Abstract The aim was to estimate the minimum number of plants required per plot to assess the anthracnose severity by artificial inoculation of V2 stage plants. Seventy-eight carioca common bean cultivars were inoculated in 13 experiments to assess its reaction to races 65, 73, 81, and 89 of Colletotrichum lindemuthianum. Sample sizes ranged from one to nine plants were adopted to setting the number of plants per plot. A total of 1000 samplings were performed for each sample size. The following parameters were estimated in each sampling: accuracy, coefficient of variation and Pearson's correlation. The mean values of each parameter in the 1000 samplings for each sample size were subjected to quadratic regression with a plateau as a function of sample size for each experiment. Six plants per plot were needed to assess the severity of anthracnose by artificially inoculating the pathogen on common bean plants at the V2 stage. V Seventyeight Seventy eight 1 65 73 81 8 lindemuthianum 100 sampling accuracy Pearsons Pearson s correlation experiment 6 7 10

ABSTRACT Elephant grass is an allogamous perennial forage crop with asexual propagation, allowing plant breeders to explore heterosis and develop hybrids. However, selecting parents for diallel crossing schemes is a major hurdle in the development of hybrids. In addition, this perennial crop has several harvests, which increases the dataset size and the complexity of the statistical analyses. Here, we propose a diallel analysis based on linear mixed models with repeatability information to identify parents and hybrids, and the optimum number of harvests. We performed a complete diallel crossing of 11 parents with data from five harvests for morphological traits and two harvests for nutritive value traits. The diallel model with repeatability information aids in the estimation of the genetic effect of diallel analysis to infer the ideal number of harvests and genotype × harvest interaction. We observed that the specific combining ability (SCA) is more critical for morphoagronomic traits, while the general combining ability (GCA) has greater importance for traits related to nutritive value. Furthermore, we detected that five harvests were sufficient for the morphoagronomic traits with a coefficient of determination (R2) of 0.8; however, ten harvests were required for an R2 of 0.9. The model is a promising single-analysis alternative for plant breeders to analyze a diallel with repeated measures and to estimate important parameters without incurring in additional financial costs. propagation hybrids However addition analyses Here 1 interaction SCA (SCA GCA (GCA Furthermore R (R2 0.8 08 0 8 however 09 9 0.9 singleanalysis single costs (R 0.

ABSTRACT. The genotype by environment interaction is the main factor that influences the response of evaluated genotypes in trials of value for cultivation and use. Adaptability and stability analyses are fundamental to understanding the performance of genotypes in a growing region. Some of these methodologies incorporate previous information for recommending an extra group of genotypes denominated as specific ideotypes under certain cultivation conditions. Based on this strategy, the centroid method and its modifications have been widely used due to the simplicity of classification of the evaluated genotypes. However, these methodologies present problems in identifying adaptability patterns of some genotypes. Artificial intelligence techniques, such as fuzzy C-means, can be an alternative to reduce these difficulties, since they use, in addition to distance information between genotypes, memberships (measures quantifying how much an observation belongs to a particular class) to increase discriminatory power. Therefore, our aim was to propose and evaluate the phenotypic adaptability method by fuzzy clustering to assist cultivar recommendations. The adaptation of the fuzzy C-Means method to classify the genotypes was implemented in BioFuzzy software. The grain yield data of black common bean genotypes were used to evaluate the potential of the method. The results obtained by this method were compared with those obtained by the centroid method. The phenotypic adaptability method by fuzzy clustering was effective in identifying the adaptability patterns of common bean genotypes. Moreover, the discriminatory power was higher than that observed with the centroid method. ABSTRACT use region conditions strategy However techniques Cmeans, Cmeans C means, means C-means difficulties measures class Therefore recommendations CMeans Means software Moreover

Abstract Carioca grains are the most cultivated commercial group of common bean and Fusarium oxysporum f. sp. phaseoli (Fop) is an important disease under field conditions. Genetic resistance is the most effective control strategy. Thus, our objective was to study the inheritance of Fop resistance in the carioca grain type common bean. Lines CNFC 11965 (S) and CVIII 8511 (R) were crossed to obtain F1 and F2 generations and backcrosses, inoculated with the isolate FOP UFV 01, and severity grades used to estimate genetic parameters. Segregation of resistant and susceptible plants in the F2 generations and backcrosses resulted in dominant monogenic inheritance of Fop resistance. The high values of heritability emphasized the probability of success in the selection processes because environmental factors were not significant. The carioca grain line CVIII 8511 is promising, and its Fop resistance gene can be transferred to commercial cultivars of this group using the backcross method.

