Genome-wide association mapping for flowering and maturity in tropical soybean: implications for breeding strategies.

Knowledge of the genetic architecture of flowering and maturity is needed to develop effective breeding strategies in tropical soybean. The aim of this study was to identify haplotypes across multiple environments that contribute to flowering time and maturity, with the purpose of selecting desired alleles, but maintaining a minimal impact on yield-related traits. For this purpose, a genome-wide association study (GWAS) was undertaken to identify genomic regions that control days to flowering (DTF) and maturity (DTM) using a soybean association mapping panel genotyped for single nucleotide polymorphism (SNP) markers. Complementarily, yield-related traits were also assessed to discuss the implications for breeding strategies. To detect either stable or specific associations, the soybean cultivars (N = 141) were field-evaluated across eight tropical environments of Brazil. Seventy-two and forty associations were significant at the genome-wide level relating respectively to DTM and DTF, in two or more environments. Haplotype-based GWAS identified three haplotypes (Gm12_Hap12; Gm19_Hap42 and Gm20_Hap32) significantly co-associated with DTF, DTM and yield-related traits in single and multiple environments. These results indicate that these genomic regions may contain genes that have pleiotropic effects on time to flowering, maturity and yield-related traits, which are tightly linked with multiple other genes with high rates of linkage disequilibrium.

Multi-locus genome-wide association study for phosphorus use efficiency in a tropical maize germplasm.

Phosphorus (P) is an essential macronutrient for maize (Zea mays L.) growth and development. Therefore, generating cultivars with upgraded P use efficiency (PUE) represents one of the main strategies to reduce the global agriculture dependence on phosphate fertilizers. In this work, genome-wide association studies (GWAS) were performed to detect quantitative trait nucleotide (QTN) and potential PUE-related candidate genes and associated traits in greenhouse and field trials under contrasting P conditions. The PUE and other agronomy traits of 132 maize inbred lines were assessed in low and normal P supply through the greenhouse and field experiments and Multi-locus GWAS was used to map the associated QTNs. Wide genetic variability was observed among the maize inbred lines under low and normal P supply. In addition, we confirm the complex and quantitative nature of PUE. A total of 306 QTNs were associated with the 24 traits evaluated using different multi-locus GWAS methods. A total of 186 potential candidate genes were identified, mainly involved with transcription regulator, transporter, and transference activity. Further studies are still needed to elucidate the functions and relevance of these genes regarding PUE. Nevertheless, pyramiding the favorable alleles pinpointed in the present study can be considered an efficient strategy for molecular improvement to increase maize PUE.

Multi-trait and multi-environment genomic prediction for flowering traits in maize: a deep learning approach.

Maize (Zea mays L.), the third most widely cultivated cereal crop in the world, plays a critical role in global food security. To improve the efficiency of selecting superior genotypes in breeding programs, researchers have aimed to identify key genomic regions that impact agronomic traits. In this study, the performance of multi-trait, multi-environment deep learning models was compared to that of Bayesian models (Markov Chain Monte Carlo generalized linear mixed models (MCMCglmm), Bayesian Genomic Genotype-Environment Interaction (BGGE), and Bayesian Multi-Trait and Multi-Environment (BMTME)) in terms of the prediction accuracy of flowering-related traits (Anthesis-Silking Interval: ASI, Female Flowering: FF, and Male Flowering: MF). A tropical maize panel of 258 inbred lines from Brazil was evaluated in three sites (Cambira-2018, Sabaudia-2018, and Iguatemi-2020 and 2021) using approximately 290,000 single nucleotide polymorphisms (SNPs). The results demonstrated a 14.4% increase in prediction accuracy when employing multi-trait models compared to the use of a single trait in a single environment approach. The accuracy of predictions also improved by 6.4% when using a single trait in a multi-environment scheme compared to using multi-trait analysis. Additionally, deep learning models consistently outperformed Bayesian models in both single and multiple trait and environment approaches. A complementary genome-wide association study identified associations with 26 candidate genes related to flowering time traits, and 31 marker-trait associations were identified, accounting for 37%, 37%, and 22% of the phenotypic variation of ASI, FF and MF, respectively. In conclusion, our findings suggest that deep learning models have the potential to significantly improve the accuracy of predictions, regardless of the approach used and provide support for the efficacy of this method in genomic selection for flowering-related traits in tropical maize.

