ABSTRACT. The selection of superior sweet potato genotypes using Bayesian inference is an important strategy for genetic improvement. Sweet potatoes are of social and economic importance, being the material for ethanol production. The estimation of variance components and genetic parameters using Bayesian inference is more accurate than that using the frequently used statistical methodologies. This is because the former allows for using a priori knowledge from previous research. Therefore, the present study estimated genetic parameters and selection gains, predicted genetic values, and selected sweet potato genotypes using a Bayesian approach with a priori information. Root shape, soil insect resistance, and root and shoot productivity of 24 sweet potato genotypes were measured. Heritability, genotypic variation coefficient, residual variation coefficient, relative variation index, and selection gains direct, indirect and simultaneous were estimated, and the data were analyzed using Bayesian inference. Data from 11 experiments were used to obtain a priori information. Bayesian inference was a useful tool for decision-making, and significant genetic gains could be achieved with the selection of the evaluated genotypes. Root shape, soil insect resistance, commercial root productivity, and total root productivity showed higher heritability values. Clones UFVJM06, UFVJM40, UFVJM54, UFVJM09, and CAMBRAIA can be used as parents in future breeding programs.

ABSTRACT In agricultural experimentation, use of the optimum plot size is an important way of increasing experimental precision; however, studies of this type are scarce for the chickpea, a legume that has been conquering both the market and consumers throughout the world. The aim of this study, therefore, was to determine the optimum plot size for evaluating experiments with the chickpea, in scenarios comprising combinations of the number of treatments, number of replications and levels of precision. Two blank experiments were carried out, comprising eight crop rows, 7 m in length, at a spacing of 50 cm between rows and 10 cm between plants; the six central rows were evaluated, giving a total of 60 plants per row. The index of soil heterogeneity was determined, and the optimum plot size was estimated using the Hatheway method in scenarios formed by a combination of i treatments (i = 4, 8, 12 and 16), r replications (r = 3, 4, 5, 6, 7 and 8) and levels of precision (LSD = 25%, 30% and 40%). The index of soil heterogeneity was greater than 0.7 for each of the variables under evaluation. The Hatheway method makes it possible to estimate different plot sizes based on the conditions and limitations of the experimental area. In experiments with the chickpea including 4 to 16 treatments, 25% LSD and six replications, plots of 25 basic units are sufficient to identify significant differences between the mean values of the treatments with a probability of 5%.

RESUMO Na experimentação agrícola, a utilização do tamanho ótimo de parcela é uma estratégia importante, para aumentar a precisão experimental, e trabalhos desta natureza são escassos para a cultura do grão-de-bico, leguminosa que vem conquistando o mercado e consumidores em todo o mundo. Assim, o objetivo deste trabalho foi determinar o tamanho ótimo de parcela, para avaliar experimentos com a cultura do grão-de-bico, em cenários formados por combinações de números de tratamentos, números de repetições e níveis de precisão. Dois experimentos em branco foram realizados, compostos por oito linhas de cultivo, de 7 m de comprimento, espaçadas em 50 cm entre linhas e 10 cm entre plantas; foram avaliadas as seis linhas centrais, totalizando 60 plantas por linha de cultivo. Foi determinado o índice de heterogeneidade do solo e o tamanho ótimo de parcela foi estimado por meio do método de Hatheway, em cenários formados pelas combinações de i tratamentos (i = 4, 8, 12 e 16), r repetições (r = 3, 4, 5, 6, 7 e 8) e níveis de precisão (DMS = 25%, 30% e 40%). O índice de heterogeneidade do solo foi superior a 0,7 para todas as variáveis avaliadas. O método de Hatheway possibilita estimar diferentes tamanhos de parcelas, de acordo com as condições e limitações da área experimental. Em experimentos com o grão-de-bico, com 4 a 16 tratamentos, DMS de 25% e seis repetições, as parcelas de 25 unidades básicas são suficientes para identificar, com probabilidade de 5%, diferenças significativas entre as médias dos tratamentos.

