Research Article Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes.

Abstract

ABSTRACT. Genetically improved cultivars of elephant grass need to be adapted to different ecosystems with a faster growth speed and lower seasonality of biomass production over the year. This study aimed to use selection indices using mixed models (REML/BLUP) for selecting families and progenies within full-sib families of elephant grass (Pennisetum purpureum) for biomass production. One hundred and twenty full-sib progenies were assessed from 2014 to 2015 in a randomized block design with three replications. During this period, the traits dry matter production, the number of tillers, plant height, stem diameter, and neutral detergent fiber were assessed. Families 3 and 1 were the best classified, being the most indicated for selection effect. Progenies 40, 45, 46, and 49 got the first positions in the three indices assessed in the first cut. The gain for individual 40 was 161.76% using Mulamba and Mock index. The use of selection indices using mixed models is advantageous in elephant grass since they provide high gains with the selection, which are distributed among all the assessed traits in the most appropriate situation to breeding programs.

Morphological characterization of Elephant grass (Pennisetum purpureum Schumach) ecotypes collected in Chiapas, Mexico

“…Elephant grass accessions have high genetic diversity, which is distributed in different groups. They have various uses, including the production of biofuels (Silva et al, 2017;Rocha et al, 2017;López et al, 2014) and the production of ethanol (Scholl et al, 2015). Likewise, their lignin, cellulose, and ash contents are suitable for direct combustion (Morais et al, 2009) and they can be used to make paper, due to their amount of lignocellulosic biomass (Madakadze et al, 2010).…”