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Amazon chicory is still a little-known vegetable despite its great agronomic potential. The characterization of chicory genotypes concerning genetic divergence is a key step for breeding programs, as it allows the selection of superior individuals and to explore the variability and complementarity of characteristics via interbreeding between newly generated genotypes. In this context, this study aimed to evaluate the genetic divergence among Amazon chicory creole genotypes from the northern Brazilian states of Pará and Rondônia based on morpho-agronomic traits. We conducted an experiment in a randomized block design with eight chicory genotypes (treatments) and four replications. Both quantitative and qualitative characteristics were evaluated. Genetic divergence was estimated via squared generalized Mahalanobis distance (D2 ), considering only quantitative characters, and the genotypes were subsequently clustered via the UPGMA method. Analysis of variance showed significant differences among genotypes for all studied characteristics, except shoot fresh weight. The UPGMA grouped the genotypes into three clusters, which demonstrated that the genotypes from Colares and Santarém Novo (Pará) (Chic-02 and Chic-04) were the most divergent as compared to the genotypes from Castanhal and Santa Isabel do Pará (Pará). Qualitative characteristics showed a monomorphic behavior and, therefore, were not used to assess genetic divergences. To obtain segregating populations with complementary characteristics, crossbreeding between the two most divergent clusters is recommended.(AU)

A chicória da Amazônia é uma hortaliça ainda pouco conhecida, mas com grande potencial agronômico. A caracterização dos genótipos de chicória quanto a divergência genética é um importante passo para programas de melhoramento genético, pois permite selecionar indivíduos superiores e explorar a variabilidade e a complementariedade de características, a partir dos novos genótipos gerados. Nesse contexto, o objetivo deste estudo foi avaliar a divergência genética de genótipos crioulos de chicória da Amazônia dos estados do Pará e Rondônia, com base em caracteres morfoagronômicos. Realizou-se um experimento em delineamento de blocos ao acaso, com oito genótipos de chicória (tratamentos) e quatro repetições. Foram avaliadas características quantitativas e qualitativas. A divergência genética foi estimada a partir da distância quadrada generalizada de Mahalanobis (D2 ), levando em consideração apenas os caracteres quantitativos, e os genótipos foram agrupados pelo método UPGMA. A análise de variância evidenciou diferença significativa entre os genótipos para todas as características, exceto massa fresca. O UPGMA agrupou os genótipos em três grupos, sendo os genótipos de Colares e Santarém Novo (Pará) (Chic-02 e Chic-04) os mais divergentes em comparação com os genótipos da região de Castanhal e Santa Isabel do Pará (Pará). As características qualitativas apresentaram padrão monomórfico, não sendo, portanto, utilizadas para avaliar a divergência. Para obter populações segregantes com complementariedade de características, recomenda-se o cruzamento entre os dois grupos mais divergentes.(AU)

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Mitigating the high costs of soybean breeding programs requires constant improvement of all the involved processes. Identifying representative and discriminating test locations, as well as excluding redundant and/or non-representative locations, makes it possible to select genotypes with more accuracy while reducing the costs of the multi-environment trials (MET). Therefore, this study had three objectives: to evaluate the representativeness and discriminating power of test locations; to identify similar test locations for each Edaphoclimatic Region (ECR) and locations that did not contribute to genotype evaluation; and to recommend the best locations for evaluating MET in order to reduce breeding program costs in the soybean macro regions 1 (M1) and 2 (M2). Grain yield (GY) data from Value-for-Cultivation-and-Use (VCU) trials obtained during the 2012-2016 crop seasons were used, totaling 132 environments (location x year) and 43 genotypes. The experiments were arranged in a randomized complete block design with three replications. Representative and discriminant locations were identified by GGL (genotype main effects plus genotype × location interaction) + GGE (genotype main effects plus genotype × environment interaction) analysis, using GGEbiplot software. Representative and discriminant locations were identified for each ECR and can be used as core locations for breeding programs. Similarly, locations that were not representative and discriminant, or that present redundancy in the results, should be excluded from or replaced in MET. The most recommended locations for conducting VCU trials in M1 were Cachoeira do Sul (ECR 101); Ronda Alta, Passo Fundo, Santa Bárbara do Sul, and Ciríaco (ECR 102); and Castro (ECR 103). For M2, the most suitable locations are Rolândia, Marechal Cândido Rondon, Campo Mourão, Santa Terezinha de Itaipu, Palotina, Floresta, and Londrina (ECR 201); Naviraí (ECR 202); and Ponta Porã and Maracajú (ECR 204).

