Maize grain yield is frequently constrained by water scarcity, particularly in tropical regions characterized by irregular rainfall patterns. Dissecting the genetic basis of drought-related traits remains challenging because their expression is strongly influenced by environmental conditions. In this study, we applied a multi-environment multi-locus genome-wide association study (MEML-GWAS) to identify genomic regions associated with drought-related traits in tropical maize. The association panel comprised 190 inbred lines from the Embrapa breeding program, which were genotyped with 500,108 GBS-derived SNPs, and crossed with two tester lines. Phenotypic data corresponded to the performance of the testcross hybrids, divided in Dent and Flint heterotic groups, evaluated across two years at two locations in Brazil under well-watered and water-stressed conditions. Traits analyzed included grain yield, anthesis-silking interval, female and male flowering time, and plant and ear height. Drought stress reduced grain yield by approximately 50% and increased the anthesis-silking interval by about two days. A total of 179 significant SNP-trait associations were detected, of which 166 showed significant SNP-by-environment interaction effects, while 13 displayed stable effects across environments. Several associations were detected specifically under water-stressed conditions, highlighting genomic regions potentially involved in drought adaptation. Functional annotation revealed candidate genes previously implicated in abiotic stress responses, including ZmTIP1, which encodes an S-acyltransferase regulating root hair development and drought tolerance. Among the novel candidate genes, GRMZM2G159125, encoding a phospholipase D, emerged as a particularly promising candidate due to its strong association with grain yield and its role in membrane lipid signaling pathways related to stress responses. Although a few associations overlapped genomic regions previously reported for drought tolerance in maize, most loci represent potentially novel genetic factors that may contribute to improving drought resilience in tropical maize breeding programs.

- The objective of this work was to select maize hybrids using the GGE biplot analysis, as well as to evaluate their stability and adaptability in different environments of the North and Midwest regions of Brazil. Thirty-six maize hybrids were evaluated in 2018, in the following five environments in the Northern and Midwestern regions, respectively: in the municipality of Vilhena, in the state of Rondonia; and in the municipalities of Sorriso, Sinop, Alta Floresta, and Carlinda, in the Northern region of the state of Mato Grosso. The experimental design was a randomized complete block design. The analysis of variance was performed, and adaptability and stability were estimated by the GGE biplot method based on grain yield performance. A significant interaction between genotypes and environments was detected, and the biplot analysis was efficient in explaining 62.74% of the total variation in the first two principal components, with the formation of three macroenvironments. The 1P2227, 'BRS 3042', and 1P2265 hybrids showed high yield, responsiveness, and stability in the evaluated environments. The DKB310VTPRO2 hybrid was the most unstable genotype. The recommended hybrids are: DKB310 for the Sorriso and Vilhena macroenvironment; 1M1810 and 1O2106 for the Carlinda environment; and 1M1807 for the Sinop environment.

The objective of the present work was to evaluate the physiological quality in seeds of haploidy inducers of different types and origins. To this end, between December 2015 and March 2016, a series of physiological quality assessments were conducted on nine genotypes inducing haploidy in corn, namely: the gymnogenetic inducers Stock 6, TAIL P1 and TAIL P2; the hybrid between the TAIL P1 x TAIL P2 inductors; the hybrid TAIL P2 x TAIL P1, analogous to the previous hybrid, but with inversion of the female parent at the crossing; and androgenetic inducers W23, 90109 igig, 91202 igig and 91207 igig. The tests carried out were germination, accelerated aging, emergence in a bed, emergence index, fresh and dry mass, length of aerial part and root and the ratio between these characteristics, the humidity and the weight of 100 seeds. The results indicated that the physiological quality was improved throughout the selection for greater haploid induction. The haploidy induction system (andorgenetic or gymnogenetic) does not interfere with physiological quality, however the results obtained reinforce the need for care in the multiplication and conservation of haploidy inducing seeds in tropical conditions for their use in breeding.

