Phenotypic, additive genetic and environment correlations of maize landraces populations in family farm systems

Abstract

Knowledge of the association between characters is very important in the genetic breeding programs, but there is limited information about correlations between traits in maize landraces in the current literature. The objectives of this study were to estimate phenotypic, additive genetic and environment correlations among traits in maize landraces, which were cultivated in family farm systems, in order to guide the participatory breeding on maize landraces. Between 294 and 400 half-sib progenies from the six populations were evaluated, subdivided in triple 7X7 and 10X10 lattice design, respectively, with single row plots of 4 m long and spaced 1.00 × 0.20 m. Estimates of correlation coefficients are reported for nine traits: grain yield (GY), relation grain weight per ear weight (GE), ears per plant (EP), days to flower (DF), plant height (PH), ear height (EH), percentage of root loding (%L), percentage of stalk loding (%BS) and percentage of damaged ears (%DE). A high number of additive genetic correlation (r A ) was obtained between grain yield and the other traits, in maize landraces populations, cycles and locations. For grain yield, the highest averages of the r A estimate were with EP (0.67), GE (0.47) and %DE (-0.63). In contrast to the current published researches, negative correlations between grain yield and days to flower were observed. Key words: Zea mays L., population, recurrent selection, participatory breeding Correlações fenotípicas, genéticas aditivas e ambientais de populações de milho crioulo em sistemas de agricultura familiar RESUMO: O conhecimento da associação entre caracteres é de grande importância nos programas de melhoramento genético, contudo a literatura apresenta limitadas informações sobre correlações em populações de milho crioulo. Os objetivos deste estudo foram estimar correlações fenotípicas, genéticas aditivas e ambientais entre caracteres de populações de milho crioulo, cultivados em sistemas de agricultura familiar, para orientar o programa de melhoramento genético participativo. Entre 294 e 400 de progênies de meios-irmãos de seis populações, foram avaliadas em látices triplos 7X7 e 10X10, respectivamente, com parcelas de 4 m de comprimento e espaçadas 1,00 × 0,20 m. Os coeficientes de correlações foram estimados para nove características: produtividade de grãos total (GY), relação peso de grãos por peso de espiga (GE), nº de espigas por planta (EP), nº de dias do florescimento (DF), altura da planta (PH), altura espiga (EH), porcentagem de acamamento (%L), porcentagem de colmos quebrados (%BS) e porcentagem de espigas danificadas (%DE). Houve um alto número de correlação genética aditiva (r A ) entre produtividade de grãos e as demais características, nas populações de milho crioulo, ciclos e locais. As maiores médias das estimativas r A para o produtividade de grãos foram com EP (0,67), GE (0,47) e DE% (-0,63). Diferentemente dos trabalhos publicados, foram observadas correlações negativas entre produtividade de grãos e dias para florescimento. Palavras-chave: Z...

Association studies between grain yield and agronomic traits of a MARS maize (Zea mays L.) population under drought and non-stress condition

“…Several maize breeders have used this method for identifying secondary traits as opposed to the use of genetic correlation (Barros et al, 2010;Chinnadurai and Pothraj, 2011;Begum et al, 2016;Baretta et al, 2016, Talabi et al, 2017Matin et al, 2017). However, the use of path coefficient analysis to identify and validate secondary traits for selection of improved grain yield under water stress and non-stress condition remains a relevant research focus in maize breeding Edmeades, 1993, 1996;Bänziger and Lafitte, 1997;Badu-Apraku et al, 2004).…”

Path analysis for morphological characters and grain yield of maize hybrids

“…Literature presents several works that use this technique by maize breeders (Carvalho et al, 2001; Barros et al, 2010;Munawar et al, 2013;Valizadeh and Bahrampour, 2013). However, such studies are still extremely important, because different population genetic structures have been considered.…”

On testing genetic covariance via the mean cross-products ratio

“…The authors performed the Student's t-test to access significance. Likewise, and Barros et al (2010) also tested genetic correlations among maize variables by using the Student's t-test. Ajayi et al (2014) tested genotypic correlations among cowpea variables using the t-test.…”

“…The authors also pointed out that the sampling variance of a genetic correlation is quite complex. Some authors (LEMOS et al, 1992;MALIK et al, 2005;BARROS et al, 2010;AJAYI et al, 2014) have also tested genetic correlation through the Student's t-test. Nevertheless, there is some misunderstanding about the degrees of freedom associated with the genetic correlation, as verified by (FERREIRA et al, 2008).…”