Genetic variation, genotypic and phenotypic correlation, heritability, and path coefficient analysis of yield and yield related traits in bread wheat (Triticum aestivum L.) varieties at Gitilo Dale, western Ethiopia
Data files
May 05, 2025 version files 13.66 KB
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Morketa_Gudeta_(Supplementary_table).txt
12.12 KB
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README.md
1.55 KB
Abstract
The present study investigated the extent of genetic variability among twenty-five bread wheat (Triticum aestivum L.) varieties. The experiment was laid out in a randomized complete block design (RCBD). The objective of the study was to assess the extent of genetic variability in bread wheat varieties and associations of traits with grain yield. Data were collected for 14 agro-morphological traits, and the analysis of variance showed that varieties were highly significantly different for most of the traits, indicating the existence of ample genetic variation among the studied bread wheat varieties. Genotypic, phenotypic, heritability, and path coefficient analysis were employed to assess how different traits were contributing to the yield increment. Biological yield, harvest index, productive tillers per plant, kernels per spike, and spikelets per spike were the most important traits identified for bread wheat grain yield improvement. No ethical consideration is required while conducting this research
The analyzed data on genetic variation, genotypic and phenotypic correlation, heritability, and path coefficient analysis of yield and yield-related traits in bread wheat (Triticum aestivum L.) varieties at Gitilo Dale, Western Ethiopia
Dataset DOI: 10.5061/dryad.crjdfn3gq
Description of the data and file structure
The experiment is mainly focused on genetic variation, genotypic and phenotypic correlation, heritability, and path coefficient analysis of yield and yield-related traits in bread wheat (Triticum aestivum L.) varieties and identified the most important traits to improve bread wheat grain.
Files and variables
File: Supplementary_Tables_(1_and_2).docx
Description: These supplementary tables contain the processed or analyzed data of twenty-five bread varieties used in the study and their mean performances; both tables contain the processed data.
Code/software
SAS software 9.10 version
The collected data on 14 agro-morphological traits were subjected to analysis of variance following the ANOVA structure developed for randomized complete block design (RCBD) procedures. These traits include days to heading (DH), days to maturity (DM), grain filling period (GFP), grain yield (GY), biological yield (BY), thousand kernel weight (TKW), harvest index (HI), hectoliter weight (HLW), total tillers per plant (TTP), productive tillers per plant (PTP), plant height (PH), kernels per spike (KPS), spikelet per spike (SLP), and spike length (SL).