Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/58553
Title: Avaliação e seleção de progênies S0:1 de milho derivada de híbridos de milho
Other Titles: Evaluation and selection of S0:1 corn progenies derived from corn hybrids
Authors: Souza, João Cândido de
Nunes, José Airton Rodrigues
Souza, João Candido de
Garbuglio, Deoclécio Domingos
Keywords: Milho - Melhoramento genético
Seleção
Linhagens promissoras
Melhoramento de plantas
Maize - Genetic improvement
Selection
Promising lines
Plant breeding
Zea mays L.
Issue Date: 16-Nov-2023
Publisher: Universidade Federal de Lavras
Citation: SAMPO, M. da G. C. Avaliação e seleção de progênies S0:1 de milho derivada de híbridos de milho. 2023. 40 p. Dissertação (Mestrado em Genética e Melhoramento de Plantas)–Universidade Federal de Lavras, Lavras, 2023.
Abstract: The present study aimed to evaluate 500 S0:1 maize progenies in order to select the best progenies based on genetic parameter estimates using mixed models approaches. The experiment was conducted at Muquém Farm, located at the Center for Scientific and Technological Development in Agriculture at the Federal University of Lavras (UFLA). A total of 500 progenies were analyzed, derived from 10 populations of the UFLA maize genetic improvement program, with 50 progenies from each population. For the purpose of comparing means, four partially inbred lines were used as controls. The experimental design adopted was Alpha lattice (12x42), with two replications, and plots consisting of two rows, each measuring 2 meters in length, with a spacing of 0.6 meters between rows and 0.25 meters between plants. The following traits were evaluated: plant height (AP) and ear height (AE), foliar disease incidence (ID), and grain yield (PROD). Statistical analyses were conducted using the R software, which allowed for the estimation of genetic parameters, genotypic correlations, and expected gains through selection. Deviance analysis via the likelihood ratio test (LRT) at a 1% significance level indicated that traits AE, PROD, and ID2 differed significantly among progenies, except for the trait AP and ID1, which did not show significant differences. To assess experimental accuracy and quality, selective accuracy was calculated, ranging from 0.75 (P7) to 0.87 (P8) for PROD, which is considered of high magnitude. As for AE, there was no r ̂g ̂g in P 4, and the highest value was 0.69 (P6), classified as moderate magnitude. For ID2, there was no r ̂g ̂g in Populations (4, 7, and 8), and the highest value was 0.59 (P6), also classified as moderate magnitude. The genetic parameter estimates revealed variability among populations, allowing for the selection of superior genotypes. Genotypic correlation was significantly positive for PROD and AP in P2 (0.413), of moderate magnitude, and also in P6 (0.353) and P7 (0.358), but of low magnitude. Regarding AP and AE, there was a significant positive correlation in all populations, with values ranging from 0.74 (P2) to 0.80 (P6), considered of strong magnitude. Direct selection allowed for the choice of four populations (P4, P5, P6, and P7), from which 10 progenies were selected in each population, using a selection intensity of 20%. This resulted in gains with selection for the PROD trait of approximately 995.42 (26.33%) for P4, 560.04 (16.19%) for P7, 410.77 (14.02%) for P6, and 40.22 (1.35%) for P5. The 10 selected progenies showed the best gain estimates in grain yield, making them promising for the continuation of the maize genetic improvement program.
URI: http://repositorio.ufla.br/jspui/handle/1/58553
Appears in Collections:Genética e Melhoramento de Plantas - Mestrado (Dissertações)



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