ABSTRACT. Among the forage species, especially in semiarid ecosystems, cactus pear is exceptional because of its high tolerance to adverse conditions and high productivity. Due to this alone, several studies have been conducted to identify the main technologies for this crop. Despite being consolidated and integrated, the cactus pear production system has limited accessibility, technical assistance, and availability of information for those dedicated to its production. This study aimed to present a digital platform, website, and applications to provide technical information on the cactus pear and demonstrate the efficiency of these applications through experimental data. On this digital platform, applications were made available for predicting the productivity of cactus pear using artificial neural networks (ANN) on a computer with routines in the R software and by simple linear regression (SLR) on smartphones on the Android system of the MIT App Inventor 2 platform. In addition, using the smartphone app, it is possible to obtain the cladode area through multiple linear regression (MLR). It is also possible to obtain the estimates of the experimental plot sizes by the maximum modified curvature, linear and quadratic methods with plateau response, relative information, comparison of variances, and convenient plot size. The platform provides technical information associated with the cactus pear crop from different sources (dissertations, theses, articles) and formats (video classes and teaching resources), offline for applications, and online with download for publications, dissertations, theses and articles, video classes, and several didactic resources. The biomathematical models integrated with the applications were highly precise in predicting the phenomena, in which the variation explained by the models in the prediction of responses for future observations had R² values of 0.95, 0.72, and 0.92, respectively, for productivity with computer-ANN and smartphone-SLR, and for the cladode area with a smartphone - MLR.

ABSTRACT Traditional germination tests which assess seed quality are costly and time-consuming, mainly when performed on a large scale. In this study, we assessed the efficiency of X-ray imaging analyses in predicting the physiological quality of tomato seeds. A convolutional neural network (CNN) called mask region convolutional neural network (MaskRCNN) was also tested for its precision in adequately classifying tomato seeds into four seed quality categories. For this purpose, X-ray images were taken of seeds of 49 tomato genotypes (46 Solanum pennellii introgression lines) from two different growing seasons. Four replicates of 25 seeds for each genotype were analyzed. These seeds were further assessed for germination and seedling vigor-related traits in two independent trials. Correlation analysis revealed significant linear association between germination and image-based variables. Most genotypes differed in terms of germination and seed development performance considering the two independent trials, except LA 4046, LA 4043, and LA4047, which showed similar behavior. Our findings point out that seeds with low opacity and percentage of damaged seed tissue and high values for living tissue opacity have greater physiological quality. In short, our work confirms the reliability of X-ray imaging and deep learning methodologies in predicting the physiological quality of tomato seeds.

RESUMO: Varronia curassavica é uma espécie medicinal nativa no Brasil e sua propriedade anti-inflamatória é atribuída aos compostos α-humuleno e β-cariofileno. O objetivo foi estudar a variabilidade de população de V. curassavica. Foram coletadas folhas de 40 indivíduos de população natural, sendo estas transferidas para frascos de vidro (2 mL). Os voláteis foram extraídos e analisados por headspace estático, associado à cromatografia gasosa, acoplada à espectrometria de massas (HS-CG-EM). Detectou-se 17 compostos: monoterpenos (1,6% - 68%) e sesquiterpenos (25,7% - 79,0%), incluindo o α-humuleno e o β-cariofileno. A análise multivariada foi realizada para estimar a dissimilaridade dos indivíduos, a qual separou quatro grupos. O grupo I foi caracterizado pela presença do α-pineno, os grupos II e IV do β-cariofileno e o grupo III do β-pineno. O teor do α-humuleno apresentou pequenas variações, enquanto o do β-cariofileno contribuiu mais para a variabilidade da população. É o primeiro relato de análise da composição química de compostos voláteis de V. curassavica utilizando a técnica HS-GC-MS.

ABSTRACT: Varronia curassavica is a medicinal species native to Brazil; its anti-inflammatory properties are attributed to α-humulene and β-caryophyllene. This study to investigated the population variability of V. curassavica. Leaves were collected from 40 individuals of a natural population and transferred to glass flasks (2 mL). The volatiles were extracted and analyzed using static headspace gas chromatography coupled with mass spectrometry (HS-GC-MS). A total of 17 compounds were detected: monoterpenes (1.6% - 68%) and sesquiterpenes (25.7% - 79.0%), including α-humulene and β-caryophyllene. Multivariate analysis was performed to estimate the dissimilarity of individuals separated the compounds into four groups. Group I was characterized by the content of α-pinene, groups II and IV by β-caryophyllene, and group III by β-pinene. The abundance of α-humulene showed small variations; while β-caryophyllene showed larger variations that contributed to the population variability. This is the first report on the chemical composition analysis of volatile compounds in V. curassavica using the HS-GC-MS technique.