Agronomic performance and quality of baby corn in response to the inoculation of seeds with Azospirillum brasilense and nitrogen fertilization in the summer harvest.

The association with Azospirillum brasilense promotes better growth and development in corn plants due to biological N fixation, the capacity to help in the synthesis of phytohormones and to improve the use of nutrients by crop plants. However, there aren't specific recommendations for the use of inoculation in baby corn crop. Thus, this study aimed to evaluate the effects of seed inoculation with A. brasilense, associated with nitrogen fertilization management, on the agronomic performance and chemical quality of baby corn grown in three summer growing seasons (2014/2015; 2015/2016 and 2016/2017). The evaluated treatments consisted of combination of five levels of seed inoculation (0.0, 50, 100, 150 and 200 mL 60,000 seeds-1) based on Azospirillum brasilense, two levels of nitrogen fertilization at sowing time (0.0 and 30.0 kg of N ha-1) and two levels of nitrogen in topdressing (0.0 and 110.0 kg of N ha-1), applied at the V4 stage of the popcorn hybrid IAC 125. The characteristics evaluated were: leaf area index (LAI), leaf nitrogen content (LNC), total husked spikelets yield (HSY) and commercial spikelets yield (CSY), and the chemical characteristics of the commercial spikelets: crude protein content (CPC), starch content (STC) and total sugar content (TSC). The inoculation, when combined with nitrogen fertilization, provided positive responses for LAI and provided an average increment of 6 kg ha-1 to CSY for every 10 mL 60,000 seeds-1 of inoculant added to the seeds. The LNC, CPC, STC and TSC weren't affected by seed inoculation. Nitrogen fertilization provided increments for all characteristics evaluated, except for TSC, which was negatively affected by nitrogen topdressing. The baby corn crop responded positively to seed inoculation with Azospirillum brasilense, combined with Nitrogen fertilization.

Comparative Analysis of Multiple GWAS Results Identifies Metabolic Pathways Associated with Resistance to A. flavus Infection and Aflatoxin Accumulation in Maize.

Aflatoxins are carcinogenic secondary metabolites produced by several species of Aspergillus, including Aspergillus flavus, an important ear rot pathogen in maize. Most commercial corn hybrids are susceptible to infection by A. flavus, and aflatoxin contaminated grain causes economic damage to farmers. The creation of inbred lines resistant to Aspergillus fungal infection or the accumulation of aflatoxins would be aided by knowing the pertinent alleles and metabolites associated with resistance in corn lines. Multiple Quantitative Trait Loci (QTL) and association mapping studies have uncovered several dozen potential genes, but each with a small effect on resistance. Metabolic pathway analysis, using the Pathway Association Study Tool (PAST), was performed on aflatoxin accumulation resistance using data from four Genome-wide Association Studies (GWAS). The present research compares the outputs of these pathway analyses and seeks common metabolic mechanisms underlying each. Genes, pathways, metabolites, and mechanisms highlighted here can contribute to improving phenotypic selection of resistant lines via measurement of more specific and highly heritable resistance-related traits and genetic gain via marker assisted or genomic selection with multiple SNPs linked to resistance-related pathways.

Biochemical composition of the pericarp cell wall of popcorn inbred lines with different popping expansion.

The popping expansion is a characteristic that is positively related with the quality of popcorn. A positive correlation between the volume of expansion and the thickness of the pericarp, and between the proportion of the opaque/shiny endosperm and the grain weight and volume, were postulated. However, there are no reports in the literature that address the importance of cell wall components in the popping expansion. Here, we investigate the biochemical composition of the pericarp cell walls of three inbred lines of popcorn with different popping expansion. Inbred lines GP12 (expansion volume >40 mL g-1), P11 (expansion volume 30 mL g-1) and P16 (expansion volume 14 mL g-1) were used for the analysis and quantification of monosaccharides by HPAEC-PAD, and ferulic and p-coumaric acids and lignin by HPLC. Our hypothesis is that the biochemical composition of the pericarp cell walls may be related to greater or lesser popping expansion. Our data suggest that the lignin content and composition contribute to popping expansion. The highest concentration of lignin (129.74 µg mg-1; 12.97%) was detected in the pericarp cell wall of the GP12 inbred line with extremely high popping expansion, and the lowest concentration (113.52 µg mg-1; 11.35%) was observed in the P16 inbred line with low popping expansion. These findings may contribute to indicating the quantitative trait locus for breeding programs and to developing other methods to improve the popping expansion of popcorn.