Abstract In this manuscript we discuss the purpose and scope of biometry and its interactions, complementation, and even overlap with several other areas of genetics. We emphasize that biometry is an area of genetics that enables researchers to analyze, process, and interpret biological phenomena from data, usually obtained from experimental tests, in an improved way to guide strategies and decision making for optimization of resources. We also highlight the importance of the biometry professional in the context of breeding and the need for continual training, due to new demands for and challenges from inclusion of different types of information for processing and analysis paradigms to better interpret these paradigms.

Abstract The aims of this study were to estimate genetic parameters, predict genotypic values, and analyze the genotypic divergence in S0 and S1 peach trees evaluated in a subtropical environment by the mixed model methodology. For this, twenty-two clones were evaluated for plant and fruit traits. Genotypic variance among clones was significant. The individual broad-sense heritabilities ranged from 0.11 to 0.84, and the individual repeatability coefficients ranged from 0.15 to 0.89. The genotypic coefficients of variation were higher than 10% for most of the traits. Clustering based on plant and fruit traits led to the formation of two and five mutually exclusive groups, respectively. Multivariate analysis of principal components indicated that some traits could be excluded from genetic evaluation. Considering the yield trait and the selection of five clones, predicted gain from selection was 70%, which shows the possibility of considerable genetic progress from clonal selection in peach trees.

ABSTRACT Jatropha curcas L. is a perennial plant with great potential for biodiesel production. Thus, the aim of this study was to select J. curcas genotypes for bioenergy purpose considering multitrait, multiharvest and effective population size. To this end, a data set with 70 J. curcas families, obtained through controlled crosses, evaluated in a randomized block design, with six replications, three plants per plot, spaced at 4 × 2 m was used. The following traits were evaluated: plant height in the 2014 and 2015 crop seasons; canopy projection in the row (2015 crop season); canopy projection between rows (2015 crop season); and grain yield (2015, 2016, and 2017 harvests). The mixed model methodology was used to estimate the variance components and to predict the genetic values. Superior genotypes were selected through Multitrait index based on factor analysis and genotype-ideotype distance (FAI-BLUP index), considering the effective population size. According to this index, 98% of all additive genetic variability were summarized in three factors. By adopting the selection intensity that allows maintaining the effective population size equal to 30 (i.e., selection of 214 individuals), the predicted gains were 15.56, 21.75, 4.16, and 5.37% for the traits grain yield in the 2015 and 2016 harvests, canopy projection in the row, and canopy projection between rows in the 2015 crop season, respectively. Thus, the results suggest that the FAI-BLUP index can be successfully used in J. curcas breeding.

RESUMO: O cultivo do pessegueiro em regiões de inverno ameno é viabilizado pela utilização de genótipos que apresentam baixa necessidade de frio, sendo este um dos principais objetivos do melhoramento para essas regiões. Assim, os objetivos deste estudo foram estimar parâmetros genéticos, avaliar a variabilidade genética e selecionar famílias adaptadas a regiões de inverno ameno em geração S1 de pessegueiros via metodologia de modelos mistos (REML/BLUP). Para isso, 22 populações, 84 famílias e 2090 indivíduos foram avaliados quanto as características: taxa de brotação (TB), densidade de nós (DN), altura da planta (AP) e diâmetro do tronco (DT). Verificou-se variabilidade genética para todas as características. As herdabilidades individuais no sentido amplo foram de baixa e média magnitudes. A característica AP apresentou correlação genética positiva de magnitude elevada com DT. A característica DN apresentou correlação genética negativa moderada com AP e DT. O agrupamento pelo método de Tocher resultou na formação de seis grupos mutuamente excludentes. Considerando intensidade de seleção de 25%, a seleção simultânea para TB, DN e DT propiciou ganhos preditos de 11.3% para TB, 9.7% para DN, -14.2% para AP e -14.3% para DT, evidenciando o grande potencial do germoplasma avaliado.

