| Autor: |
Silva VB; Laboratório de Engenharia Agrícola, , , Brasil verabritosl@hotmail.com., Daher RF; Laboratório de Engenharia Agrícola, , , Brasil., Araújo MSB; Laboratório de Melhoramento Genético Vegetal, , , Brasil., Souza YP; Laboratório de Melhoramento Genético Vegetal, , , Brasil., Cassaro S; Laboratório de Engenharia Agrícola, , , Brasil., Menezes BRS; Departamento de Genética, Universidade Federal Rural do Rio de Janeiro, Seropédica, RJ, Brasil., Gravina LM; Laboratório de Engenharia Agrícola, , , Brasil., Novo AAC; Laboratório de Engenharia Agrícola, , , Brasil., Tardin FD; Empresa Brasileira de Pesquisa Agropecuária, Embrapa Agrossilvipastoril, Sinop, MT, Brasil., Júnior ATA; Laboratório de Melhoramento Genético Vegetal, , , Brasil. |
| Abstrakt: |
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. |
