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The objective of this work was to evaluate the association between estimates of adaptability, stability, and productivity in soybean (Glycine max), and to estimate the repeatability coefficient of these associations between years. A total of 22 genotypes were evaluated in 27 environments in the 2012/2013 crop season and in 19 environments in 2013/2014. In the next crop seasons, 28 genotypes were evaluated in 26 environments, in 2014/2015, and in 25 environments in 2015/2016, totalizing 97 trials. Fourteen methods were evaluated; Spearman correlation coefficients were obtained for the parameters of stability, adaptability, and productivity; and the repeatability coefficients, as well as the minimum number of required environments for a coefficient of determination of 80 and 90%, were calculated. The minimum number of environments required to estimate the degree of association between the parameters was low (seven sites). The methods of Eberhart & Russell and GGE biplot are essential in the evaluation of productivity, adaptability, and stability in soybean because they are able to encompass these aspects using a minimum set of methods. The methods of Annicchiarico (AN), Silva & Barreto (SB), Cruz (CR), and Storck & Vencovsky (SV) can be used to generate complementary information, such as: stability for general, favorable, and unfavorable environments (AN); adaptability in favorable and unfavorable environments (SB, CR, and SV); and average productivity in all environments and in favorable or unfavorable environments (SV). Resumo: O objetivo deste trabalho foi avaliar as associações entre estimativas de adaptabilidade, estabilidade e produtividade em soja (Glycine max), e estimar o coeficiente de repetibilidade dessas associações entre anos. Foram avaliados 22 genótipos em 27 ambientes, na safra 2012/2013, e em 19 ambientes na 2013/2014. Nas safras seguintes, foram avaliados 28 genótipos em 26 ambientes, em 2014/2015, e em 25 ambientes em 2015/2016, no total de 97 ensaios. Quatorze métodos foram avaliados; os coeficientes de correlação de Spearman foram obtidos para os parâmetros adaptabilidade, estabilidade e produtividade; e os coeficientes de repetibilidade, bem como o número mínimo de ambientes necessário para se obter um coeficiente de determinação de 80 e 90%, foram calculados. O número mínimo de ambientes necessários para estimar o grau de associação entre as estimativas dos parâmetros foi baixo (sete locais). Os métodos de Eberhart & Russell e GGE biplot são essenciais na avaliação da produtividade, da adaptabilidade e da estabilidade em soja, pois conseguem englobar estes aspectos com o uso de um conjunto mínimo de métodos. Já os métodos de Annicchiarico (AN), Silva & Barreto (SB), Cruz (CR) e Storck & Vencovsky (SV) podem ser utilizados para gerar informações complementares, tais como: verificação da estabilidade para ambientes em geral e para ambientes favoráveis e desfavoráveis (AN); adaptabilidade em ambientes favoráveis e desfavoráveis (SB, CR e SV); e produtividade média em todos os ambientes, e em ambientes favoráveis ou desfavoráveis (SV).

The objective of this work was to evaluate the productive performance, and the adaptability and stability parameters of modern soybean (Glycine max) cultivars in multi-environment trials, as well as to identify the ideal genotypes for eight growing environments in Brazil. A randomized complete block experimental design was carried out, with three replicates, for the evaluation of 46 soybean cultivars in eight environments, in the microregions of adaptation 102, 201, and 202, in the 2014/2015 crop season. A complex genotype x environment interaction occurred, with changes in the ranking of genotypes among locations. The NA 5909 RG, M6410IPRO, NS 5959 IPRO, NS6823RR, M5917IPRO, NS 6767 RR, and 6563RSF IPRO cultivars showed the highest mean yields. The NA 5909 RG, NS6823RR, M6410IPRO, and NS 5959 IPRO cultivars showed high adaptability and stability and high grain yield, in the evaluated environments, and were ranked next to the ideal genotype for the analyzed environments. There are modern soybean cultivars, which are adapted, stable, and highly productive, for cultivation in the microregions 102, 201, and 202 for soybean crop adaptation in Brazil.

