SELECTION OF SUPERIOR GENOTYPES OF LIMA BEAN LANDRACES BY MULTIVARIATE APPROACH

The knowledge of genetic diversity in plant population is essential to the success of plant breeding programs. Thus, previous characterization of landraces is one of the first steps before the indication of genotypes to these plant breeding programs. This study aimed to characterize, through morphological traits, and estimate the genetic diversity in landraces of lima bean (Phaseolus lunatus L.). Genetic diversity was estimated by using multivariate methods that selected individual landraces to be indicated for farmers and consumers. According to morphological traits proposed by Biodiversity International, the genotypes UFPI-667 and UFPI-682 showed higher dissimilarity and high potential to be used in crosses since they are genetically distant and complementary. The principal component analysis identified positive and significant phenotypic associations between variables: pod length, pod width, and grain production. According to the multivariate methods used, the landraces UFPI-666, UFPI-650, UFPI-651, UFPI-687, UFPI-658, UFPI-673, UFPI-667, and UFPI-674 are potential candidates for selection since they have relevant features for lima bean breeding, such as shorter cycles and higher grain production. This study showed that multivariate analysis can be used as an effective tool to find potential traits in lima bean and can assist the lima bean breeders in the selection of potential landraces. Accessions UFPI-667 and UFPI-682 can be indicated as genitors for breeding programs, as they are genetically distant and complementary in their characteristics.

Automated summary

Knowledge of genetic diversity in plant population is crucial for the success of plant breeding programs. This study characterized and estimated the genetic diversity in landraces of lima bean using morphological traits and multivariate methods. The results showed that certain landraces exhibited high dissimilarity and potential for use in crosses. The study also identified significant phenotypic associations between pod length, pod width, and grain production through principal component analysis.