Year 2022, Volume 68 Issue 1 (31.03.2022)

Year : 2022
Volume : 68
Issue : 1 (31.03.2022)
   
Authors : Doriana (BODE) XHULAJ, Romina KOTO
Title : ESTIMATION OF GENETIC VARIABILITY OF AUTOCHTHONOUS WHEAT (TRITICUM AESTIVUM L.) GENOTYPES USING MULTIVARIATE ANALYSIS
Abstract : This study was conduct to evaluate the morphological variability of 23 autochthonous wheat genotypes (Triticum aestivum L.) part of the base collection of the Gene Bank (Agricultural University of Tirana). Crop production is strongly related with genetic diversity within germplasm and its improvement. Various statistical techniques have been used to study diversity among different genotypes. Among these techniques multivariate is most frequently used one for the genetic association of genotypes. Principal components and cluster analysis were carried out involving quantitative traits, such as tiller capacity, plant height, spike length, number of spikelet per spike, number of seeds per spikelet, seed size, weight of seeds per spike and seed yield. According to PCA, three components exhibited about 67.15% of the variability within 23 wheat genotypes. Accessions were grouped into three major clusters based on Euclidean distance, suggesting a variance of 41.72% within classes and 58.28% between classes. Accessions with major level of dissimilarity between them were AGB 3071 (Univers 6) and AGB 3064 (IKBA_05). The results suggested that plant height, spike length, number of spikelet per spike and weight of seeds per spike were the most important characters in differentiating the genotypes. The use of principal component and correlation coefficient analysis in the wheat germplasm, simplify dependable classification of genotypes, the identification of the superior genotypes and their relation with morphological traits with possibility expenditure in breeding programs.
For citation : Xhulaj, Bode, D., Koto, R. (2022): Estimation of genetic variability of autochthonous wheat (Triticum aestivum L.) genotypes using multivariate analysis. Agriculture and Forestry, 68 (1): 131-143. doi:10.17707/AgricultForest.68.1.07
Keywords : cluster, PC, genotypes, morphological, traits, variability
   
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