The objective of this work was to identify core locations in two soybean macroregions in Brazil for the evaluation and selection of soybean (Glycine max) lineages. Twenty-two cultivars were tested in 23 locations in these two macroregions (MR1 and MR2), during four years, from 2012 to 2015. Trials were conducted in a randomized complete block design with three replicates. All analyses were performed using the GGEbiplot software. The genotype main effects plus genotype × location interaction + genotype main effects plus genotype × environment interaction and genotypic effect vs. genotype x environment effect analyses were used to identify core locations, i.e., locations with high representativeness and consistency of results. Chapada, in the state of Rio Grande do Sul, and Maracaju, in the state of Mato Grosso do Sul, were the core locations in MR1 and MR2, respectively. These locations were the most representative and consistent over the years, and the genotypic effect explained a high proportion of phenotypic variance. Resumo: O objetivo deste trabalho foi identificar locais-chave de teste em duas macrorregiões sojícolas no Brasil, para avaliação e seleção de linhagens de soja (Glycine max). Foram testadas 22 cultivares em 23 locais, nessas duas macrorregiões (MR1 e MR2), durante quatro anos, de 2012 a 2015. Os ensaios foram conduzidos em delineamento de blocos ao acaso, com três repetições. Todas as análises foram realizadas com uso do programa GGEbiplot. As análises efeito principal de genótipo mais interação genótipo × local + efeito principal de genótipo mais interação genótipo × ambiente e efeito genotípico vs. efeito do genótipo x ambiente foram utilizadas para identificar locais de teste, isto é, locais com alta representatividade e consistência de resultados. Chapada, no Rio Grande do Sul, e Maracaju, no Mato Grosso do Sul, foram os principais locais em MR1 e MR2, respectivamente. Estes locais foram os mais representativos e consistentes ao longo dos anos, e o efeito genotípico explicou uma alta proporção da variância fenotípica.

Genomic selection (GS) can potentially accelerate genetic improvement of soybean [Glycine max L. (Merrill)] by reducing the time to complete breeding cycles. The objectives of this study were to (1) explore the accuracy of GS in soybean, (2) evaluate the contribution of intrapopulational structure to the accuracy of GS, and (3) compare the efficiencies of phenotypic selection and GS in soybean. For this, phenotypic and genotypic data were collected from 324 soybean genotypes (243 recombinant inbred lines and 81 cultivars) and GS was performed for five yield related traits. BayesB methodology with a 10-fold cross-validation was used to compute accuracies. The GS accuracies were evaluated for grain yield, plant height, insertion of first pod, days to maturity, and 1000-grain weight at eight locations. We found that GS can reduce the time required to complete a selection cycle in soybean, which can lead to increased production of this commercially important crop. Furthermore, genotypic accuracy was similar regardless of population structure correction.

Brazil is one of the largest soybean (Glycine max L. Merrill) producers in the world, as well as main exporter. Little information is available about both the composition of Brazilian genotypes in respect to soluble sugars contents such as sucrose, glucose, raffinose and stachyose, and the effect of genotype × environment interaction (GEI). This study evaluated the soluble sugar contents, the GEI and the genetic variability of highly cultivated cultivars and new soybean lines. A sample of 46 commercial Brazilian cultivars and 35 pre-commercial lines were evaluated at six locations during the 2014/15 crop season, in a randomized complete block design with three replications. Soluble sugars were evaluated using an infrared spectroscopy (NIR) method. The average contents of sucrose, glucose, raffinose and stachyose were 3.3, 1.62, 0.39 and 3.07% which were lower than the levels found in other countries. All field traits were highly influenced by the environment. The cultivar NS 6121 RR presented a reduced (and stable across the environments) raffinose and stachyose content and can be used as a source of novel genes in breeding programs. Brazilian soybean presents genotypic differences which can be exploited to reduce or increase soluble sugar contents in breeding programs. There is a strong GEI for sucrose, glucose, raffinose and stachyose contents for Brazilian environments. The evaluated genotypes presented reduced contents of raffinose and stachyose, which are considered antinutritional factors. The new soybean lines presented similar soluble sugar contents to the tested cultivars.

Soybean (Glycine max (L.) Merrill) is an important source of oil for biodiesel production in Brazil. However, the traits related to oil content and fatty acid profile are not targeted by soybean breeding programs. Developing methods to increase oleic and reduce linolenic fatty acid content within soybean genotypes will increase the use of soybeans for food and feed, as well as biodiesel production. Biodiesel produced with high polyunsaturated fatty acids (PUFAs) content has a high tendency to undergo oxidation, making storage difficult and overall quality reduced. On the other hand, oils with high levels of monounsaturated fatty acids (MUFAs) are preferred for biodiesel production because oxidation is not increased, improve cold flow properties significantly and nitrogen oxide emissions are decreased. In addition, soybean oil with high concentration of PUFAs causes low oxidative stability, resulting in rancidity, a rapid decline of optimal flavor and reducing storage time of manufactured food products. 242 recombinant inbred lines (RILs) were evaluated in six locations in Brazil for grain yield, oil content, oil production, and fatty acid composition. A multi-trait index based on factor analysis and ideotype-design (FAI-BLUP index) was applied to identify genotypes best related with the ideotype for biodiesel production. This method is based on mixed models, with genotype and environment effects being considered as random and fixed, respectively. In addition, the best linear unbiased prediction (BLUP) method was used to predict the genetic values. Six RILs outperformed both parents and can be selected as genotypes more suitable for biodiesel production. Genetic selection reduced linolenic fatty acid content by 14%. Results indicated the presence of genetic variability for fatty acid composition. The significant increases in oleic and reductions in linolenic contents may be easily achieved with the introduction of mutant FAD2-1A and FAD2-1B genes through breeding programs or biotechnological strategies.

