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Showing 3 results for Principal Component Analysis

Seyedeh Zahra Hosseini, Ahmad Ismaili, Seyed Sajad Sohrabi,
Volume 5, Issue 2 (3-2019)
Abstract

Drought is a threaded factor in the world production and application of breeding methods could improve the tolerant and adapted cultivators under drought stress condition. In order to evaluate and determine the stress tolerance indices and identifion of tolerant genotypes to drought stress, 15 safflower genotypes were evaluated in a randomized complete block design with three replications in two conditions (stress and non-stress). Analysis of variance showed significant differences among genotypes for all traits, stress tolerance indices and yield in both conditions. Significant positive correlation was found between grain yield in the stress condition with indicators stress tolerance index, harmonic mean and geometric mean productivity indicating that these indices are suitable criteria for screening drought tolerant genotypes. No significant correlation was observed between Ys with tolerance index and mean productivity, hence they can be discarded as the desirable markers for identifying drought tolerant genotypes. In conclusion, using a graphical approach of three dimensional scatter plots, Principal component analysis and biplot analysis, two tolerant genotype (Syrian and Kino-76) were selected for future programs in stress and non-stress condition.
 
Hosein Astaraki, Mahmoud Lotfi, Sasan Aliniaeifard, Ali Izadi-Darbandi, Payman Sharifi, Hossein Ramshini,
Volume 10, Issue 2 (2-2024)
Abstract

In order to select the most tolerant genotypes of melon to drought stress, 30 landraces and cultivars were evaluated at Broujerd Agricultural Research Station in 2018. Under normal and drought stress conditions genotypes were evaluated in a randomized complete block design with three replications. Drought stress was started when fruits appeared. Based on the rate of evaporation in class A evaporation pan (normal conditions: 50 mm, stress conditions: 100 mm), irrigation was carried out. The results of this study showed that Yield under drought stress and normal conditions showed high correlations with stress tolerance indices such as MP (Mean Productivity), GMP (Geometric Mean Productivity) and STI (Suitability Tolerance Index). The broad sense hereditary under drought stress condition varied from 81% for yield per plant to 97% for the fruit lenght. Under drought stress condition, the highest percentage of genetic coefficient of variation (GCV) was observed for Weight of flesh and skin (49 percent) and the lowest for days to maturity (4 percent). Based on the PCA biplot, the genotypes of Mamaghani, Rish-baba, Garmak and Japuni melon were identified as tolerant and Mazandrani, Uzbak1 and Ginsen Makuwa were classified as sensitive to drought stress. These results could be useful for breeding purposes and the genotypes can be crossed with each other to produce segregating populations and selection of the best plants.

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.


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