Efficiency of Combining Strains Ag87 (Bacillus megaterium) and Ag94 (Lysinibacillus sp.) as Phosphate Solubilizers and Growth Promoters in Maize.

Increasing phosphorus (P) use efficiency in agricultural systems is urgent and essential to significantly reduce the global demand for this nutrient. Applying phosphate-solubilizing and plant growth-promoting bacteria in the rhizosphere represents a strategy worthy of attention. In this context, the present work aimed to select and validate bacterial strains capable of solubilizing phosphorous and promoting maize growth, aiming to develop a microbial inoculant to be used in Brazilian agriculture. Bacterial strains from the maize rhizosphere were evaluated based on their ability to solubilize phosphate and produce indole acetic acid. Based on these characteristics, 24 strains were selected to be further evaluated under laboratory, greenhouse, and field conditions. Among the selected strains, four (I04, I12, I13, and I17) showed a high potential to increase maize root growth and shoot P content. Strains I13 (Ag87) and I17 (Ag94) were identified by genomic sequencing as Bacillus megaterium and Lysinibacillus sp., respectively. These strains presented superior yield increments relative to the control treatment with 30% P. In addition, combining Ag87 and Ag94 resulted in even higher yield gains, indicating a synergistic effect that could be harnessed in a commercial inoculant for Brazilian agriculture.

Bacillus velezensis strain Ag75 as a new multifunctional agent for biocontrol, phosphate solubilization and growth promotion in maize and soybean crops.

Soybean and maize are some of the main drivers of Brazilian agribusiness. However, biotic and abiotic factors are of great concern, causing huge grain yield and quality losses. Phosphorus (P) deficiency is important among the abiotic factors because most Brazilian soils have a highly P-fixing nature. Thus, large amounts of phosphate fertilizers are regularly applied to overcome the rapid precipitation of P. Searching for alternatives to improve the use of P by crops is essential to reduce the demand for P input. The use of multifunctional rhizobacteria can be considered one of these alternatives. In this sense, the objective of the present work was to select and validate bacterial strains with triple action (plant growth promoter, phosphate solubilizer, and biocontrol agent) in maize and soybean, aiming to develop a multifunctional microbial inoculant for Brazilian agriculture. Bacterial strains with high indole acetic acid (IAA) production, phosphate solubilization, and antifungal activity against soil pathogenic fungi (Rhizoctonia solani, Macrophomina phaseolina, and Fusarium solani) were selected from the maize rhizosphere. Then, they were evaluated as growth promoters in maize under greenhouse conditions. Based on this study, strain 03 (Ag75) was selected due to its high potential for increasing biomass (root and shoot) and shoot P content in maize. This strain was identified through genomic sequencing as Bacillus velezensis. In field experiments, the inoculation of this bacterium increased maize and soybean yields by 17.8 and 26.5%, respectively, compared to the control (25 kg P2O5). In addition, the inoculation results did not differ from the control with 84 kg P2O5, indicating that it is possible to reduce the application of phosphate in these crops. Thus, the Ag75 strain has great potential for developing a multifunctional microbial inoculant that combines the ability to solubilize phosphate, promote plant growth, and be a biocontrol agent for several phytopathogenic fungi.

A Deep Learning Approach to Population Structure Inference in Inbred Lines of Maize.

Analysis of population genetic variation and structure is a common practice for genome-wide studies, including association mapping, ecology, and evolution studies in several crop species. In this study, machine learning (ML) clustering methods, K-means (KM), and hierarchical clustering (HC), in combination with non-linear and linear dimensionality reduction techniques, deep autoencoder (DeepAE) and principal component analysis (PCA), were used to infer population structure and individual assignment of maize inbred lines, i.e., dent field corn (n = 97) and popcorn (n = 86). The results revealed that the HC method in combination with DeepAE-based data preprocessing (DeepAE-HC) was the most effective method to assign individuals to clusters (with 96% of correct individual assignments), whereas DeepAE-KM, PCA-HC, and PCA-KM were assigned correctly 92, 89, and 81% of the lines, respectively. These findings were consistent with both Silhouette Coefficient (SC) and Davies-Bouldin validation indexes. Notably, DeepAE-HC also had better accuracy than the Bayesian clustering method implemented in InStruct. The results of this study showed that deep learning (DL)-based dimensional reduction combined with ML clustering methods is a useful tool to determine genetically differentiated groups and to assign individuals into subpopulations in genome-wide studies without having to consider previous genetic assumptions.

