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.

The aim of this study was to identify maize haploid plants and compare the efficiency of identification of maize haploid plants using the R1-nj morphological marker, plant vigor, flow cytometry, chromosome counting, and microsatellite molecular markers under tropical conditions. We also established a protocol for chromosome duplication in maize haploid plants. Fourteen

Understanding the crop diversity is critical for a successful breeding program, helping to dissect the genetic relationship among lines, and to identify superior parents. This study aimed to investigate the genetic diversity of maize (Zea mays L.) inbred lines and to verify the relationship between genetic diversity and heterotic patterns based on hybrid yield performance. A total of 1,041 maize inbred lines were genotyped-by-sequencing, generating 32,840 quality-filtered single nucleotide polymorphisms (SNPs). Diversity analyses were performed using the neighbor-joining clustering method, which generated diversity groups. The clustering of lines based on the diversity groups was compared with the predefined heterotic groups using the additive genomic relationship matrix and unweighted pair group method with arithmetic mean. Additionally, the genetic diversity of lines was correlated with yield performance of their corresponding 591 single-cross hybrids. The SNP-based genetic diversity analysis was efficient and reliable to assign lines within predefined heterotic groups. However, these genetic distances among inbred lines were not good predictors of the hybrid performance for grain yield, once a low but significant Pearson's correlation (.22, p-value ≤ .01) was obtained between parental genetic distances and adjusted means of hybrids. Thus, SNP-based genetic distances provided important insights for effective parental selection, avoiding crosses between genetically similar tropical maize lines.

Artificial chromosome duplication is one of the most important process in the attainment of doubled haploids in maize. This study aimed to evaluate the induction ability of the inducer line KEMS in a tropical climate and test the efficiency of the R1-Navajo marker by flow cytometry to evaluate two chromosome duplication protocols and analyze the development of the doubled haploids in the field. To accomplish this goal, four genotypes (F1 and F2 generations) were crossed with the haploid inducer line KEMS. The seeds obtained were selected using the R1-Navajo marker and subject to two chromosome duplication protocols. Duplication was confirmed using flow cytometry. The percentages of self-fertilized plants after duplication as well as the quantities of doubled haploid seeds obtained after the self-fertilization processes were analyzed. It was observed that the germplasm influences haploid induction but not the duplication rates of the tested protocols. Protocol 2 was more efficient for the duplication of haploids, in the percentage of self-fertilized plants after duplication, and in the attainment of doubled haploid lines. Moreover, the haploid inducer line KEMS can produce haploids in a tropical climate. Other markers, in addition to the R1-Navajo system, should be used in the selection of haploid seeds.Index terms: R-Navajo; colchicine; induction of maternal haploids; Zea mays. RESUMOA duplicação cromossômica artificial está dentre as etapas mais importantes na obtenção de duplo-haploides em milho. Este estudo objetivou avaliar a capacidade de indução da linhagem indutora KEMS em clima tropical e testar a eficiência do marcador R1-navajo por meio de citometria de fluxo; avaliar dois protocolos de duplicação cromossômica e, analisar o desenvolvimento dos haploides duplicados no campo. Para isso, quatro genótipos (gerações F1 e F2) foram cruzados com a linhagem KEMS. As sementes obtidas foram selecionadas pelo marcador R1-navajo e submetidas a dois protocolos de duplicação cromossômica. A duplicação foi confirmada por meio de citometria de fluxo. As porcentagens de plantas autofecundadas após duplicação foram analisadas, bem como as quantidades de sementes duplo-haploides obtidas após as autofecundações. Foi observado que o germoplasma influencia a indução de haploides, mas não na taxa de duplicação dos protocolos testados. O protocolo 2 foi mais eficiente na duplicação de haploides, na porcentagem de plantas autofecundadas após duplicação, e na obtenção de linhagens duplo-haploides. Além disso, a linhagem indutora KEMS pode induzir haploides em clima tropical. Outros marcadores além do sistema do R1-navajo devem ser utilizados na seleção de sementes haploides.Termos para indexação: R-navajo; colchicina; indução de haploides maternos; Zea mays.

Genomic selection has been implemented in several plant and animal breeding programs and it has proven to improve efficiency and maximize genetic gains. Phenotypic data of grain yield was measured in 147 maize (Zea mays L.) single‐cross hybrids at 12 environments. Single‐cross hybrids genotypes were inferred based on their parents (inbred lines) via single nucleotide polymorphism (SNP) markers obtained from genotyping‐by‐sequencing (GBS). Factor analytic multiplicative genomic best linear unbiased prediction (GBLUP) models, in the framework of multienvironment trials, were used to predict grain yield performance of unobserved tropical maize single‐cross hybrids. Predictions were performed for two situations: untested hybrids (CV1), and hybrids evaluated in some environments but missing in others (CV2). Models that borrowed information across individuals through genomic relationships and within individuals across environments presented higher predictive accuracy than those models that ignored it. For these models, predictive accuracies were up to 0.4 until eight environments were considered as missing for the validation set, which represents 67% of missing data for a given hybrid. These results highlight the importance of including genotype‐by‐environment interactions and genomic relationship information for boosting predictions of tropical maize single‐cross hybrids for grain yield.

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The breeding program of Urochloa ruziziensis evaluates many genotypes in initial phases. Evaluations through grades might make the selection less costly. The aim of this study was to verify the efficiency of visual selection for green biomass yield in relation to different selection strategies, such as mass selection by phenotypic mean, BLUP (Best Linear Unbiased Prediction) and at random. For this purpose, 2,309 regular genotypes were evaluated in an augmented block design in two cuts. The evaluators gave grades for plant vigor, and later, the plots were measured for green biomass yield. The coincidences of the selected genotypes were estimated by different selection strategies. Then, 254 clones of the genotypes selected in different strategies were evaluated in a clonal test in a triple lattice design in four cuts. The statistical analyses were performed in SAS using the Mixed procedure. The regular genotype level and clone-mean basis heritabilities were 31.16 and 62.91%, respectively, for green mass yield. The expected selection gains were 21.09% (visual), 25.43% (phenotypic mean), and 27.5% (BLUP). Moreover, the realized heritabilities for these strategies were 15.58, 11.87, and 15.86%, respectively, which might be associated with genotype by environment interaction. Therefore, the visual selection could be a useful strategy in initial phases of a U. ruziziensis breeding program because the efficiency was moderate to high in relation to phenotypic mean and BLUP.