The aim of this study was to evaluate the experimental precision of different methods of statistical analysis for trials with large numbers of soybean genotypes, and their relationship with the number of replicates. Soybean yield data (nine trials; 324 genotypes; 46 cultivars; 278 lines; agricultural harvest of 2014/15) were used. Two of these trials were performed at the same location, side by side, forming a trial with six replicates. Each trial was analyzed by the randomized complete block, triple lattice design, and use of the Papadakis method. The selective accuracy, least significant difference, and Fasoulas differentiation index were estimated, and model assumptions were tested. The resampling method was used to study the influence of the number of replicates, by varying the number of blocks and estimating the precision measurements. The experimental precision indicators of the Papadakis method are more favorable as compared to the randomized complete block design and triple lattice. To obtain selective accuracy above the high experimental precision range in trials with 324 soybean genotypes, two repetitions can be used, and data can be analyzed using the randomized complete block design or Papadakis method. RESUMO: O objetivo deste estudo foi avaliar a precisão experimental de diferentes métodos de análise estatística para ensaios com grande número de genótipos de soja e sua relação com o número de repetições. Foram usados dados de produtividade de grãos de soja (nove ensaios, 324 genótipos, 46 cultivares, 278 linhagens, safra agrícola de 2014/15). Dois destes ensaios foram realizados no mesmo local, lado a lado, constituindo um ensaio com seis repetições. Cada ensaio foi analisado pelos delineamentos de blocos ao acaso, látice triplo e uso do método de Papadakis. Foram estimados a acurácia seletiva, diferença mínima significativa e índice de diferenciação de Fasoulas, e, ainda foram testados os pressupostos do modelo. O método de reamostragem foi usado para estudar a influência do número de repetições, variando o número de blocos e estimando as medidas de precisão. Os indicadores de precisão experimental do método de Papadakis são mais favoráveis, quando comparados com os delineamentos de blocos ao acaso e látice triplo. Para obter acurácia seletiva acima da faixa de alta precisão experimental em ensaios com 324 genótipos de soja, pode-se usar duas repetições e analisar os dados, usando o delineamento de blocos completos ao acaso ou método de Papadakis.

The use of different genetic dissimilarity indicators can help in both the selection of crop improvement strategies and as artificial crosses. The objectives of this work were to estimate the genetic dissimilarity among seven oat genotypes (Avena sativa L.) through molecular (dg) and morphological (dm) markers. Data were obtained from two experiments carried out in Capão do Leão County, RS, Brazil, in 2000. The estimated correlation coefficient (r = 0.33) indicated a low association between dg and dm estimates. The genotypes with similar pedigrees (UPF 16 and UPF 17), with a bootstrapping value of 82.7%, performed the most consistent group (dg) and clustered more closely in both techniques (dg and dm). However, genotypes with similar pedigree clustered in distant groups. Both dissimilarity estimates need to be used in order to obtain a more reliable choice of dissimilar parents, with higher probability of developing promising base populations.O uso de diferentes medidas de dissimilaridade genética auxilia na definição de estratégias de melhoramento e no direcionamento de cruzamentos artificiais. O objetivo deste trabalho foi estimar a dissimilaridade genética entre sete genótipos de aveia branca (Avena sativa L.) através de marcadores moleculares AFLP (dg) e caracteres agronômicos (dm). Os resultados foram constatados em dois experimentos desenvolvidos no município de Capão do Leão (RS), Brasil, em 2000. O coeficiente de correlação encontrado (r=0.33) indicou baixa correspondência entre as estimativas de dg e dm. Os genótipos com a mesma genealogia (UPF 16 e UPF 17), com valor de bootstraping de 82,7%, formaram o grupo mais consistente (dg) e o agrupamento mais similar em ambas as técnicas (dg e dm); entretanto, agruparam-se genótipos de genealogia similar em diferentes grupos. Ambas as estimativas de dissimilaridade, quando utilizadas conjuntamente, proporcionam maior suporte para a escolha de genitores dissimilares, com grande probabilidade de desenvolvimento de populações-base promissoras.

