High heritability along with genetic advance was observed for seed yield (tones ha-(1)), oil yield (kg ha-(1)) harvest index which indicates selection of these traits at early generation would be effective. Oil yield (kg ha(−1)) harvest index and number of capsules plant (−1) showed highly significant positive with seed yield (ton ha(−1)). Cluster analysis revealed that 36 linseed genotypes were grouped into two clusters and four genotypes remain ungrouped. The maximum inter clusters distance was observed between clusters II and the local check. The data set was reduced into four significant principal components (PCs) that comprise (80%) of the variance. The first PC accounted for 34% of the variances that implies greater proportion of variable information explained by PC1. The traits, which contributed more to PC1, were seed yield per plant, primary branches per plant, secondary branches per plant and plant height showed positive association and had positive direct effect on seed yield. This indicates that any improvement of oil yield and harvest index would result in substantial increase on seed. |
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