|
|
|
 |
Search published articles |
 |
|
Showing 2 results for Heatmap
Hossein Zeinalzadeh-Tabrizi, Sadollah Mansouri, Abbas Fallah-Toosi,
Volume 8, Issue 1 (8-2021)
Abstract
Analysis of genotype by environment interaction using different statistical methods is very important in plant breeding. In order to evaluate the seed yield stability of promising sesame lines using different parametric and non-parametric statistics, an experiment was conducted using 13 promising sesame lines with check variety Oltan at three locations of Karaj, Mashhad, and Moghan (Iran) in a randomized complete block design with four replications over two years (2016 and 2017). Combined analysis of variance for seed yield of promising sesame lines showed that the effect of genotype and the three-way interaction of genotype × year × location at the level of 0.01% probability were statistically significant. Karaj-96 environment with 1346 kg/ha and Mashhad-96 environment with 1001 kg/ha had the highest and lowest mean yield, respectively. The highest and lowest mean seed yield among genotypes in all test environments were related to G6 line with 1444 kg/ha and G12 line with 762 kg/ha, respectively. Heatmap along with cluster analysis divided both genotypes and stability parameters into three groups. Based on cluster analysis, genotype G12 was clustered into the first group, genotypes G1, G3, G7, G8, and G13 were clustered into the second group and the rest of the genotypes along with the check cultivar Oltan were clustered into the third group. The genotypes of the second group with the highest rank in most criteria of stability stasistics were stable compared to other genotypes and among them, the genotypes G8, G1 and G3 (with mean yields 1417, 1398 and 1291 Kg/ha, repectively) were selected and recommended in the test locations due to their average yield above the average yield of all genotypes.
Parastoo Zarei, Hedieh Badakhshan, Ghader Mirzaghaderi,
Volume 11, Issue 1 (9-2024)
Abstract
Evaluating genetic diversity in plant species is essential for crop improvement. This research compared the genetic diversity between common oat (Avena sativa) and wild oat (Avena fatua) using molecular markers, phenotypic traits, and chromosomal characteristics. SCoT and IRAP markers generated 283 and 117 bands, respectively. Both marker systems revealed higher polymorphism in wild oat compared to common oat. SCoT markers showed 65.37 percent polymorphism in wild oat versus 60.07 percent in common oat, while IRAP markers exhibited 76.07 and 69.23 percent polymorphism, respectively. Genetic diversity indices (Ne, He, and PIC) indicated slightly higher genetic diversity in wild oat for both marker systems, although the genetic distance between the two species was relatively low. Population structure analysis using Bayesian methods, Principal Coordinate Analysis (PCoA), and Analysis of Molecular Variance (AMOVA) consistently identified distinct subpopulations and significant genetic variation within species. Phenotypic trait analysis revealed significant differences among genotypes. Common oat genotypes generally exhibited greater plant height, while wild oat genotypes had higher 100-seed weight. Heatmap cluster analysis grouped genotypes into three clusters based on phenotypic traits. All genotypes were hexaploid but showed differences in chromosomal parameters such as total chromosome length, centromeric index, and dispersion index. However, no significant differences were found between common and wild oat species in these parameters. Principal Component Analysis (PCA) of chromosomal parameters explained 94.72 percent of the cumulative variance, with PC1 emphasizing centromere position and PC2 highlighting chromosomal asymmetry. This comprehensive study provides valuable insights for breeding and conservation strategies in oat species.
|
|
