The objective of this work was to identify sorghum lines tolerant to water stress at post-flowering. The treatments were set as a factorial arrangement, comprised of two water regimes and 25 genotypes, during the years of 2006, 2007 and 2008. The experimental design was a randomized block, with three replications. Since the combined analysis of variance revealed significant differences among the lines, among the environments and the presence of significant genotypes x environments interaction, two univariate stability estimates (Lin & Binns and Annicchiarico) and one multivariate (AMMI) were utilized for ranking the yield stability of the genotypes. Water stress decreases significantly the yield of the genotypes. The two univariate methods presented similar results, and were complementary to AMMI, allowing the selection of tolerant and responsive lines. Lines 9929020, CMSXS 230B and N 95B were drought tolerant and stable, followed by the lines BR 008B, Tx 2737 e Tx 2908 with high yield, but intermediate stability.

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 performance of genotypes in a wide range of environments can be affected by extensive genotype × environment (G × E) interactions, making the subdivision of the testing environments into relatively more homogeneous groups of locations (mega‐environments) a necessary strategy. The genotype main effects + genotype × environment interaction biplot method (GGE) allows identification of mega‐environments and selection of stable genotypes adapted to specific environments and mega‐environments. The objectives of this study were to identify mega‐environments regarding sorghum [Sorghum bicolor (L.) Moench] grain yield and demonstrate that the GGE biplot method can identify essential locations for conducting tests in different mega‐environments. A total of 22 competition trials of grain sorghum genotypes were conducted over three crop seasons across several production locations in Brazil. A total of 25, 22, and 30 genotypes were evaluated during the first, second, and third crop seasons, respectively. After identifying the presence of G × E interactions, the data were subjected to adaptability and stability analyses using the GGE biplot method. A phenotypic correlation network was used to express functional relationships between environments. The GGE biplot was found to be an efficient approach for identifying three mega‐environments in grain sorghum in Brazil, selecting representative and discriminative environments, and recommending more adaptive and stable grain sorghum genotypes.

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.

The sorghum is an important crop in Brazil because is an alternative crop for the cultivation offseason or in regions where the production of other cereals is limited by water deficit. This work evaluated 25 simple hybrids of grain sorghum, 22 pre-commercial hybrids of Embrapa Milho e Sorgo and three commercial cultivars. These hybrids were evaluated in nine producing regions using a randomized block design. The characteristics evaluated were height, grain yield and flowering. The means were analyzed by DMS of Tukey's test. The high height observed for the hybrids 0307689 and 1G282 indicates a restriction in the utilization in environments subject to high winds, because of the possibility of lodging and break of the plants, with consequent losses at harvest. The number of days for flowering was not limiting for any genotype; however, several pre-commercial hybrids were earlier than the cultivars. Considering stability and adaptability, the hybrids 1G282, BRS 308 and 0009061 presented the highest grain yield. Hybrids 0307131, 0307651 and 0307071 presented higher performance in Teresina. The results suggest the need for further assessments for recommending the most suitable hybrids for each region.