ABSTRACT: The growing of peach in mild winter regions is made viable through the use of genotypes that have low need for cold conditions, and this is one of the main aims of breeding for these regions. Thus, the aims of this study were to estimate genetic parameters, evaluate genetic variability, and select families adapted to mild winter regions in the S1 generation of peach through mixed model methodology (REML/BLUP). For that purpose, 22 populations, 84 families, and 2090 individuals were evaluated for the following traits: bud burst rate (BR), node density (ND), plant height (PH), and trunk diameter (TD). Genetic variability was found for all the traits. Individual heritability in the broad sense was of low and medium magnitudes. The PH trait had positive genotypic correlation of high magnitude with TD. The ND trait had moderate negative genotypic correlation with PH and TD. Clustering by the Tocher method resulted in the formation of six mutually exclusive groups. Considering selection intensity of 25%, simultaneous selection for BR, ND, and TD led to predicted gains of 11.3% for BR, 9.7% for ND, -14.2% for PH, and -14.3% for TD, showing the great potential of the germplasm evaluated.

Resumo: O objetivo deste trabalho foi avaliar a eficiência dos métodos de Eberhart & Russell e Lin & Binns, modificados para automação da tomada de decisão pela lógica difusa, na avaliação da adaptabilidade e da estabilidade de cultivares de feijoeiro-comum (Phaseolus vulgaris). Foram avaliadas 18 cultivares do grupo comercial carioca em 11 ambientes, no Brasil. Todos os resultados foram obtidos por programação no programa R. Os controladores desenvolvidos foram fundamentados no sistema de inferência difusa desenvolvido por Mamdani. Este sistema foi modelado para possibilitar interpretações do método de Eberhart & Russell isoladamente ou em conjunto com o método de Lin & Binns modificado. O controlador baseado em Eberhart & Russell e o baseado em Eberhart & Russell e Lin & Binns identificaram as mesmas cultivares como tendo adaptabilidade geral, mas diferiram quanto à classificação das cultivares adaptadas a ambientes desfavoráveis. As cultivares BRSMG Pioneiro, BRS Pontal, IAC-Carioca Tybatã e IPR Juriti apresentaram adaptabilidade geral, enquanto Campeão, Pérola e BRS Estilo mostraram adaptabilidade específica a ambientes favoráveis. Os métodos de lógica difusa utilizados mostram eficiência e possibilitam a classificação de todas as cultivares avaliadas.

Abstract: The objective of this work was to evaluate the efficiency of the methods of Eberhart & Russell and Lin & Binns, modified for the automation of decision-making by fuzzy logic, in assessing the adaptability and stability of common bean (Phaseolus vulgaris) cultivars. Eighteen cultivars of the “carioca” commercial group were evaluated in 11 environments, in Brazil. All results were obtained by programming in the R software. The developed controllers were based on the fuzzy inference system developed by Mamdani. This system was modeled to enable interpretations of the method of Eberhart & Russell alone or together with the modified method of Lin & Binns. The controller based on Eberhart & Russell and the one based on Eberhart & Russell and Lin & Binns identified the same cultivars as having general adaptability, but differed as to the classification of cultivars adapted to unfavorable environments. The BRSMG Pioneiro, BRS Pontal, IAC-Carioca Tybatã, and IPR Juriti cultivars presented general adaptability, whereas Campeão, Pérola, and BRS Estilo showed specific adaptability to favorable environments. The fuzzy logic methods used are efficient and allow the classification of all evaluated cultivars.

Abstract Studies highlight the hypocotyl diameter (HD) as an effective indicator of plant architecture (PA). Here, we estimated the genetic gain based on HD to improve PA. Twenty populations of cycles zero (C0) and one (C1), both in the F4 generation, were evaluated for PA, grain yield (GY) and HD. Plants with thickest HD in C0 were intercrossed in a circulant diallel mating design. In cycle C1, an estimated genetic gain of 4.93% was achieved for PA and 4.95% for HD. The populations with the highest probability of breeding lines with a thicker HD belong to cycle C1, and this selection strategy did not alter the GY of the populations of this cycle. Thus, indirect selection based on HD is promising for breeding for common bean PA by recurrent mass selection.