Genetic Progress of Seed Yield and Nitrogen Use Efficiency of Brazilian carioca Common Bean Cultivars Using Bayesian Approaches.

Common bean (Phaseolus vulgaris L.) is one of the most important crops worldwide and is considered an essential source of proteins, fibers, and minerals in the daily diet of several countries. Nitrogen (N) is considered the most important nutrient for common bean crop. On the other hand, the reduction of chemical fertilizers is a global challenge, and the development of cultivars with more N use efficiency (NUsE) is considered one of the main strategies to reduce the amount of N fertilizers. Genetic progress of NUsE has been reported in several crops; however, there was still no quantity in common bean. In this study, our goal was to analyze the genetic progress of seed yield (SY) and NUsE-related traits of 40 carioca common bean cultivars release from 1970 to 2017 in eight environments under low (zero) or high N (40 kg ha-1) in top-dressing. Genetic progress, principal component analysis, correlations among traits, and cultivar stability were analyzed using Bayesian approaches. The lowest values of the deviance information criterion (DIC) for the full model tested indicated the presence of the genotype × N × environment interaction for all evaluated traits. Nitrogen utilization efficiency (NUtE) and nitrogen uptake efficiency (NUpE) were the traits that most contributed to discriminate cultivars. The genetic progress of SY under high N (0.53% year-1, 95% HPD = 0.39; 0.65% year-1) was similar to that obtained in low N conditions (0.48% year-1, 95% HPD = 0.31; 0.64% year-1). These results indicate that modern cultivars do not demand more N fertilizers to be more productive. In addition, we observed a high genetic variability for NUsE-related traits, but there was no genetic progress for these variables. SY showed negative correlation with seed protein content (Prot) in both N conditions, and there was no reduction in Prot in modern cultivars. Both modern and old cultivars showed adaptability and stability under contrasting N conditions. Our study contributed to improve our knowledge about the genetic progress of common bean breeding program in Brazil in the last 47 years, and our data will help researchers to face the challenge of increase NUsE and Prot in the next few years.

Genome-Wide Prediction of Complex Traits in Two Outcrossing Plant Species Through Deep Learning and Bayesian Regularized Neural Network.

Genomic selection models were investigated to predict several complex traits in breeding populations of Zea mays L. and Eucalyptus globulus Labill. For this, the following methods of Machine Learning (ML) were implemented: (i) Deep Learning (DL) and (ii) Bayesian Regularized Neural Network (BRNN) both in combination with different hyperparameters. These ML methods were also compared with Genomic Best Linear Unbiased Prediction (GBLUP) and different Bayesian regression models [Bayes A, Bayes B, Bayes Cπ, Bayesian Ridge Regression, Bayesian LASSO, and Reproducing Kernel Hilbert Space (RKHS)]. DL models, using Rectified Linear Units (as the activation function), had higher predictive ability values, which varied from 0.27 (pilodyn penetration of 6 years old eucalypt trees) to 0.78 (flowering-related traits of maize). Moreover, the larger mini-batch size (100%) had a significantly higher predictive ability for wood-related traits than the smaller mini-batch size (10%). On the other hand, in the BRNN method, the architectures of one and two layers that used only the pureline function showed better results of prediction, with values ranging from 0.21 (pilodyn penetration) to 0.71 (flowering traits). A significant increase in the prediction ability was observed for DL in comparison with other methods of genomic prediction (Bayesian alphabet models, GBLUP, RKHS, and BRNN). Another important finding was the usefulness of DL models (through an iterative algorithm) as an SNP detection strategy for genome-wide association studies. The results of this study confirm the importance of DL for genome-wide analyses and crop/tree improvement strategies, which holds promise for accelerating breeding progress.

Genome-wide haplotype-based association analysis of key traits of plant lodging and architecture of maize identifies major determinants for leaf angle: hapLA4.