En los últimos 30 años (cosechas agrícolas de 1991/92 a 2021/2022), el maíz ha vivido una verdadera revolución en Brasil. Actualmente, el país se ha consolidado como el tercer productor y segundo exportador de este cereal, con una producción de más de 100 millones de toneladas de este grano por año agrícola. En este período, el cultivo de soja se destaca como el gran impulsor de los avances tecnológicos, llevando al maíz y a otros cultivos a posiciones más destacadas y transformando los sistemas de producción de granos; que antes eran de monocultivo o rotación, a sistemas más intensificados, con dos (o más) cultivos agrícolas por año en la misma área. La región del Cerrado brasileño, antes considerada no apta para la agricultura, es hoy el gran granero de la producción de granos de Brasil. En estas tres décadas de escalada en la producción de maíz, se destacan algunos hitos legales y tecnológicos, como la Ley de Protección de Cultivares y su reglamento (desde 1997), el Sistema de Siembra Directa, el cultivo de maíz en segunda cosecha o “safrinha” (después de la soja) y el uso de biotecnologías. Estos factores fueron determinantes para que el crecimiento de la producción de maíz superara en más de 3,6 veces el volumen de la campaña agrícola 1991/92, mientras que el área destinada al cultivo de maíz aumentó sólo 1,5 veces. Los incrementos en la productividad están ligados a tecnologías y conocimientos aplicados a la gestión de los sistemas productivos, en el binomio soja-maíz, y no solo en un cultivo aislado; permitiendo mayores avances en la producción bruta de ambos granos (rendimientos recientes en la cosecha de maíz son unas 2,5 veces mayores que hace 30 años). Este trabajo presenta datos y hechos que permitieron a Brasil salir de una posición de vulnerabilidad, en cuanto a la oferta de grano de maíz, para convertirse en un actor importante en la producción y comercialización de este cereal a nivel mundial.

The development of resistant cultivars is one of the strategies applied in pest control. The method has the advantages of reduced cost and the lack of unwanted effects on the environment. Over the past decades, significant effort has been made toward developing the natural maize resistance to pests by evaluating germplasm and cultivar selection. This review highlights a maize breeding program, potential, advances, and challenges in addressing these characteristics. Also, it describes the main components and procedures applied in the mass rearing of insect pests of maize, artificial diets, techniques of artificial infestation employed in genotype selection, and methods to evaluate the mechanisms and causes of resistance. Studies on the inheritance of resistance, the breeding methods, and the potential for integrating classical and transgenic resistance are also emphasized.

The objective of this work was to use the partial diallel methodology to compare double-haploid lines (DHs) of maize with lines obtained by traditional methods. To obtain hybrids, five double-haploid lines, used as female parents, were crossed with four testers, as male parents. Twenty hybrids were obtained from double-haploid lines, being: 8 experimental, and 8 commercial from Embrapa and 4 from other companies. Were evaluated; final stand (ST), tipping and breaking (TOMB), plant height (AP), ear insertion height (AE), grain moisture at harvest (UG) and total grain weight (PROD). Analysis of variance was performed, unfolding the degrees of freedom of the genotype, Tukey test at 5% probability, and the decomposition of the sums of squares of the treatments into general and specific combining ability for testers and DH lines. AP and AE were higher in hybrids derived from DHs lines, while productivity and final stand were higher in experimental controls. However, some hybrids, such as the hybrid DH1800007 presented higher PROD than commercial and experimental controls. The data obtained demonstrate that hybrids derived from double-haploid lines, in addition to accelerating the time to obtain new cultivars, enable the development of hybrids with superior agronomic performance.

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.

The objective of this work was to evaluate commercial maize hybrids, under conventional sprinkler irrigation, in two sowing seasons (July and August 2017), in the municipality of Teresina, Piauí. A randomized block design was used, with two replications and 39 treatments (commercial maize hybrids). The characteristics evaluated were grain yield, water use efficiency, number of ears and number of grains per area. For the experiment with sowing done in July 2017, the average grain yield was 9.82 Mg ha-1 and the water use efficiency was 1.9 kg m-3, which are, respectively, 4.7 % and 15.8 % higher in relation to the experiment with sowing done in August 2017. Regardless of the sowing season, grain yields over 10.0 Mg ha-1 of three hybrids (LG 6418, CD 3880 PW and 2A 401 PW) stand out. The yield components, number of kernels per ear and grain mass per ear, show high values of correlation (over 0.80) with grain yield.