RESUMO. O presente estudo tem como objetivo propor sistemas de controle fuzzy para auxiliar na recomendação de cultivares de diversas culturas agronômicas. Para avaliar a aplicabilidade desses controladores foram utilizados dados de produtividade de grãos de 23 linhagens e duas cultivares de feijão do grupo comercial vermelho, avaliados em nove ambientes da Zona da Mata do Estado de Minas Gerais, Brasil. A partir dos parâmetros da análise de Eberhart e Russell foram desenvolvidos controladores fuzzy com sistemas de inferência Mamdani e Sugeno. Foram realizadas análises de variância conjunta e de adaptabilidade e estabilidade pelo método de Eberhart e Russell e os parâmetros obtidos para cada linhagem foram submetidos aos respectivos controladores. Verificou-se a ocorrência de interação genótipos por ambientes significativa, existindo a necessidade da realização de análises de adaptabilidade e estabilidade. Em ambos os controladores (Mamdani e Sugeno), sete linhagens (2, 9, 14, 16, 17, 20 e 23) apresentaram adaptabilidade geral, enquanto que somente a linhagem 15 apresentou adaptabilidade a ambientes desfavoráveis. Verificou-se também que ambos os sistemas de inferência adotados, são úteis para desenvolver controladores que visam recomendação de cultivares. Assim, constatou-se potencialidade dos sistemas de controle fuzzy na identificação do comportamento das linhagens de feijoeiro.

ABSTRACT. The objective of the present study was to propose fuzzy control systems to support the recommendation of cultivars of different agronomic crops. Grain yield data from 23 lines and 2 cultivars of red bean were used to evaluate the applicability of these controllers. Genotypes were evaluated in nine environments in the Zona da Mata region, Minas Gerais State, Brazil. Using the parameters of Eberhart and Russell analysis, fuzzy controllers were developed with the Mamdani and Sugeno inference systems. Analyses of adaptability and stability were carried out by the method of Eberhart and Russell. The parameters obtained for each genotype were submitted to the respective controllers. There were significant genotypes x environments interaction, which justified the necessity of performing an adaptability and stability analysis. For both controllers (Mamdani and Sugeno), seven lines presented general adaptability, while only one presented adaptability to unfavorable environments. It was also found that both inference systems were useful for developing controllers that had the aim of recommending cultivars. Thus, it was noted that fuzzy control systems have the potential to identify the behavior of bean genotypes.

RESUMO. Dentre os caracteres tecnológicos que ainda precisam ser melhorados no algodoeiro, destaca-se o comprimento das fibras. Deste modo, os objetivos com este trabalho foram quantificar as inter-relações entre caracteres agronômicos e tecnológicos de fibras e identificar caracteres que possam ser utilizados para a seleção indireta de genótipos de algodoeiro com maior comprimento de fibras. Foram avaliados caracteres agronômicos e tecnológicos em 36 linhagens elite de algodoeiro cultivadas em três ambientes. Foram estimadas as correlações canônicas entre dois grupos de caracteres: agronômicos e tecnológicos. Realizou-se análise de trilha considerando o comprimento de fibras como variável dependente principal. Os genótipos apresentaram variabilidade para todos os caracteres avaliados e não houve interação genótipos x ambientes significativa para nenhum caráter. É possível melhorar os principais caracteres tecnológicos do algodoeiro a partir da seleção indireta em caracteres agronômicos. A seleção de genótipos de algodoeiro com menor porte e maior peso médio de capulhos pode ser uma estratégia para aumentar o comprimento de fibras e melhorar os demais caracteres tecnológicos. Índices de seleção contendo altura de plantas, peso de capulhos, resistência e uniformidade de fibras é uma das principais estratégias para selecionar genótipos de algodoeiro com alta produtividade de algodão em caroço e fibras longas.