ABSTRACT. The purpose of the present study was to evaluate the principal component analysis (PCA) to guide technical assistance regarding several dairy farms’ issues, which includes improving microbiological quality and physical-chemical composition of raw refrigerated milk. Data of monthly analysis of fat, protein, lactose, dry defatted stratum, somatic cell count, total bacterial count, milk temperature of 8,101 samples of milk from expansion tanks and production of 78 farms located in the northern region of Minas Gerais, Brazil were processed. Descriptive statistical measures and Pearson correlation coefficient were estimated involving all evaluated traits during the dry and rainy seasons. In addition, multivariate analyses were performed using PCA. The results showed that two farm sites were negatively related to milk quality in both seasons. One farm stood out positively, being able to be used as a herd management model to drive technical assistance actions. Thus, PCA is efficient in simplifying large amounts of data, allowing simpler and faster technical herd management interpretation.

Resumo: A couve (Brassica oleracea var. acephala) apresenta grande importância devido a sua facilidade de propagação, aceitabilidade e às suas propriedades nutracêuticas. O objetivo no presente trabalho foi realizar ajustes metodológicos para a condução do teste de tetrazólio em sementes de couve. Inicialmente foram realizados pré-testes com relação ao tempo de pré-condicionamento a 20 °C por 10 e 14 horas (tempos definidos pela curva de embebição) e métodos de remoção do tegumento das sementes de couve (remoção total do tegumento; corte na região distal ao eixo embrionário; corte longitudinal no maior sentido e sementes inteiras). Posteriormente, as metodologias mais eficientes foram avaliadas usando diferentes concentrações da solução do sal de tetrazólio (0,075%; 0,2%; 0,5% e 1,0%) e tempos (2, 4 e 6 h) de imersão das sementes na solução, utilizando-se quatro lotes. As sementes foram analisadas individualmente e classificadas como viáveis ou não viáveis. O teste de tetrazólio é eficiente para a avaliação da viabilidade de sementes de couve fornecendo resultados correlacionados com a germinação. As sementes de couve devem ser pré-condicionadas entre papel por 10 horas a 20 °C, e ter o tegumento removido para imersão em solução do sal de tetrazólio a 0,5% por 4 horas a 30 °C.

Abstract: Kale (Brassica oleracea var. acephala) has great importance due to its easy propagation, acceptability and nutraceutical properties. The aim of the present work was to make methodological adjustments to conduct the tetrazolium test in kale seeds. Pre-tests were initially carried out to assess the priming time at 20 °C for 10 and 14 hours (times defined by the imbibition curve) and methods of removing the coat of kale seeds (total removal of the seed coat; cut in the distal region to the embryonic axis; longitudinal cut along the longest axis and whole seeds). Subsequently, the most efficient methodologies were evaluated using different concentrations of the tetrazolium salt solution (0.075%; 0.2%; 0.5% and 1.0%) and times (2, 4 and 6 h) of seed immersion in the solution, using four lots. The seeds were analyzed individually and classified as viable or non-viable. The tetrazolium test is efficient for evaluating the viability of kale seeds, providing results correlated with germination. Kale seeds should be primed between paper for 10 hours at 20 °C, and the seed coat should be removed for immersion in a 0.5% tetrazolium salt solution for 4 hours at 30 °C.

