Multi-trait index: selection and recommendation of superior black bean genotypes as new improved varieties.

Common bean provides diet rich in vitamins, fiber, minerals, and protein, which could contribute into food security of needy populations in many countries. Developing genotypes that associate favorable agronomic and grain quality traits in the common bean crop could increase the chances of adopting new cultivars black bean. In this context, the present study aimed at selection of superior black bean lines using multi-variate indexes, Smith-Hazel-index, and genotype by yield*trait biplot analysis. These trials were conducted in Campos dos Goytacazes - RJ, in 2020 and 2021. The experimental design used was randomized blocks, with 28 treatments and three replications. The experimental unit consisted of four rows 4.0 m long, spaced at 0.50 m apart, with a sowing density of 15 seeds per meter. The two central rows were used for the evaluations. The selection of superior genotypes was conducted using the multiple trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), multi-trait index based on factor analysis and genotype-ideotype distance (FAI-BLUP), Smith-Hazel index, and Genotype by Yield*Trait Biplot (GYT). The multivariate indexes efficiently selected the best black bean genotypes, presenting desirable selection gains for most traits. The use of multivariate indexes and GYT enable the selection of early genotypes with higher grain yields. These lines G9, G13, G17, G23, and G27 were selected based on their performance for multiple traits closest to the ideotype and could be recommended as new varieties.

Genetic divergence and truncation and simultaneous selection in inbred families (S1) of elephant grass for bioenergetic purposes via mixed models.

The State University of North Fluminense Darcy Ribeiro (UENF) has been developing for fifteen years a breeding program that aims at the development of new cultivars of elephant grass due to its high potential and the low availability of cultivars developed by genetic breeding programs that meet the needs of producers in the State of Rio de Janeiro. In this sense, inbred families were also obtained as a way of fixing potential alleles for traits related to production, as the inbreeding process apparently does not strongly affect elephant grass in aspects related to inbreeding depression. This study aimed to estimate genetic diversity, variance components and prediction of genotypic values in 11 (S1) elephant grass families, and perform the truncation and simultaneous selection of traits using the selection index, by mixed models. The experimental design consisted of randomized blocks with 11 (S1) families, three replications, and six plants per plot. For variables dry matter production, percentage of dry matter, plant height, stem diameter, number of tillers and leaf blade width, was performed the estimation of genetic parameters and selection of the best genotypes based selection index using mixed model. The descriptors were subjected to correlation analysis, distance matrices were generated by the Mahalanobis method, and individuals were grouped by the UPGMA method. In the selection via mixed models (REML/BLUP), families 6, 11, 8, 1, 3, 7, and 9 contributed most of the genotypes selected for the evaluated traits, indicating their high potential to generate superior genotype. The selection indices via mixed models indicated that the multiplicative index presented a greater selection gain.The phenotypic correlations showed the possibility of performing an indirect selection from six evaluated traits.The genotypes were separated into 18 groups by the Mahalanobis distance, allowing the observation of a wide genetic diversity. The most divergent and productive genotypes were self-fertilized to obtain the second generation (S2), continuing the development program.