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.

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.

Sorghum breeding programs are based predominantly on developing homozygous lines to produce single cross hybrids, frequently with relatively narrow genetic bases. The adoption of complementary strategies, such as genetic diversity study, enables a broader vision of the genetic structure of the breeding germplasm. The purpose of this study was to evaluate the genetic diversity of sorghum breeding lines using structure analysis, principal components (PC) and clustering analyses. A total of 160 sorghum lines were genotyped with 29,649 SNP markers generated by genotyping-by-sequencing (GBS). The PC and clustering analyses consistently divided the R (restorer) and B (maintainer) lines based on their pedigree, generating four groups. Thirty-two B and 21 R lines were used to generate 121 single-cross hybrids, whose performances were compared based on the diversity clustering of each parental line. The genetic divergence of B and R lines indicated a potential for increasing heterotic response in the development of hybrids. The genetic distance was correlated to heterosis, allowing for the use of markers to create heterotic groups in sorghum.

A produção nacional de soja (Glycine max L. Merrill) destina-se, em sua maior parte, à obtenção de óleo e farelo. No Brasil, o consumo do farelo de soja está restrito às indústrias de ração para animais (MONTEIRO et al., 2003). Para esta finalidade, a soja não pode ser utilizada sem tostagem, principalmente quando utilizada na alimentação de animais monogástricos, devido à presença de fatores antinutricionais no grão, os quais interferem na absorção e aproveitamento de nutrientes, limitando o valor nutricional dessa leguminosa.Entre os fatores antinutricionais encontrados na semente de soja, os principais são os Inibidores de Tripsina Kunitz (KTI) e as Lectinas (LEC) (PUSZTAI et al., 1997;ARMOUR et al., 1998;SILVA, M. R.;SILVA, M. A. A. P., 2000), os quais afetam o crescimento e/ou metabolismo basal de diferentes espécies animais. Segundo Armour et al. (1998), os inibidores de tripsina Kunitz, quando incluídos na dieta, promovem uma diminuição na ingestão de alimento pelos animais, redução na digestão e absorção de proteínas, além de uma menor AbstractSoybean seeds contain protein anti-nutritional factors, protease inhibitors, and lectins, which limit their use in human and animal nutrition. Aiming to reduce these factors in soybean seeds, a genotype devoid of Kunitz Trypsin Inhibitor (KTI) and Lectin (LEC) was developed by the Breeding Program for Soybean Quality of the Biotechnology Institute (BIOAGRO) of the Federal University of Viçosa, Minas Gerais, Brazil. The present work aimed at the biochemical and nutritional characterization of this soybean genotype. The protein nutritional quality and intestinal morphological alterations were determined in Wistar rats fed with diets based on soy flour and casein.

Spodoptera frugiperda is the most economically important maize pest in Brazil. There is little information about the genetic structure, using SSR markers, of S. frugiperda populations collected from maize crops. In this study, 21 SSR markers were used to evaluate the genetic diversity and population structure of S. frugiperda collected from distinct Brazilian geographical regions. Two hundred and twenty-seven alleles were recorded with an average of 10.76 per marker, and Polymorphic Information Content (PIC) values ranging from 0.242 to 0.933, with an average of 0.621, indicating a high discriminating power. The overall F ST , 0.061, indicated a moderate genetic differentiation among the S. frugiperda populations collected from maize, and the AMOVA showed that 87.36% of the genetic variation is within populations. The Mantel test showed significant correlation between genetic and geographic distances. The genetic data demonstrated that all individuals from the six sampling sites were structured as two sub-populations, being one of them composed only by the CL population, collected in the Rio Grande do Sul state. The knowledge about genetic diversity and population structure of S. frugiperda is important for the development of strategies for the insect pest management and monitoring systems, especially for the differentiated CL population.