ABSTRACT. Fiber length stands out among technological traits as one that still needs to be improved in cotton. Thus, the objectives of this work were to quantify the interrelations between agronomic and technological fiber traits and to identify traits that could be used for the indirect selection of cotton genotypes with longer fiber lengths. Agronomic and technological traits were evaluated in 36 elite lines of cotton that were cultivated in three environments. Canonical correlations were estimated between two groups of traits: agronomic and technological. Path analysis was performed that considered fiber length as the primary dependent variable. The genotypes presented variability in all the evaluated traits, and no significant genotype vs. environmental interaction was observed for any of them. The main technological traits of cotton crops can be improved by an indirect selection of agronomic traits. The selection of cotton genotypes with a smaller size and a higher mean boll weight can be used to increase fiber length and improve other technological traits. Selection indices containing plant height, mean boll weight, fiber strength, and fiber uniformity can be one of the main strategies for the selection of cotton genotypes with a high yield of cotton bolls and long fibers.

RESUMO O conhecimento da adaptabilidade e estabilidade da produção de frutos em diferentes locais ou anos é crucial para aumentar o potencial de produção agrícola. Por isso, o objetivo deste trabalho foi avaliar a existência de interação entre cultivares e anos, bem como avaliar a estabilidade de cultivares de pessegueiro e nectarineira quanto à massa de matéria fresca de fruto, relação SS/AT e duração de ciclo nas condições de Viçosa-MG. Para isto foram avaliadas 28 cultivares de pessegueiro e duas cultivares de nectarineira pertencentes ao pomar da Universidade Federal de Viçosa nos anos de 2011, 2012 e 2013. Foram avaliados os caracteres massa de matéria fresca de fruto, relação SS/AT e duração de ciclo e utilizados os métodos Tradicional e de Eberhart & Russell (1966) para estudo da estabilidade fenotípica no tempo. A interação cultivares x anos é significativa para todas as características. ‘Josefina’ apresenta adaptabilidade geral para relação SS/AT, e ‘Flordaprince’ e ‘Tropical’ para duração de ciclo. Para ambientes favoráveis são indicadas as cultivares ‘Capdebosq’ e ‘Maciel’ quanto à característica massa de fruto, e ‘Coral’ e ‘Talismã’ quanto à relação SS/AT. ‘Rubimel’ é indicada para ambiente desfavorável com relação à massa de fruto.

ABSTRACT Information on adaptability and stability of fruit production in different environments or years is crucial to increasing agricultural production potential. Therefore, the objective of this study was to evaluate whether there is interaction between cultivars and years, as well as to assess the stability of peach and nectarine cultivars regarding fruit fresh mass, SS/TA ratio, and cycle length in Viçosa -MG, Brazil. The characteristics fruit fresh mass (FM), soluble solids/titratable acidity ratio (SS/TA), and cycle length (CL) were evaluated in 28 cultivars of peach and two cultivars of nectarine from the orchard of the Universidade Federal de Viçosa, in 2011, 2012, and 2013. The methods used to determine the phenotypic stability across time were Eberhart & Russell (1966) and the Traditional. The interaction cultivars x years was significant for all traits. Cultivar ‘Josefina’ showed broad adaptability for SS/TA ratio, and cultivars ‘Flordaprince’ and ‘Tropical’ for cycle length. For favorable environments, the cultivars ‘Capdebosq’ and ‘Maciel’ are indicated regarding the characteristic fruit mass, and ‘Coral’ and ‘Talismã’ for SS/TA ratio. ‘Rubimel’ was adaptable to unfavorable environments regarding fruit mass.

RESUMO O objetivo deste trabalho foi avaliar a adaptabilidade e estabilidade de 29 híbridos comerciais de milho, no sudeste de Minas Gerais, com emprego de três metodologias. Os 29 híbridos comercias de milho foram avaliados para produtividade de grãos, em cinco locais do sudeste de Minas Gerais, na safra 2014/2015. Utilizou-se o delineamento em blocos ao acaso com duas repetições. Cada parcela foi constituída de duas linhas de cinco metros de comprimento, espaçadas em 0,80 m com área útil de 8,00 m2. Além das análises de variâncias individual e conjunta, empregou-se os métodos de Eberhart & Russell (1966), AMMI (Additive Main Effects and Multiplicative Interaction Analysis) e modelos mistos para avaliar a adaptabilidade e estabilidade dos 29 híbridos. Houve diferença significativa (P < 0,01) para os efeitos de híbridos, ambientes e interação híbridos x ambientes. A maioria dos híbridos avaliados apresentou ampla adaptabilidade e boa estabilidade. Conclui-se que as metodologias de Eberhart & Russell, AMMI e modelos mistos, apresentam resultados semelhantes na classificação de híbridos de milho com ampla adaptabilidade; há divergência na indicação de híbridos com adaptabilidade específica a ambientes favoráveis e desfavoráveis e; com base nas três metodologias, os híbridos SHS7920PRO, BM709PRO2, BRS1055 e o BM650PRO2 apresentam adaptabilidade geral nos ambientes avaliados.