RESUMO: Nos últimos anos, tem aumentado o interesse crescente pelo uso de resíduos orgânicos na agricultura. Dessa forma, objetivou-se com este estudo avaliar o biochar e a casca do pequi (Caryocar brasiliense Cambess) nas propriedades químicas do solo e na produção e nutrição de plantas de feijoeiro. O experimento foi realizado em vasos com solo (4 dm3 ~ 5,44 kg), em delineamento experimental inteiramente casualizado, em esquema fatorial 4 x 3 + 2, com quatro repetições. Os tratamentos foram quatro doses de biochar (0,0, 2,5, 5,0, 7,5 e 10,0 % v/v), três tamanhos de partículas diferentes (G1, <0,5 mm; G2, 0,5-1,0 mm e G3, 1,0-2,0 mm) e dois tratamentos controle, um sem e outro com adição de corretivo da acidez do solo. O biochar de casca do pequi atuou como corretivo da acidez do solo e como fonte de potássio para as plantas. Entretanto, em doses mais elevadas de biochar, houve uma diminuição na produção das plantas de feijão devido aos desequilíbrios nutricionais.

ABSTRACT: In recent years there has been a growing interest in the use of organic waste in agriculture. In this way, was aimed with this study to evaluate the biochar from pequi shell (Caryocar brasiliense Cambess) on the soil chemical properties and on the production and nutrition of common bean plants. The experiment was carried out in pots with soil (4 dm3 ~ 5,44 kg), in a completely randomized experimental design, 4 x 3 + 2 factorial scheme, with four replications. The treatments were four doses of biochar (0.0, 2.5, 5.0, 7.5 and 10.0 % v/v), three different particle size (G1, <0.5 mm; G2, 0.5-1,0 mm and G3, 1.0-2.0 mm) and two control treatments, one without and another with addition of soil corrective acidity. The biochar from pequi shell acted as a corrective of soil acidity and as a source of potassium for the plants. However, in higher doses of biochar there was a decrease in bean plants production due to nutritional imbalances.

Resumo O objetivo deste trabalho foi avaliar a dissimilaridade genética entre cultivares e genótipos de soja para a seleção de genitores, bem como propor um novo método para a utilização de mapas auto-organizáveis de Kohonen (SOMs) e testar sua eficiência por meio da análise discriminante de Anderson. Foram avaliados os descritores morfoagronômicos de cultivares e genótipos de soja. Para análise dos dados, utilizaram-se redes neurais artificiais do tipo SOM. O método proposto permitiu a determinação da melhor arquitetura de rede de forma não subjetiva. Além disso, no início do treinamento, foi possível mitigar o efeito da aleatoriedade dos pesos sinápticos sobre os grupos formados. Foram formados seis grupos dissimilares; portanto, há dissimilaridade genética entre cultivares e genótipos de soja. As cultivares C25, C8 e C13 podem ser combinadas com as C36, C31, C32 e C33, por apresentarem bons atributos de produtividade e alta dissimilaridade. A metodologia proposta é vantajosa em comparação ao uso de SOMs tradicionais e se mostrou eficiente devido à consistência dos agrupamentos de acordo com a análise discriminante de Anderson.

Abstract The objective of this work was to evaluate the genetic dissimilarity between soybean cultivars and genotypes for the selection of parents, as well as to propose a new method for using Kohonen’s self-organizing maps (SOMs) and to test its efficiency through Anderson’s discriminant analysis. The morphoagronomic descriptors of soybean cultivars and genotypes were evaluated. For data analysis, SOM-type artificial neural networks were used. The proposed method allowed the determination of the best network architecture in a nonsubjective way. Furthermore, at the beginning of training, it was possible to mitigate the randomness effect of the synaptic weights on the formed clusters. Six dissimilar clusters were formed; therefore, there is genetic dissimilarity between soybean cultivars and genotypes. Cultivars C25, C8, and C13 can be combined with C36, C31, C32, and C33 because they show good yield-related attributes and high dissimilarity. The proposed methodology is advantageous in comparison with the use of traditional SOMs, besides being efficient due to clustering consistency according to Anderson’s discriminant analysis.

ABSTRACT. Leaf area is one of the most commonly used physiological parameters in plant growth analysis because it facilitates the interpretation of factors associated with yield. The different leaf formats related to soybean genotypes can influence the quality of the model fit for the estimation of leaf area. Direct leaf area measurement is difficult and inaccurate, requires expensive equipment, and is labor intensive. This study developed methodologies to estimate soybean leaf area using neural networks and considering different leaf shapes. A field experiment was carried out from February to July 2017. Data were collected from thirty-six cultivars separated into three groups according to the leaf shape. Multilayer perceptrons were developed using 300 leaves per group, of which 70% were used for training and 30% for validation. The most important morphological measures were also tested with Garson’s method. The artificial neural networks were efficient in estimating the soybean leaf area, with coefficients of determination close to 0.90. The left leaflet width and right leaflet length are sufficient to estimate the leaf area. Network 4, trained with leaves from all groups, was the most general and suitable for the prediction of soybean leaf area.