The use of different genetic dissimilarity indicators can help in both the selection of crop improvement strategies and as artificial crosses. The objectives of this work were to estimate the genetic dissimilarity among seven oat genotypes (Avena sativa L.) through molecular (dg) and morphological (dm) markers. Data were obtained from two experiments carried out in Capão do Leão County, RS, Brazil, in 2000. The estimated correlation coefficient (r = 0.33) indicated a low association between dg and dm estimates. The genotypes with similar pedigrees (UPF 16 and UPF 17), with a bootstrapping value of 82.7%, performed the most consistent group (dg) and clustered more closely in both techniques (dg and dm). However, genotypes with similar pedigree clustered in distant groups. Both dissimilarity estimates need to be used in order to obtain a more reliable choice of dissimilar parents, with higher probability of developing promising base populations. O uso de diferentes medidas de dissimilaridade genética auxilia na definição de estratégias de melhoramento e no direcionamento de cruzamentos artificiais. O objetivo deste trabalho foi estimar a dissimilaridade genética entre sete genótipos de aveia branca (Avena sativa L.) através de marcadores moleculares AFLP (dg) e caracteres agronômicos (dm). Os resultados foram constatados em dois experimentos desenvolvidos no município de Capão do Leão (RS), Brasil, em 2000. O coeficiente de correlação encontrado (r=0.33) indicou baixa correspondência entre as estimativas de dg e dm. Os genótipos com a mesma genealogia (UPF 16 e UPF 17), com valor de bootstraping de 82,7%, formaram o grupo mais consistente (dg) e o agrupamento mais similar em ambas as técnicas (dg e dm); entretanto, agruparam-se genótipos de genealogia similar em diferentes grupos. Ambas as estimativas de dissimilaridade, quando utilizadas conjuntamente, proporcionam maior suporte para a escolha de genitores dissimilares, com grande probabilidade de desenvolvimento de populações-base promissoras.

We estimated the genetic distances among 10 spring wheat genotypes based on pedigree data, morphological traits and AFLP markers, used individually and combined with morphological traits, to find the best predictors of general- and specific-combining abilities among parental genotypes. Ten wheat parents were crossed in a diallel form, disregarding reciprocal hybrids, totaling 45 combinations. The F₁ hybrids, F₂ populations and parents were evaluated in the field in 2007. The experimental plots consisted of 20 plants for F₁ hybrids and 40 plants for parental and F₂ populations. All methods (pedigree data, AFLP markers and morphological traits, used individually and combined) were found to be useful for the assessment of genetic diversity. The significant coefficient correlations ranged from low (0.45) to moderate (0.67) between the distance measures and hybrid performance. There was significant agreement between the distance measures based on AFLP markers vs morphological traits + AFLP markers (r = 0.47) and between pedigree data vs morphological traits + AFLP markers (r = 0.43). The pedigree distance was positively associated with traits 100-kernel weight and grain yield per plant in F₁ (correlations of 0.67 and 0.62, respectively) and F₂ (correlations of 0.62 and 0.59, respectively) generations. These correlation values indicate that the genetic distance, based on pedigree data, could replace diallel crosses for the selection of parents with higher combining ability and with moderate reliability.

The objective of this study were to estimate the general ability and specific combining ability in ten wheat genotypes in two generations (F1 and F2) to indicate parents and hybrid combinations that are promising to achieve new favorable combinations. Ten wheat genotypes were hybridized in a complete diallel, without reciprocals, totaling 45 hybrid combinations. F1 hybrids and the F2 populations and parents were evaluated in a randomized block design with three replicates in spaced plant. The effect of general combining ability (GCA) was greater than specific combining ability (SCA) in both generations, regardless of the characters evaluated. The best performances of the CGC to grain yield per plant (GYP), number of kernels per spike (NKS), number of spikes per plant (NSP) and plant height (PH) were observed for the parents Fundacep 50, Pampeano, BRS Figueira and UTF 0605, respectively. Promising hybrid combinations (high magnitude of SCA in both generations and high average for the character and at least one parent presenting desirable GCA) were selected. The association of GCA with the performance of characters GYP (F1 = F2 = 0.75 and 0.81), NKS (F1 = F2 = 0.61 and 0.60) and PH (F1=0.99 and F2= 0.98) showed to be a reliable criterion for choice of parents, regardless of generation evaluated.