Breeding for drought tolerance is a challenging task that requires costly, extensive, and precise phenotyping. Genomic selection (GS) can be used to maximize selection efficiency and the genetic gains in maize (Zea mays L.) breeding programs for drought tolerance. Here, we evaluated the accuracy of genomic selection (GS) using additive (A) and additive + dominance (AD) models to predict the performance of untested maize single-cross hybrids for drought tolerance in multi-environment trials. Phenotypic data of five drought tolerance traits were measured in 308 hybrids along eight trials under water-stressed (WS) and well-watered (WW) conditions over two years and two locations in Brazil. Hybrids' genotypes were inferred based on their parents' genotypes (inbred lines) using single-nucleotide polymorphism markers obtained via genotyping-by-sequencing. GS analyses were performed using genomic best linear unbiased prediction by fitting a factor analytic (FA) multiplicative mixed model. Two cross-validation (CV) schemes were tested: CV1 and CV2. The FA framework allowed for investigating the stability of additive and dominance effects across environments, as well as the additive-by-environment and the dominance-by-environment interactions, with interesting applications for parental and hybrid selection. Results showed differences in the predictive accuracy between A and AD models, using both CV1 and CV2, for the five traits in both water conditions. For grain yield (GY) under WS and using CV1, the AD model doubled the predictive accuracy in comparison to the A model. Through CV2, GS models benefit from borrowing information of correlated trials, resulting in an increase of 40% and 9% in the predictive accuracy of GY under WS for A and AD models, respectively. These results highlight the importance of multi-environment trial analyses using GS models that incorporate additive and dominance effects for genomic predictions of GY under drought in maize single-cross hybrids.

Water deficit is one of the most common causes of severe crop‐production losses worldwide in maize (Zea mays L.). The main goal of this study was to infer about genotype × environment interaction (G × E) and to estimate genetic correlations between drought tolerance traits in maize using factor analytic (FA) multiplicative mixed models in the context of multi‐environment trial (MET) and multi‐trait multi‐environment trial (MTMET) analyses. The traits measured were: grain yield (GY), ears per plot (EPP), anthesis‐silking interval (ASI), female flowering time (FFT), and male flowering time (MFT). Three‐hundred and eight hybrids were evaluated in a total of eight trials conducted under water‐stressed (WS) and well‐watered (WW) conditions across 2 yr and two locations in Brazil. For most of the traits (GY, ASI, and FFT), the magnitude of the genetic variances differed across WS and WW conditions. Genetic correlations between water conditions for FFT and MFT were 0.81 and 0.82, respectively, indicating that it might be unnecessary to measure these traits in both water conditions. Grain yield and EPP showed moderate to high G × E, with genetic correlations of 0.57 and 0.39 between WS and WW conditions, respectively, which suggested that gene expression was not consistent across different water regimes. Therefore, it is necessary to evaluate these traits under both water conditions. Genetic correlations between pairs of traits, in general, were higher under WS conditions compared with WW conditions. Grain yield exhibited moderate correlations with EPP (r = 0.62) and FFT (r = −0.42) under WS conditions. The FA models can be a useful tool for MET and MTMET analyses in maize breeding programs for drought tolerance.

Vitamin A deficiency causes xerophthalmia in preschool-aged children worldwide. The objective of this study was to estimate the genetic parameters that would be useful in selecting parent plants for developing productive hybrids with higher levels of provitamin A in the maize kernel. A complete 7 9 7 diallel mating scheme was used to generate 21 single-cross hybrids. The F 1 crosses and check hybrids were evaluated in complete block design across three different Brazilian environments, and carotenoid content was analyzed by high performance liquid chromatography. General combining ability effects were significant for all traits except a-carotene This result indicates that the contribution of the additive effect was more important for provitamin A and other carotenoids and, consequently that there is high chance of improving this trait through recurrent selection methods. Line 3 produced the highest level of kernel provitamin A among the inbred lines evaluated and also demonstrated the potential to contribute to the development of genetic materials with a good performance for provitamin A. Inbred lines 1, 6, and 7 showed a higher concentration of favorable alleles for grain yield, and inbred lines 3 and 6 exhibited a higher concentration of favorable alleles for b-carotene. Hybrid 1 9 3 performed well in terms of provitamin A and grain yield and combination 2 9 3 was the best performer in terms of lutein content.

2019. Variability in herbivore-induced defence signalling across different maize genotypes impacts significantly on natural enemy foraging behaviour.

e PAULO CÉSAR LEMOS DE CARVALHO 4 RESUMO -Três ciclos de seleção entre e dentro de progênies de meios-irmãos foram praticados na população de milho (Zea mays L.) de alta qualidade protéica CMS-52, nos tabuleiros costeiros dos estados de Sergipe e Bahia, no período de 1995 a 1997, visando à obtenção de uma população melhor adaptada às condições edafoclimáticas da região. As progênies foram avaliadas em látice simples 14 x 14, com recombinação das progênies superiores, dentro do mesmo ano agrícola, de modo a se obter um ciclo por ano. Os valores dos parâmetros genéticos decresceram do ciclo original para o ciclo I, mantendo-se no ciclo II com magnitudes semelhantes ao ciclo I. As altas magnitudes desses parâmetros genéticos, as altas médias de produtividades das progênies, e o ganho médio esperado com a seleção entre e dentro de progênies, por ciclo de seleção (12,3%), mostram o grande potencial da população em responder à seleção, o que permitirá a obtenção de uma população mais produtiva e melhor adaptada às condições edafoclimáticas da região. A magnitude da interação progênies x locais evidenciou a importância de se avaliarem as progênies em mais de um local, para melhorar a eficiência do processo seletivo e obter estimativas mais consistentes dos componentes da variância.Termos para indexação: Zea mays, parâmetros genéticos, variação genética, teste de progênie, seleção, métodos de melhoramento. THREE CYCLES SELECTION AMONG AND WITHIN HALF SIB PROGENIES IN THE MAIZE POPULATION CMS-52ABSTRACT -Three cycles of selection among and within half-sib progenies were carried out in the high quality protein maize (Zea mays L.) population CMS-52, at the tabuleiros costeiros of Sergipe and Bahia, Brazil, during the period of 1995 to 1997. The work aimed at obtaining a better adapted population for the regional environment. The progenies were evaluated on a 14 x 14 látice design. Recombination of the superior progenies was processed within the same year in order to get one cycle per year. The values of the genetic parameters decreased from the original cycle to cycle I, keeping at cycle II similar magnitudes of cycle I. The high magnitudes of the genetic parameters, the high productivity means of progenies, and the averaged gain expected from the selection among and within progenies per selection cycle (12.3%) show the high potential of the population to respond to selection, which will permit to attain a higher yielding population, better adapted to the regional environment. The high progeny x location interaction showed the importance for progeny evaluation in more than one location, to increase the efficiency of the selection process and to obtain more accurate estimates of variance components.