Scientific Journal

Comparative Multivariate Evaluation of Autumn Sugar Beet Genotypes across two Climatic Regions

Document Type : Original Article

Authors

1 Sugar Beet Research Department, Hamedan Agricultural and Natural Resources Research and Education Center, AREEO, Hamedan, Iran

2 Horticulture-Crops Research Department, Golestan Agricultural and Natural Resources Research and Education Center, AREEO, Gorgan, Iran

3 Sugar Beet Research Department, Fars Agricultural and Natural Resources Research and Education Center, AREEO, Shiraz , Iran

10.22034/pgr.2025.2070711.1019
Abstract
This aimed to assess genetic diversity, evaluate quantitative and qualitative traits, and identify superior sugar beet genotypes in two different climatic environments (Fasa and Gonbad). A set of yield, and industrial quality-related traits, including root yield, white sugar yield, molasses sugar percentage, root alkalinity, α-amino nitrogen, sodium content, and potassium content, were measured and analyzed. The results of this study showed that most traits exhibited high heritability and substantial genetic advance, enabling effective selection at early stages of breeding. Multivariate analyses, including genotype × trait biplot and cluster analysis, revealed the genetic structure of the population. In the biplot diagram, yield and quality traits such as root yield, white sugar yield, and white sugar content showed positive and significant correlations, and genotypes 6, 7, 14, and 19 were positioned along these vectors and were identified as superior genotypes. In contrast, traits such as root alkalinity, sodium content, and molasses sugar percentage showed negative correlations with desirable sugar traits, and genotypes located near these vectors were evaluated as undesirable. Cluster analysis in both environments resulted in the formation of three distinct clusters. Genotypes in the third cluster in Fasa and the first cluster in Gonbad exhabited higher mean values for yield and quality traits and were identified as valuable genetic resources. These findings indicate that multi-trait approaches and targeted genotype selection across diverse climatic conditions can effectively enhance sugar beet improvement.

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