A redução dos elevados custos dos programas de melhoramento de soja requer melhoria constante detodos os processos envolvidos. A identificação de locais de teste representativos e discriminativos, bemcomo a exclusão de locais redundantes e/ou não representativos, possibilita a seleção de genótipos commaior precisão, e ao mesmo tempo reduz os custos dos ensaios multiambientes (MET). Portanto, esteestudo teve três objetivos: avaliar a representatividade e a discriminância dos locais de teste; identificarlocais de teste semelhantes e que não contribuíram para a avaliação genotípica dentro de cada RegiãoEdafoclimática (ECR); e recomendar os melhores locais para a avaliação de MET, a fim de reduzir oscustos do programa de melhoramento genético nas macrorregiões 1 (M1) e 2 (M2) de adaptação da soja.Dados de rendimento de grãos (RG) de ensaios de “Valor de Cultivo e Uso” (VCU) obtidos duranteos anos agrícolas 2012-2016 foram utilizados, totalizando 132 ambientes (local x ano) e 43 genótipos.Os experimentos foram conduzidos em delineamento de blocos completamente casualizados, comtrês repetições. Locais representativos e discriminantes foram identificados pela análise GGL (efeitoprincipal de genótipo + interação genótipo × local) + GGE (efeito principal de genótipo + interaçãogenótipo × ambiente), utilizando o software GGEbiplot. Locais representativos e discriminantes foramidentificados para cada ECR, e podem ser utilizados como locais-chave em programas de melhoramento.Da mesma forma, locais que não foram representativos e discriminantes, ou que apresentam redundânciaforam identificados e devem ser excluídos ou substituídos no MET. Os locais recomendados para acondução de ensaios de VCU na M1 são: Cachoeira do Sul (ECR 101); Ronda Alta, Passo Fundo, SantaBárbara do Sul e Ciríaco (ECR 102); e Castro (ECR 103). Já para M2, os locais recomendados são:Rolândia, Marechal Cândido Rondon, Campo Mourão...

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Mitigating the high costs of soybean breeding programs requires constant improvement of all the involved processes. Identifying representative and discriminating test locations, as well as excluding redundant and/or non-representative locations, makes it possible to select genotypes with more accuracy while reducing the costs of the multi-environment trials (MET). Therefore, this study had three objectives: to evaluate the representativeness and discriminating power of test locations; to identify similar test locations for each Edaphoclimatic Region (ECR) and locations that did not contribute to genotype evaluation; and to recommend the best locations for evaluating MET in order to reduce breeding program costs in the soybean macro regions 1 (M1) and 2 (M2). Grain yield (GY) data from Value-for-Cultivation-and-Use (VCU) trials obtained during the 2012-2016 crop seasons were used, totaling 132 environments (location x year) and 43 genotypes. The experiments were arranged in a randomized complete block design with three replications. Representative and discriminant locations were identified by GGL (genotype main effects plus genotype × location interaction) + GGE (genotype main effects plus genotype × environment interaction) analysis, using GGEbiplot software. Representative and discriminant locations were identified for each ECR and can be used as core locations for breeding programs. Similarly, locations that were not representative and discriminant, or that present redundancy in the results, should be excluded from or replaced in MET. The most recommended locations for conducting VCU trials in M1 were Cachoeira do Sul (ECR 101); Ronda Alta, Passo Fundo, Santa Bárbara do Sul, and Ciríaco (ECR 102); and Castro (ECR 103). For M2, the most suitable locations are Rolândia, Marechal Cândido Rondon, Campo Mourão, Santa Terezinha de Itaipu, Palotina, Floresta, and Londrina (ECR 201); Naviraí (ECR 202); and Ponta Porã and Maracajú (ECR 204).(AU)