Genotyping-by-sequencing (GBS) datasets typically feature high rates of miss-ingness and heterozygote undercalling, prompting the use of data imputation. We compared the accuracy of four imputation methods—NPUTE, Beagle, k - nearest neighbors imputation (KNNI), and fast inbreed line library imputation (FILLIN)—using GBS data of maize ( Zea mays L.) inbred lines, genotyped using different multiplexing levels. Two strategies for SNP-calling and genotype imputation were evaluated. First, only lines genotyped through 96-plex were used for single nucleotide polymorphism (SNP) discovery, whereas both 96-and 384-plex were simultaneously used in the second strategy. In the first genotype imputation strategy, only the 96-plex lines were imputed, then the remaining lines were appended (96-plex-imputed plus 384-plex) and then imputed. In the second imputation strategy, we jointly imputed both datasets. We also investigated the impacts of including heterozygous genotypes and distinct rates of missing genotypes per locus. The different SNP-calling strategies and percentage of missing data did not substantially affect the imputation accuracy. However, the different imputation strategies showed a substantial effect. Generally, imputations were less accurate for heterozygotes. The scenario 96-plex-imputed plus 384-plex showed accuracies similar to the 96-plex scenario. Beagle and NPUTE produced the highest accuracies. Our results indicate that combining SNP-calling and imputation strategies can enhance genotyping in a cost-effective manner, resulting in higher imputation accuracies.

Weighted outperformed unweighted genomic prediction using an unbalanced dataset representative of a commercial breeding program. Moreover, the use of the two cycles preceding predictions as training set achieved optimal prediction ability. Predicting the performance of untested single-cross hybrids through genomic prediction (GP) is highly desirable to increase genetic gain. Here, we evaluate the predictive ability (PA) of novel genomic strategies to predict single-cross maize hybrids using an unbalanced historical dataset of a tropical breeding program. Field data comprised 949 single-cross hybrids evaluated from 2006 to 2013, representing eight breeding cycles. Hybrid genotypes were inferred based on their parents’ genotypes (inbred lines) using single-nucleotide polymorphism markers obtained via genotyping-by-sequencing. GP analyses were fitted using genomic best linear unbiased prediction via a stage-wise approach, considering two distinct cross-validation schemes. Results highlight the importance of taking into account the uncertainty regarding the adjusted means at each step of a stage-wise analysis, due to the highly unbalanced data structure and the expected heterogeneity of variances across years and locations of a commercial breeding program. Further, an increase in the size of the training set was not always advantageous even in the same breeding program. The use of the two cycles preceding predictions achieved optimal PA of untested single-cross hybrids in a forward prediction scenario, which could be used to replace the first step of field screening. Finally, in addition to the practical and theoretical results applied to maize hybrid breeding programs, the stage-wise analysis performed in this study may be applied to any crop historical unbalanced data.

ABSTRACTWater 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.

RESUMO - O presente estudo teve por objetivo determinar a retenção de carotenoides em milho biofortificado com carotenoides precursores de vitamina A (ProVA) processado através da moagem a seco e nos derivados canjica, fubá e creme de milho, durante o armazenamento pós-processamento por 24 dias. O perfil de carotenoides foi determinado por cromatografia líquida de alta eficiência (CLAE) e o total de carotenoides precursores de vitamina A foi quantificado a partir das concentrações de α-caroteno, β-caroteno e β-criptoxantina. Os produtos da moagem via seca dos grãos de milho biofortificado (BRS 4104) apresentaram médias percentuais de retenção real de carotenoides totais (CT) de 75,37% (canjica), 73,51% (fubá) e 59,47% (creme) em relação aos grãos, enquanto para carotenoides ProVA os percentuais foram de 74,20% (canjica), 75,21% (fubá) e 60,55% (creme), evidenciando, em média, 30% de perdas como efeito da moagem a seco na retenção de carotenoides presentes nos grãos de milho. Durante o armazenamento ao longo do período de 24 dias ocorreu diminuição linear da retenção de CT e de ProVA nos três derivados estudados. Menores concentrações de carotenoides totais e ProVA nos produtos da moagem via seca de milho (canjica, fubá e creme de milho) e a redução na retenção dessas substâncias observadas durante armazenamento devem ser consideradas, quando da utilização de produtos do milho biofortificado como estratégia complementar em programas nutricionais para redução da deficiência de vitamina A em humanos.Palavras-chave: Zea mays, processamento, degradação, pró-vitamina A, compostos bioativos.CAROTENOIDS RETENTION IN BIOFORTIFIED MAIZE PROCESSED THROUGH DRY MILLING AND DURING STORAGE OF THE RESULTING PRODUCTS ABSTRACT - The objetive of the present study was to determine the retention of carotenoids in maize biofortified with vitamin A precursors (ProVA) processed through dry milling and during storage of the products flaking grits, corn meal and fine meal. Carotenoid profile was determined by high performance liquid chromatography (HPLC) and the total vitamin A precursor carotenoids quantified considering the concentration of α-carotene, β-carotene and β-cryptoxanthin. Dry-milling products of ProVA maize BRS 4104 showed mean true retention for total carotenoids of 75.37% (flaking grits), 73.51% (corn meal) and 59.47% (fine meal), whereas retention for ProVA carotenoids were 74.20% (flaking grits), 75.21% (corn meal) and 60.55% (fine meal) revealing 30% of losses on average due to dry milling effect on the retention of carotenoids present in the maize grains. During the 24-day storage period there was a linear decrease in the retention of total carotenoids and ProVA in the three maize biofortified products. Reduced total carotenoids and ProVA contents in the maize dry milling products (flaking grits, corn meal and fine meal) compared to the whole kernels as well as the important losses of these substances during storage is recommended to be taking into account when using biofortified maize as a complementary strategy in nutrition programs focused on improvement of vitamin A deficiency in humans.Keywords: Zea mays, processing, degradation, pro-vitamin A, bioactive compounds.

