ABSTRACT The objective of this study was to estimate the genetic parameters and predict selection of genetic gains and genetic diversity of 12 Andropogon lateralis ecotypes collected in the State of Rio Grande do Sul, Brazil. To estimate genetic parameters and predict selection gains, the REML/BLUP technique was applied. Genetic diversity among the ecotypes was evaluated by two clustering methods (optimization and hierarchical) and principal component (PC) analysis, the latter method also used to discard variables. The genetic parameters studied showed high potential for selection of important agronomic forage traits for livestock production. Results showed that the 12 A. lateralis Nees ecotypes exhibited high genetic variability for the studied forage characters and indicated parental prosperity for crosses within the genetic breeding program. Principal component analysis showed that number of total vegetative tillers, leaf:stem ratio, number of reproductive tillers, and leaf dry matter yield accounted for 80.6% of the observed variation in PC1. These variables are important characteristics for quantifying the dry matter production and nutritional value of forage plants, and they can help to discriminate amongst ecotypes. Ecotypes sourced from the Pelotas, Piratini, Passo Fundo, Bagé, and Montenegro regions showed superior forage production when evaluated by the BLUP methodology. Therefore, this group was identified as the most suitable for selection and crossing purposes. Tocher’s cluster analysis grouped the ecotypes into five divergent groups. Principal component and UPGMA hierarchical methods were also efficient at separating the ecotypes. 1 Sul Brazil REMLBLUP REML applied optimization PC (PC A program tillers leafstem stem ratio 806 80 6 80.6 PC1 plants Pelotas Piratini Fundo Bagé methodology Therefore purposes Tochers Tocher s groups 8 80.

ABSTRACT The objective of this study was to verify the repeatability of the expression of forage characters in intraspecific hybrids of Paspalum notatum Flügge to aid early selection. Across five harvests, plant height, tiller population density, leaf dry matter, stem dry matter, inflorescence dry matter, total dry matter, and growth habit were quantified for five parents, 189 hybrids, and a commercially available cultivar as a control (n = 195). Analysis of variance, principal components analysis, and structural analysis methods were used to determine the repeatability coefficients. The repeatability coefficients ( ρ ^) for all evaluated characteristics generated by the different methods were between 0.05 (ANOVA II) and 0.95 (PCACov). For most of the characteristics studied, repeatability coefficients and determination coefficients were considered high. The repeatability coefficients estimates obtained for the eight characteristics evaluated with the ANOVA I and II methods were almost always lower than those obtained by PCA and structural analysis methods. Based on the covariance matrix, the principal component method generated higher estimates than those produced by ANOVA or structural analysis. Assuming a minimum 80% reliability to verify the relative superiority of the hybrids across all assessed traits, the five harvests proved adequate for selecting the optimal plant materials to advance to the next phase of the breeding program. However, reliable early selection for leaf dry matter, leaf:stem ratio, and total dry matter required a minimum of two harvests. The genetic parameters (h2 and CVg) showed a favorable scenario for direct selection to increase forage production. height density parents 18 n 195. 195 . 195) variance ^ 005 0 05 0.0 095 95 0.9 PCACov. PCACov (PCACov) studied high matrix 80 traits program However leafstem ratio h2 h (h CVg production 1 19 00 0. 09 9 (PCACov 8

Abstract The Paspalum genus has potential for further genetic improvement because of its adaptability to different ecosystems and production of high yields for grazing livestock. We estimate the genetic parameters of 195 intraspecific P. notatum hybrids using Restricted Maximum Likelihood (REML), followed by selection based on Best Linear Unbiased Prediction (BLUP) through multivariate analysis. The intraspecific hybrids studied showed considerable genetic variability in the evaluated forage traits, displaying their potential for progression in subsequent stages of the genetic improvement program. Notably, plant height emerged as an important trait for indirect selection to enhance forage production. The use of the REML/BLUP procedure proves to be a robust tool for data analysis, particularly for perennial species. Furthermore, multivariate analysis based on BLUPs should be used in the selection process within breeding programs. Based on the BLUP values, hybrids D3, D16, C17, C2 and B17 were identified as superior for forage production, and they hold promise for future breeding programs for future breeding initiatives aimed at direct selection to improve yield. livestock 19 P REML, REML , (REML) (BLUP traits program Notably REMLBLUP species Furthermore values D3 D D16 C17 C B B1 yield 1 (REML D1 C1