A redução dos elevados custos dos programas de melhoramento de soja requer melhoria constante detodos os processos envolvidos. A identificação de locais de teste representativos e discriminativos, bemcomo a exclusão de locais redundantes e/ou não representativos, possibilita a seleção de genótipos commaior precisão, e ao mesmo tempo reduz os custos dos ensaios multiambientes (MET). Portanto, esteestudo teve três objetivos: avaliar a representatividade e a discriminância dos locais de teste; identificarlocais de teste semelhantes e que não contribuíram para a avaliação genotípica dentro de cada RegiãoEdafoclimática (ECR); e recomendar os melhores locais para a avaliação de MET, a fim de reduzir oscustos do programa de melhoramento genético nas macrorregiões 1 (M1) e 2 (M2) de adaptação da soja.Dados de rendimento de grãos (RG) de ensaios de “Valor de Cultivo e Uso” (VCU) obtidos duranteos anos agrícolas 2012-2016 foram utilizados, totalizando 132 ambientes (local x ano) e 43 genótipos.Os experimentos foram conduzidos em delineamento de blocos completamente casualizados, comtrês repetições. Locais representativos e discriminantes foram identificados pela análise GGL (efeitoprincipal de genótipo + interação genótipo × local) + GGE (efeito principal de genótipo + interaçãogenótipo × ambiente), utilizando o software GGEbiplot. Locais representativos e discriminantes foramidentificados para cada ECR, e podem ser utilizados como locais-chave em programas de melhoramento.Da mesma forma, locais que não foram representativos e discriminantes, ou que apresentam redundânciaforam identificados e devem ser excluídos ou substituídos no MET. Os locais recomendados para acondução de ensaios de VCU na M1 são: Cachoeira do Sul (ECR 101); Ronda Alta, Passo Fundo, SantaBárbara do Sul e Ciríaco (ECR 102); e Castro (ECR 103). Já para M2, os locais recomendados são:Rolândia, Marechal Cândido Rondon, Campo Mourão...(AU)

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One of the main challenges in plant breeding programs is the efficient quantification of the genotype-by-environment interaction (GEI). The presence of significant GEI may create difficulties for breeders in the selection and recommendation of superior genotypes for a wide environmental network. Among the diverse statistical procedures developed for this purpose, we highlight those based on mixed models and factor analysis that are called factor analytic (FA) models. However, some inferential issues are related to the factor analytic model, such as Heywood cases that make the model non-identifiable. Moreover, the representation of the loads and factors in the conventional biplot does not involve any measurement of uncertainty. In this work, we propose dealing with the FA model using the Bayesian framework with direct sampling of factor loadings via spectral decomposition; this guarantees identifiability in the estimation process and eliminates the need for the rotationality of factor loadings or imposition of any ad hoc constraints. We used simulated and real data to illustrate the method's application in multi-environment trials (MET) and to compare it with traditional FA mixed models on controlled unbalancing. In general, the Bayesian FA model was robust under different simulated unbalanced levels, presenting the superior predictive ability of missing data when compared to competing models, such as those based on FA mixed models. In addition, for some scenarios, the classical FA mixed model failed in estimating the full FA model, illustrating the parametric problems of convergence in these models. Our results suggest that Bayesian factorial models might be successfully used in plant breeding for MET analysis.

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Plant fiber is a renewable and biodegradable material that can be used effectively to reinforce various composites. Pineapple hybrids selected for their fiber quality are in the phase of agronomic validation in Brazil by the Embrapa Cassava and Fruits research unit. The selection of a hybrid for large-scale fiber production depends on obtaining a large number of seedlings. This study evaluated the morphogenetic response and propagation potential of eight hybrids of Ananas comosus var. erectifolius, for the purpose of producing high-quality seedlings on a large scale. Stem and crown buds were reduced and placed in MS nutritive medium supplemented with BAP at 0.5 mg L-1, NAA at 0.01 mg L-1 and Phytagel® at 2.5 g L-1. After 45 days, the number of oxidized, contaminated and surviving buds was determined. Swollen buds and plantlets were transferred to a multiplication medium containing MS sucrose, salts and vitamins. The propagation potential was evaluated based on the geometric growth rate among sub-cultures. The FIB-NEG hybrid presented the best results for the establishment phase (40.28%). The best propagative potential was obtained from crown buds with the highest values for FIB-EST (3.93), FIB-MIN (3.91) and FIB-BOY (3.91) hybrids.(AU)