Traits related to plant lodging and architecture are important determinants of plant productivity in intensive maize cultivation systems. Motivated by the identification of genomic associations with the leaf angle, plant height (PH), ear height (EH) and the EH/PH ratio, we characterized approximately 7,800 haplotypes from a set of high-quality single nucleotide polymorphisms (SNPs), in an association panel consisting of tropical maize inbred lines. The proportion of the phenotypic variations explained by the individual SNPs varied between 7%, for the SNP S1_285330124 (located on chromosome 9 and associated with the EH/PH ratio), and 22%, for the SNP S1_317085830 (located on chromosome 6 and associated with the leaf angle). A total of 40 haplotype blocks were significantly associated with the traits of interest, explaining up to 29% of the phenotypic variation for the leaf angle, corresponding to the haplotype hapLA4.04, which was stable over two growing seasons. Overall, the associations for PH, EH and the EH/PH ratio were environment-specific, which was confirmed by performing a model comparison analysis using the information criteria of Akaike and Schwarz. In addition, five stable haplotypes (83%) and 15 SNPs (75%) were identified for the leaf angle. Finally, approximately 62% of the associated haplotypes (25/40) did not contain SNPs detected in the association study using individual SNP markers. This result confirms the advantage of haplotype-based genome-wide association studies for examining genomic regions that control the determining traits for architecture and lodging in maize plants.

Azospirillum brasilense promotes increases in growth and nitrogen use efficiency of maize genotypes.

The development of cultivars with an improved nitrogen use efficiency (NUE) together with the application of plant growth-promoting bacteria is considered one of the main strategies for reduction of fertilizers use. In this sense, this study: i) evaluated the effect of Azospirillum brasilense on the initial development of maize genotypes; ii) investigated the influence of A. brasilense inoculation on NUE under nitrogen deficit; and iii) sought for more NUE genotypes with higher responsiveness to A. brasilense inoculation. Twenty-seven maize genotypes were evaluated in three independent experiments. The first evaluated the initial development of maize genotypes with and without A. brasilense (strain Ab-V5) inoculation of seeds on germination paper in a growth chamber. The second and third experiments were carried out in a greenhouse using Leonard pots and pots with substrate, respectively, and the genotypes were evaluated at high nitrogen, low nitrogen and low nitrogen plus A. brasilense Ab-V5 inoculation. The inoculation of seeds with A. brasilense Ab-V5 intensified plant growth, improved biochemical traits and raised NUE under nitrogen deficit. The inoculation of seeds with A. brasilense can be considered an economically viable and environmentally sustainable strategy for maize cultivation.

Genome wide association study for gray leaf spot resistance in tropical maize core.

Gray leaf spot is a maize foliar disease with worldwide distribution and can drastically reduce the production in susceptible genotypes. Published works indicate that resistance to gray leaf spot is a complex trait controlled by multiple genes, with additive effect and influenced by environment. The aim of this study was to identify genomic regions, including putative genes, associated with resistance to gray leaf spot under natural conditions of disease occurrence. A genome wide association study was conducted with 355,972 single nucleotide polymorphism markers on a phenotypic data composed by 157 tropical maize inbred lines, evaluated at Maringá -Brazil. Seven single nucleotide polymorphisms were significantly associated with gray leaf spot, some of which were localized to previously reported quantitative trait loci regions. Three gene models linked to the associated single nucleotide polymorphism were expressed at flowering time and tissue related with gray leaf spot infection, explaining a considerable proportion of the phenotypic variance, ranging from 0.34 to 0.38. The gene model GRMZM2G073465 (bin 10.07) encodes a cysteine protease3 protein, gene model GRMZM2G007188 (bin 1.02) expresses a rybosylation factor-like protein and the gene model GRMZM2G476902 (bin 4.08) encodes an armadillo repeat protein. These three proteins are related with plant defense pathway. Once these genes are validated in next studies, they will be useful for marker-assisted selection and can help improve the understanding of maize resistance to gray leaf spot.

Stress-induced synthesis of proline confers tolerance to water deficit in transgenic wheat.

Water deficit is one of the main abiotic factors that affect spring wheat planted in subtropical regions. Accumulation of proline appears to be a promising approach to maintain the productivity of plants under stress condition. However, morphological alterations and growth reduction are observed in transgenic plants carrying genes coding for osmoprotectants controlled by constitutive promoters. We report here the effects of water deficit on wheat plants transformed with the Vigna aconitifolia Delta(1)-pyrroline-5-carboxylate synthetase (P5CS) cDNA that encodes the key regulatory enzyme in proline biosynthesis, under the control of a stress-induced promoter complex-AIPC. Transgenic wheat plants submitted to 15 days of water shortage presented a distinct response. We have found that drought resulted in the accumulation of proline. The tolerance to water deficit observed in transgenic plants was mainly due to protection mechanisms against oxidative stress and not caused by osmotic adjustment.

