The efficient use of fodder and grassland as the basis of animal feed represents a way of raising productivity and reducing production costs. In this scenario, elephant-grass stands out among the most used forages in the intensive animal production systems in the world mainly due to its high productive potential, support capacity and nutritional quality. The purpose of this work was to estimate genetic parameters for the selection of elephant-grass (Pennisetum purpureum Schumach.) clones for forage production in two seasons, a period of water restriction and the total period of study. We evaluated 80 accessions of elephant-grass by means of the mixed-models methodology (REML/BLUP). The evaluation of DM yield (DMY) of the different genotypes were executed in edaphoclimatic conditions in Campos dos Goytacazes, Rio de Janeiro, Brazil. The Selegen-REML/BLUP software accomplished the statistical and genetic analyses. It was seen that the DMY trait was with a low estimate of coefficient of genotypic variation (3.08%), which demonstrates possible difficulties with the selection for this trait. Heritability-coefficient estimate was 0.3606 for the dry season and 0.4193 for the total period. Those results were the variation in that trait due to genetic causes. Although those values may not be considered of high magnitude, they are of great interest for the breeding mainly because it is a polygenic trait. In both periods, genotypes 7, 25, 41, 43, 57, 58, 62, 64, 68, and 77 stood out among the others, since it presented the highest genetic gains for DMY, which will enhance progress in the evaluated trait.
Elephant grass has high biomass production, with qualities suitable for conversion into bioenergy, but has long been used exclusively for animal feed and only in recent years has it become an energetic alternative. Therefore, it is necessary to select genotypes with potential for energy production. This study evaluated the effect of five harvest times (8, 12, 16, 20, and 24 weeks) on the yield and chemical composition related to biomass quality through combined polynomial regression analyses of the following elephant grass genotypes: Cubano Pinda, Mercker 86-México, Pusa Napier n°1, Mole de Volta Grande, P-241-Piracicaba, and King Grass. A completely randomized design with three replicates, in a split-plot arrangement, was adopted, including two factors (plots = genotypes, subplots = harvest times). The evaluated variables were whole-plant dry matter yield, in t ha -1 (DMY), percentage of neutral detergent fiber (%NDF), and percentage of acid detergent fiber (%ADF). The elephant-grass genotypes Cubano de Pinda, Mercker 86-México, and P-241-Piracicaba showed a linear first-degree effect as a function of the harvest intervals, indicating that they did not reach their maximum production potential. Genotypes Pusa Napier n°1, Mole de Volta Grande, and King Grass, in turn, had a linear second-degree effect. For the NDF variable, all genotypes showed a significant linear second-degree effect as a function of the harvest intervals, except P-241-Piracicaba, for which no regression was observed. For this genotype, there was a significant linear first-degree effect on the %ADF variable.
The elephant grass has gained prominence as one of the main forage species used for biomass production. Therefore, the aim of this study was to identify elephant grass genotypes with high energy biomass production potential by evaluating morpho-agronomic and biomass quality. The following traits were evaluated in this study: dry matter yield (DMY), percentage of whole-plant dry matter (%DM), percentage of neutral detergent fiber (%NDF), percentage of acid detergent fiber (%ADF); percentage of cellulose (%CEL), percentage of lignin (%LIG), percentage of carbon (%C), percentage of nitrogen (%N), and carbon: nitrogen ratio (C: N). Five different production ages were evaluated, and significant differences were observed for the variable DMY. The harvests performed at 20 and 24 weeks of age, provided the best response for biomass energy production (DMY) from elephant grass, averaging 20.50 and 23.77 t.ha −1. The genotypes that most stood out during the evaluation period at the five production ages were King Grass, Mole de Volta Grande, and Mercker 86-México. Genotypes Mole de Volta Grande and King Grass are the most suitable for elephant grass breeding programs aimed at biomass energy production in the conditions of Campos dos Goytacazes-RJ, Brazil.
The use of mixed models for evaluating diallel crosses is a highly timely option to the reliable prediction of progeny genetic values. In the sweet pepper crop, hybrids are commercially explored on a large scale, mainly because of their characteristics of economic importance. This study aimed to assess the potential of hybrids obtained from a partial diallel among five sweet pepper lines developed for the hydroponic cultivation system and two simple hybrids, by applying mixed models. It was performed crosses in the partial diallel scheme among the (L1B, L6, L7, L18, and L19) lines and the simple hybrids ‘Valdor’ and ‘Atlantis’. Plants were cultivated in hydroponic system with substrate and irrigated three times a day using nutrient solution. On the basis of mixed models, the following traits were assessed: mean fruit diameter (FD), mean fruit length (FL), mean fruit number per plant (FNP), mean fruit mass (FM), early yield (EYIELD), and mean fruit mass per plant (FMP). The L6 line was the one that showed the highest estimate of general combination capacity for FMP, FM, and EYIELD, proving to be promising for recommendation. The hybrid that provided the best specific combining ability for FD, FM, FMP, and EYIELD was L6 x ‘Valdor’. Triple hybrids were efficient to maximize yield for the traits of interest by the use of the mixed model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.