A fibra vegetal é uma fonte renovável, biodegradável e de excelente desempenho como reforço em compósitos variados. Híbridos selecionados pela qualidade de suas fibras estão em fase de validação agronômica na Embrapa Mandioca e Fruticultura e sua adoção para produção de fibra em larga escala depende de um elevado número de mudas. Este trabalho teve como objetivo avaliar a resposta morfogenética e o potencial propagativo de oito híbridos de Ananas comosus var. erectifolius, com a finalidade de produzir mudas de qualidade em larga escala. Gemas do caule e coroa foram reduzidas, introduzidas em meio nutritivo MS suplementado com BAP a 0,5 mg L-1, ANA a 0,01 mg L-1 e Phytagel® a 2,5 g L-1. Aos 45 dias foram avaliados o número de gemas oxidadas, contaminadas e sobreviventes. Gemas intumescidas e plantas formadas foram transferidas para o meio de multiplicação contendo sacarose, sais e vitaminas MS. Avaliou-se o potencial propagativo a partir de uma taxa de crescimento geométrico entre subcultivos. O híbrido FIB-NEG (40.28%) apresentou os melhores resultados em porcentagem para a fase de estabelecimento. O melhor potencial propagativo foi obtido a partir de gemas de coroa, com os valores mais elevados registrados para os híbridos FIB-EST (3.93), FIB-MIN (3.91) e FIB-BOY (3.91).(AU)

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Plant fiber is a renewable and biodegradable material that can be used effectively to reinforce various composites. Pineapple hybrids selected for their fiber quality are in the phase of agronomic validation in Brazil by the Embrapa Cassava and Fruits research unit. The selection of a hybrid for large-scale fiber production depends on obtaining a large number of seedlings. This study evaluated the morphogenetic response and propagation potential of eight hybrids of Ananas comosus var. erectifolius, for the purpose of producing high-quality seedlings on a large scale. Stem and crown buds were reduced and placed in MS nutritive medium supplemented with BAP at 0.5 mg L-1, NAA at 0.01 mg L-1 and Phytagel® at 2.5 g L-1. After 45 days, the number of oxidized, contaminated and surviving buds was determined. Swollen buds and plantlets were transferred to a multiplication medium containing MS sucrose, salts and vitamins. The propagation potential was evaluated based on the geometric growth rate among sub-cultures. The FIB-NEG hybrid presented the best results for the establishment phase (40.28%). The best propagative potential was obtained from crown buds with the highest values for FIB-EST (3.93), FIB-MIN (3.91) and FIB-BOY (3.91) hybrids.

A fibra vegetal é uma fonte renovável, biodegradável e de excelente desempenho como reforço em compósitos variados. Híbridos selecionados pela qualidade de suas fibras estão em fase de validação agronômica na Embrapa Mandioca e Fruticultura e sua adoção para produção de fibra em larga escala depende de um elevado número de mudas. Este trabalho teve como objetivo avaliar a resposta morfogenética e o potencial propagativo de oito híbridos de Ananas comosus var. erectifolius, com a finalidade de produzir mudas de qualidade em larga escala. Gemas do caule e coroa foram reduzidas, introduzidas em meio nutritivo MS suplementado com BAP a 0,5 mg L-1, ANA a 0,01 mg L-1 e Phytagel® a 2,5 g L-1. Aos 45 dias foram avaliados o número de gemas oxidadas, contaminadas e sobreviventes. Gemas intumescidas e plantas formadas foram transferidas para o meio de multiplicação contendo sacarose, sais e vitaminas MS. Avaliou-se o potencial propagativo a partir de uma taxa de crescimento geométrico entre subcultivos. O híbrido FIB-NEG (40.28%) apresentou os melhores resultados em porcentagem para a fase de estabelecimento. O melhor potencial propagativo foi obtido a partir de gemas de coroa, com os valores mais elevados registrados para os híbridos FIB-EST (3.93), FIB-MIN (3.91) e FIB-BOY (3.91).

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Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of Brazil nut tree (Bertholletia excelsa) genotypes based on fruit yield. For this, we assessed the number of fruits and dry mass of seeds of 75 Brazil nut genotypes, from native forest, located in the municipality of Itaúba, MT, for 5 years. To better estimate r, four procedures were used: analysis of variance (ANOVA), principal component analysis based on the correlation matrix (CPCOR), principal component analysis based on the phenotypic variance and covariance matrix (CPCOV), and structural analysis based on the correlation matrix (mean r - AECOR). There was a significant effect of genotypes and measurements, which reveals the need to study the minimum number of measurements for selecting superior Brazil nut genotypes for a production increase. Estimates of r by ANOVA were lower than those observed with the principal component methodology and close to AECOR. The CPCOV methodology provided the highest estimate of r, which resulted in a lower number of measurements needed to identify superior Brazil nut genotypes for the number of fruits and dry mass of seeds. Based on this methodology, three measurements are necessary to predict the true value of the Brazil nut genotypes with a minimum accuracy of 85%.