Resumo O objetivo deste trabalho foi estimar o número ótimo de colheitas para a seleção confiável de híbridos de abobrinha-italiana (Cucurbita pepo) por meio do coeficiente de repetibilidade. O delineamento experimental foi em blocos ao acaso, com 33 tratamentos (31 híbridos experimentais e 2 comerciais) e quatro repetições, com seis plantas por parcela. Realizaramse 15 colheitas. Sete características morfoagronômicas dos frutos foram avaliadas, e os coeficientes de repetibilidade foram estimados por meio de quatro métodos estatísticos. Os coeficientes de repetibilidade variaram de baixos a moderados, independentemente da característica estudada. Para uma seleção de alta precisão (R2≥90%), um elevado número de colheitas avaliadas foi necessário, especialmente para as características relacionadas à produtividade de frutos, conforme a seguir: 30 a 54 colheitas para a seleção baseada na produtividade total; e 43 a 83 colheitas para a0 produtividade comercial, que variou conforme o método estatístico de estimação. A análise de componentes principais baseada na matriz de covariância demandou a menor quantidade de colheitas para uma precisão satisfatória da seleção. São suficientes 15 colheitas para a seleção satisfatória de todas as características avaliadas, com precisão superior a 70%.

Abstract The objective of this work was to estimate the optimal number of harvests for the reliable selection of zucchini (Cucurbita pepo) hybrids through the repeatability coefficient. The experimental design was randomized complete blocks with 33 treatments (31 experimental hybrids and 2 commercial ones) and four replicates, with six plants per plot. Fifteen harvests were carried out. Seven morphoagronomic fruit characteristics were evaluated, and repeatability coefficients were estimated using four statistical methods. The repeatability coefficients ranged from low to moderate, regardless of the studied characteristic. For a high-precision selection (R2≥90%), a high number of evaluated harvests was required, especially for traits related to fruit yield, as follows: 30 to 54 harvests for selection based on total yield; and 43 to 83 harvests for commercial yield, which varied according to the statistical estimation method. The principal component analysis based on the covariance matrix required the least number of harvests for a satisfactory selection precision. Fifteen harvests are sufficient for a satisfactory selection of all evaluated characteristics, with a precision above 70%.

ABSTRACT: The sampling methods for soil and plant evaluation in integrated production systems need to be refined for their use in experiments. This study purposed a sampling representativeness model to evaluate soil carbon and physiological parameters of marandu palisadegrass intercropped with double rows of eucalyptus in a silvopastoral system in southeastern Brazil. Four transects were delimited within the silvopastoral system and the soil was sampled at 0-5, 5-10, and 10-20 cm depths to evaluate two parameters of soil organic matter: total organic carbon (TOC) and soil microbial carbon (Cmic). We also evaluated three physiological parameters of marandu palisadegrass: stomatal conductance, transpiration rate, and photosynthetic rate. The sampling strategy was evaluated by the Hatheway and Modified Maximum Curvature (MMC) methods. We found that cultivation of the alley with forage grass and double rows of eucalyptus must be considered to ensure sampling representativeness in a silvopastoral system, once TOC and Cmic and physiological parameters showed variation within the integrated production system. The MMC method could be useful to evaluate silvopastoral systems for experiments and characterization of agricultural areas, as 11 soil samples are representative to evaluate Cmic and TOC, and 13 samples are enough to evaluate the physiological parameters in marandu palisadegrass. The Hatheway method could be applied to experiments that need higher accuracy with a reduction in the minimum difference to be detected between the treatments and a consequent increase in the number of samples to be collected.