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.

Abstract: The objective of this work was to evaluate corn cultivars grown in the state of Amazonas, Brazil, which simultaneously show high grain yield, adaptability, and stability. The trials were carried out in seven environments in the state of Amazonas, in a randomized complete block design, with two replicates. The grain yield of 30 corn cultivars was evaluated in four growing seasons, from 2011/2012 to 2014/2015. The genetic parameters were estimated by the REML/Blup methodology. The selection for adaptability and stability was based on the predicted genetic value and on the harmonic mean of the relative performance of the genetic values. Despite the existence of genotype x environment interaction, cultivars with high adaptability and stability were identified. Iranduba - lowland, in 2011/2012 and 2014/2015 - and Rio Preto da Eva - upland, in 2012/2013 - stood out as favorable environments, while Iranduba - upland, in 2011/2012 and 2012/2013 - and Manaus - upland, in 2012/2013 and 2013/2014 - were classified as unfavorable environments. The single-cross hybrid BRS 1055 showed productive superiority and high stability in this region. The Sint 10771, Sint 10781, and Sint 10699 synthetic varieties showed high adaptability. BRS Caimbé shows specific adaptability to cropping in upland environments of the state of Amazonas, Brazil.

O Banco Ativo de Germoplasma de Milho (BAGMilho) preservado na Embrapa Milho e Sorgo mantém cerca de 4.000 variedades. Entretanto, essas variedades não têm o padrão agronômico das cultivares comerciais, o que reduz o seu potencial do uso direto. O pré-melhoramento possibilita o desenvolvimento de genótipos com maior potencial de uso por meio da hibridização entre acessos do BAGMilho e genótipos melhorados. O objetivo desse trabalho foi avaliar famílias endogâmicas obtidas de cruzamentos entre linhagens-elite e os acessos do BAGMilho composto fonte de resistência à mancha-branca e composto fonte de resistência à ferrugem-polissora quanto à reação a patógenos, produtividade e caracteres agronômicos. Famílias endogâmicas derivadas de retrocruzamentos entre estes Compostos fonte de resistência e linhagens-elite foram avaliadas em cruzamentos com testadores dos grupos heteróticos duro e dentado. Os ensaios foram conduzidos em Sete Lagoas e Nova Porteirinha em duas épocas de semeadura. Os resultados permitiram selecionar as famílias endogâmicas MB130, MB181, MB164, FP109, FP133, FP104, FP120, FP112, FP103 e FP140 para uso em cruzamentos com linhagens do grupo heterótico duro e as famílias endogâmicas MB024, MB032, MB083, FP028, FP036 e FP020 para uso em cruzamentos com linhagens do grupo heterótico dentado.

SUMMARY Analysing the stability and adaptation of cultivars to different environments is always necessary before recommending them for planting on large areas. Additive main effects and multiplicative interaction (AMMI) models have been used to analyse genotype-by-environment interactions (G × E). AMMI models require data with homogeneous variance, normal errors and additive effects. However, agronomic data do not always conform to these statistical assumptions. The objective of the present study was to analyse G × E interactions for severity and incidence of grey leaf spot, a foliar disease in maize caused by Cercospora zeae-maydis , using a generalized AMMI model. Data were collected and evaluated for 36 maize cultivars from experiments carried out in nine Brazilian regions in 2010/11 by the Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA – Milho e Sorgo). Only two of three stable genotypes defined by a quasi-likelihood model with a logistic link function could be recommended for their desirable agronomic characteristics. Four growing locations in which the genotypes were stable were identified, but in only one of these was stability associated with very severe grey leaf spot disease. Cultivars adapted to specific locations with low percentage disease severity were also identified.