MULTIVARIATE ANALYSIS OF GENETIC DIVERSITY AMONG THIRTY-SEVEN Chenopodium quinoa GENOTYPES UNDER ORGANIC AND MINERAL FERTILIZATION
AHMED MEDHAT MOHAMED Al-NAGGAR *
Department of Agronomy, Faculty of Agriculture, Cairo University, Egypt
ABD EL-SAMAD MAHMOUD YOUNIS
Field Crops Research Department, Agricultural and Biological Research Inst., National Research Centre, 33 El-Behooth St., Giza, Egypt
MOHAMED MOHAMED ATTA
Department of Agronomy, Faculty of Agriculture, Cairo University, Egypt
MAISA LOTFY ABD EL-MONEIM
Central Laboratory of Organic Agriculture, Agricultural Research Center, Giza, Egypt
MARIAM SABRY AL-METWALLY
Central Laboratory of Organic Agriculture, Agricultural Research Center, Giza, Egypt
*Author to whom correspondence should be addressed.
Abstract
Assessing the genetic diversity among quinoa germplasm is of prime importance for its effective utilization in breeding programs. The aims of the present investigation were to evaluate the magnitude of genetic diversity, based on phenotypic data, among 37 quinoa genotypes, under organic and/or inorganic fertilizer conditions and assess interrelationships between seed yield and its related traits under both environments. Two experiments were carried out in two seasons; the 1st experiment under organic fertilization and the 2nd under mineral fertilization conditions. A randomized complete blocks design with three replications was used. Principle component analysis (PCA) and GT-Biplot technique were used. Quinoa genotypes recorded significant differences (P≤0.01) for all studied traits under each environment. The promising genotype(s) for each trait were identified. Results of GT-biplot indicated that the traits, branches/plant, seed diameter, seed yield/plant, seed nitrogen content, biological yield/plant, 1000-seed weight, seed oil content, plant height, inflorescence diameter, inflorescences/plant and chlorophyll concentration index were strongly correlated with seed yield/ha, had high estimates of heritability and genetic advance and thus could be considered as secondary traits for high seed yield either under organic or inorganic fertilization. The clustering analysis assigned the 37 quinoa genotypes into three groups. The highest genetic dissimilarity Euclidean coefficients were recorded between G23 and each of G8, G34, G4, G9, G24 and G5; they are the most unrelated genotypes, but the lowest dissimilarity was between G13 and G26, they are the most related genotypes. The identified promising genotypes and secondary traits could be offered to quinoa breeders for use in future breeding programs to improve seed yield.
Keywords: Cluster an alysis, GT-biplot, principle component analysis, quinoa