Genetic divergence of the common bean (Phaseolus vulgaris L.) group Carioca using morpho-agronomic traits by multivariate analysis.

The objective of this study was to evaluate the genetic divergence among the common bean group Carioca by the Tocher method (based on Mahalanobis distance) and graphic dispersion of canonic variables, aiming to identify populations with wide genetic variability. Eighteen genotypes were evaluated in four seasons using a randomized block design with four replications. The mean weight of 100 seeds, in three experiments, and the mean number of pods per plant, in one experiment, were the most important characteristics for the genetic divergence, representing more than 46% of the total variation in the first canonic variable. The first two canonic variables were sufficient to explain about 88.23% of the total variation observed in the average of the four environments. The results showed that CNFC 8008 and CNFC 8009 genotypes presented the best yield averages in all the experiments. While Pérola, Princesa and CNFC 8005 cultivars were the most dissimilar for morpho-agronomic traits. Therefore, the combinations of PérolaxCNFC 8008, CNFC 8005xCNFC 8009, PérolaxCNFC 8009, PrincesaxCNFC 8008 and PrincesaxCNFC 8009 were indicated for interpopulational breeding.

A Genome-Wide Association Study for Agronomic Traits in Soybean Using SNP Markers and SNP-Based Haplotype Analysis.

Mapping quantitative trait loci through the use of linkage disequilibrium (LD) in populations of unrelated individuals provides a valuable approach for dissecting the genetic basis of complex traits in soybean (Glycine max). The haplotype-based genome-wide association study (GWAS) has now been proposed as a complementary approach to intensify benefits from LD, which enable to assess the genetic determinants of agronomic traits. In this study a GWAS was undertaken to identify genomic regions that control 100-seed weight (SW), plant height (PH) and seed yield (SY) in a soybean association mapping panel using single nucleotide polymorphism (SNP) markers and haplotype information. The soybean cultivars (N = 169) were field-evaluated across four locations of southern Brazil. The genome-wide haplotype association analysis (941 haplotypes) identified eleven, seventeen and fifty-nine SNP-based haplotypes significantly associated with SY, SW and PH, respectively. Although most marker-trait associations were environment and trait specific, stable haplotype associations were identified for SY and SW across environments (i.e., haplotypes Gm12_Hap12). The haplotype block 42 on Chr19 (Gm19_Hap42) was confirmed to be associated with PH in two environments. These findings enable us to refine the breeding strategy for tropical soybean, which confirm that haplotype-based GWAS can provide new insights on the genetic determinants that are not captured by the single-marker approach.

Testers in supersweet corn lines / Avaliação de testadores em linhagens de milho superdoce

ABSTRACT: The purpose of this study was to evaluate the discriminatory capacity of tester lines for tropical corn lines converted to supersweet shrunken (sh2) gene, for the development of hybrids adapted to tropical conditions. Lines were used as female parents in crosses with three testers: open-pollinated mixed variety; supersweet line L4; supersweet commercial hybrid Tropical Plus. Four trials were carried out to evaluate topcrosses in Maringá - PR e Sabáudia - PR, Brazil in the main growing season of 2015/16. The following traits were evaluated: total ear weight (TEW, in kg), commercial ear weight (CEW, in kg) and total soluble solids (TSS, in °Brix). The GCA estimates for TEW and CEW were highest for L4. The lines Balu-114 and UEM-25 were selected based on the effects of g ̂ ifor the traits studied and should be used in the establishment of base populations for the breeding of superior lines. The s ̂ ijvalue for TEW was highest for cross BALU-182 x Tropical, while for CEW was the highest value for cross BALU-94 x Mista.