ABSTRACT The aim of this study was to evaluate the adaptability and stability of 29 commercial maize hybrids in the southeast of the State of Minas Gerais, Brazil, employing three methods. The 29 commercial maize hybrids from the 2014/2015 crop were evaluated for grain yield in five locations in the southeast of Minas Gerais. A randomised-block design was used, with two replications. Each lot comprised two rows, five meters in length, at a spacing of 0.80 m, giving an effective area of 8.00 m2. In addition to individual and combined variance analysis, the methods of Eberhart & Russell (1966), AMMI (Additive Main Effects and Multiplicative Interaction Analysis) and mixed models were used to evaluate the adaptability and stability of the 29 hybrids. There was a significant difference (P<0.01) for the effects of hybrid, environment and the hybrid x environment interaction. The majority of the hybrids under evaluation displayed broad adaptability with good stability. It was concluded that the Eberhart & Russell, AMMI and mixed-model methods show similar results in classifying maize hybrids of broad adaptability. There is a difference in indicating hybrids with specific adaptability to favourable and unfavourable environments. Based on the three methods, the hybrids SHS7920PRO, BM709PRO2, BRS1055 and BM650PRO2 show a general adaptability for the environments under evaluation.

Resumo: O objetivo deste trabalho foi avaliar o uso de redes neurais artificiais em comparação à modelagem por meio de modelos lineares generalizados na predição de resistência à ferrugem em café arábica (Coffea arabica). Foram utilizados 245 indivíduos provenientes de uma população F2, oriundos da autofecundação do híbrido F1 H511-1, resultante do cruzamento da cultivar suscetível Catuaí Amarelo IAC 64 (UFV 2148-57) e do genitor resistente Híbrido de Timor (UFV 443-03). Os 245 indivíduos foram genotipados com 137 marcadores. Realizaram-se análises com redes neurais artificiais e com modelos lineares generalizados sob o enfoque bayesiano. As redes neurais identificaram quatro marcadores importantes pertencentes a grupos de ligação que foram recentemente mapeados, enquanto o modelo generalizado bayesiano identificou somente dois marcadores pertencentes a esses grupos. Foram observadas taxas de erro de predição inferiores (1,60%) para predizer a resistência à ferrugem em café arábica, quando foram utilizadas as redes neurais artificiais em vez de modelos lineares generalizados sob o enfoque bayesiano (2,4%). Os resultados mostraram que as redes neurais artificiais são uma abordagem promissora para predizer a resistência à ferrugem em café arábica.

Abstract: The objective of this work was to evaluate the use of artificial neural networks in comparison with Bayesian generalized linear regression to predict leaf rust resistance in Arabica coffee (Coffea arabica). This study used 245 individuals of a F2 population derived from the self-fertilization of the F1 H511-1 hybrid, resulting from a crossing between the susceptible cultivar Catuaí Amarelo IAC 64 (UFV 2148-57) and the resistant parent Híbrido de Timor (UFV 443-03). The 245 individuals were genotyped with 137 markers. Artificial neural networks and Bayesian generalized linear regression analyses were performed. The artificial neural networks were able to identify four important markers belonging to linkage groups that have been recently mapped, while the Bayesian generalized model identified only two markers belonging to these groups. Lower prediction error rates (1.60%) were observed for predicting leaf rust resistance in Arabica coffee when artificial neural networks were used instead of Bayesian generalized linear regression (2.4%). The results showed that artificial neural networks are a promising approach for predicting leaf rust resistance in Arabica coffee.