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Most strawberry genotypes grown commercially in Brazil originate from breeding programs in the United States, and are therefore not adapted to the various soil and climatic conditions found in Brazil. Thus, quantifying the magnitude of genotype x environment (GE) interactions serves as a primary means for increasing average Brazilian strawberry yields, and helps provide specific recommendations for farmers on which genotypes meet high yield and phenotypic stability thresholds. The aim of this study was to use AMMI (additive main effects and multiplicative interaction) and GGE biplot (genotype main effects + genotype x environment interaction) analyses to identify high-yield, stable strawberry genotypes grown at three locations in Espírito Santo for two agricultural years. We evaluated seven strawberry genotypes (Dover, Camino Real, Ventana, Camarosa, Seascape, Diamante, and Aromas) at three locations (Domingos Martins, Iúna, and Muniz Freire) in agricultural years 2006 and 2007, totaling six study environments. Joint analysis of variance was calculated using yield data (t/ha), and AMMI and GGE biplot analysis was conducted following the detection of a significant genotypes x agricultural years x locations (G x A x L) interaction. During the two agricultural years, evaluated locations were allocated to different regions on biplot graphics using both methods, indicating distinctions among them. Based on the results obtained from the two methods used in this study to investigate the G x A x L interaction, we recommend growing the Camarosa genotype for production at the three locations assessed due to the high frequency of favorable alleles, which were expressed in all localities evaluated regardless of the agricultural year.

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In the final phases of new soybean cultivar development, lines are cultivated in several locations across multiple seasons with the intention of identifying and selecting superior genotypes for quantitative traits. In this context, this study aimed to study the genotype-by-environment interaction for the trait grain yield (kg/ha), and to evaluate the adaptability and stability of early-cycle soybean genotypes using the additive main effects and multiplicative interaction (AMMI) analysis, genotype main effects and genotype x environment interaction (GGE) biplot, and factor analysis methods. Additionally, the efficiency of these methods was compared. The experiments were carried out in five cities in the State of Mato Grosso: Alto Taquari, Lucas do Rio Verde, Sinop, Querência, and Rondonópolis, in the 2011/2012 and 2012/2013 seasons. Twenty-seven early-cycle soybean genotypes were evaluated, consisting of 22 lines developed by Universidade Federal de Uberlândia (UFU) soybean breeding program, and five controls: UFUS Carajás, MSOY 6101, MSOY 7211, UFUS Guarani, and Riqueza. Significant and complex genotype-by-environment interactions were observed. The AMMI model presented greater efficiency by retaining most of the variation in the first two main components (61.46%), followed by the GGE biplot model (57.90%), and factor analysis (54.12%). Environmental clustering among the methodologies was similar, and was composed of one environmental group from one location but from different seasons. Genotype G5 presented an elevated grain yield, and high adaptability and stability as determined by the AMMI, factor analysis, and GGE biplot methodologies.

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O objetivo deste trabalho foi investigar a eficiência do método estatístico da cokrigagem na estimativa do Ca e Mg foliares da bananeira 'Prata Anã', utilizando os teores de Ca e Mg do solo como variáveis auxiliares. Foram coletadas em torno de cada planta quatro amostras de solo na camada de 0 ­ 0,2 m e em seguida homogeneizadas formando uma amostra composta. Para análise foliar foram coletadas de 10 a 25 cm da parte interna mediana do limbo foliar, na terceira folha a contar do ápice eliminando-se a nervura central, no período de inflorescência da planta, em uma malha regular, totalizando 100 pontos amostrais espaçados de 6 x 4 m. Obteve-se as margens de erros associadas à cokrigagem por comparação dos valores estimados com aqueles determinados em laboratório. Os resultados mostraram que a técnica foi capaz de estimar os nutrientes foliares com eficiência.

The objective of this study was to investigate the efficiency of the cokrigagem statistical method to estimate the Ca and Mg leaf of tree banana 'Prata Anã', using the Ca and Mg in the soil as auxiliary variables. Were collected around each plant four samples of soil layer from 0 - 0.2 m then homogenised to form a composite sample. For leaf analysis were collected from 10 to 25 cm from the inner leaf of the median, the third leaf from apex eliminating the midrib, from inflorescence of the plant in a regular grid, totaling 100 sampling points spaced 6 x 4 m. Obtained the margins of error associated with cokrigagem by comparing the estimated values with those determined in the laboratory. The results showed that the technique was able to estimate the nutrient content efficiently

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