RESUMO: O presente trabalho teve como objetivo avaliar o desempenho de testadores quanto à capacidade de discriminação de linhagens tropicais convertidas à superdoce, por meio da incorporação do gene shrunken (sh2), visando a produção de híbridos adaptados às condições tropicais. As linhagens utilizadas como parentais femininos foram os testadores: variedade de polinização aberta Mista; linhagem superdoce L4; híbrido comercial superdoce Tropical Plus. Os quatro experimentos foram conduzidos em Maringá - PR e Sabáudia - PR, na safra verão de 2015/16. As características avaliadas foram: Peso de espigas totais (PET, em kg), Peso de espigas comerciais (PEC, em kg) e sólidos solúveis totais (SST, em ºBrix). A linhagem L4 foi o testador que mais proporcionou efeito de heterose. As maiores estimativas de CGC para PET e PEC foram obtidas por L4. As linhagens Balu-114 e UEM-25 foram selecionados com base nos efeitos de g ̂ i para as características estudadas e deverão ser utilizados na formação de populações base para a extração de linhagens superiores. O cruzamento BALU-182 x Tropical apresentou o maior valor de s ̂ ijpara PET, enquanto o cruzamento BALU-94 x Mista obteve o melhor valor para PEC.

Diallel analysis and prediction of untested maize single cross hybrids / Análise dialélica e predição de híbridos simples de milho não testados

Popcorn (Zea mays everta) is a popular snack food and very appreciated in Brazil, presenting higher aggregate value when compared with field corn. The aim of this study were to identify superior inbred lines and single crosses hybrids (SH) for popcorn traits, as well as the prediction of the performance of untested single cross hybrids. Sixteen maize inbred lines were crossed in a 9x7 partial diallel, but it was possible to evaluate 47 single crosses in two distinct locations. Predicted genetic values, diallel analysis and the prediction of untested HS were performed by mixed models. Deviance effects for treatments x locations were considered non-significant (p>0.05) for grain yield (GY) and popping expansion (PE), showing an average performance from the HS in the locations. Inbred lines P5-1, P3.3T, GER-P3, P9-1, P12-2 andGER-P12 were selected considering the general combining ability, and should be used for obtaining superior genotypes. Based on the non-additive effects, the single hybrid P3.3T x GERP-P12 was selected for grain yield and popping expansion, and could be exploited in future trials. Neither of the untested single crosses showed desirable performance for grain yield and popcorn expansion.

O milho pipoca (Zea mays everta) é um alimento consumido e apreciado em todo o Brasil, apresentando valor comercial superior ao do milho comum. O presente trabalho teve como objetivo identificar linhagens e híbridos simples (HS) com desempenho superior para as principais características relacionadas ao milho pipoca, além da predição do desempenho de híbridos simples não testados. Foi realizado um dialelo parcial 9x7, dos quais apenas 47 HS foram avaliados em dois locais. Os valores genéticos preditos, análise dialélica e a predição dos HS não avaliados foram realizadas via modelos mistos. Os efeitos da deviance na interação tratamentos x locais foram considerados não significativos (p>0.05) para rendimento de grãos (RG) e capacidade de expansão (CE), indicando um comportamento médio dos HS nos ambientes testados. Com base nos efeitos aditivos, as linhagens P5-1, P3.3T, GER-P3, P9-1, P12-2 e GER-P12 foram selecionados e deverão ser usadas na formação de genótipos com desempenho superior. O híbrido P3.3T x GER-P12 foi selecionadopor apresentar elevado desempenho específico para rendimento e capacidade de expansão, podendo ser utilizado em futuros experimentos. Entre os híbridos não avaliados, nenhum apresentou desempenho satisfatório para as características avaliadas.

A collection of popcorn as a reservoir of genes for the generation of lineages.

In the present study, we analyze the genetic structure and diversity among accessions of popcorn obtained from the CIMMYT International Maize and Wheat Improvement Center that represent the diversity available for current use by breeding programs. The main objectives were to identify SSR loci that were the best indicators of genetic diversity, to measure the genetic diversity within popcorn genotypes, and to analyze the genetic structure of the promising populations destined for use in breeding programs. The mean gene diversity of all SSR loci was 0.6352. An extremely high population differentiation level was detected (F(st) = 0.3152) with F(st) for each locus ranging from 0.1125 (Umc1229) to 0.4870 (Umc1755). Analyzing the genetic structure of eight popcorn accessions was especially important for identifying both SSR loci with high levels of heterozygosity and genotypes showing high heterozygosity (BOYA462 and ARZM13 050). This analysis should be the medium and long-term selection goal for the generation of inbred lines and the future production of new cultivars. Plant accessions ARZM05 083, ARZM13 050, and URUG298 may also be useful varieties that exhibit important agronomic characteristics that can be used through crosses to broaden the genetic basis of popcorn.