RESUMO Modelos de predição podem contribuir para a análise de dados e tomada de decisões no manejo de uma cultura. Objetivou-se avaliar a viabilidade da predição de produtividade de bananeiras ‘Prata-Anã’ e ‘BRS Platina’, por meio de redes neurais artificiais, bem como determinar os descritores morfológicos mais importantes para este fim. Foram mensurados a altura de planta; perímetro do pseudocaule ao nível do solo, a 30 e 100 cm de altura; número de folhas vivas na colheita; massa, comprimento e diâmetro do engaço; número de pencas e de frutos; massa do cacho e das pencas; massa média das pencas; e relação entre a massa do engaço e do cacho. Os dados foram submetidos a análise por redes neurais artificiais, utilizando-se o software R. Os melhores ajustes foram obtidos com dois e três neurônios na camada intermediária, respectivamente, para ‘Prata-Anã’ e ‘BRS Platina’. Esses modelos apresentaram os menores erros quadráticos médios, o que corresponde a maior proximidade entre os dados preditos e os reais, e, por conseguinte, maior eficiência das redes na predição da produtividade. Pelo coeficiente de determinação, verificaram-se os melhores ajustes para ‘Prata-Anã’ (R2 = 0,99 para todas as composições de rede), enquanto, para ‘BRS Platina’, a adequação dos dados possibilitou R² com valores entre 0,97 e 1,00, aproximadamente. Previsões de produtividade para ‘Prata-Anã’ e ‘BRS Platina’ foram obtidas com alta eficiência por meio de redes neurais artificiais.

ABSTRACT Prediction models may contribute to data analysis and decision-making in the management of a crop. This study aimed to evaluate the feasibility of predicting the yield of ‘Prata-Anã’ and ‘BRS Platina’ banana plants by means of artificial neural networks, as well as to determine the most important morphological descriptors for this purpose. The following characteristics were measured: plant height; perimeter of the pseudostem at the ground level, at 30 cm and 100 cm; number of live leaves at harvest; stalk mass, length and diameter; number of hands and fruits; bunches and hands masses; hands average mass; and ratio between the stalk and bunch masses. The data were submitted to artificial neural networks analysis using the R software. The best adjustments were obtained with two and three neurons at the intermediate layer, respectively for ‘Prata-Anã’ and ‘BRS Platina’. These models presented the lowest mean square errors, which correspond to the higher proximity between the predicted and the real data, and, therefore, a higher efficiency of the networks in the yield prediction. By the coefficient of determination, the best adjustments were found for ‘Prata-Anã’ (R² = 0.99 for all the network compositions), while, for ‘BRS Platina’, the data adjustment enabled an R² with values between 0.97 and 1.00, approximately. Yield predictions for ‘Prata-Anã’ and ‘BRS Platina’ were obtained with high efficiency by using artificial neural networks.

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.

Resumo Ramas de batata-doce apresentam características satisfatórias para alimentação animal, porém não têm sido exploradas na forma de feno. Objetivou-se avaliar o uso de ramas de batata-doce para a produção de feno e a divergência genética em clones de batata-doce. Foram avaliados dez clones de batata-doce, conduzidos a campo em blocos ao acaso e cinco repetições. Foram determinados o teor de matéria seca, as produtividades de massa verde e massa seca (PMS), a relação folha e haste das ramas e a produção total e comercial de raízes (PRC). Obtidos os fenos, avaliaram-se as características MS, PB, FDN, FDA, lignina, amido, açúcares solúveis, macro e micronutrientes. Estimou-se a divergência genética entre os clones de batata-doce. O clone UFVJM-54 aliou alta PRC com maior PMS. Os fenos apresentaram teores de PB variando de 11,99 a 15,09%, FDN 47,22 a 55,55%, FDA 22,92 a 28%, e 6,87 a 13,72% de LIG. De forma geral, os teores de minerais nos fenos foram satisfatórios. Os clones foram separados em cinco grupos diferentes. As ramas de batata-doce podem ser utilizadas para a produção de feno. Os clones UFVJM-37, UFVJM-46 e UFVJM-54 são recomendados para cruzamentos com os demais genótipos.

Abstract Sweet potato branches have satisfactory characteristics for animal feed, but have not been exploited in the form of hay. The objective of this work was to evaluate the use of the sweet potato branches for the hay production and genetic divergence in sweet potato clones. Were evaluated ten sweet potato clones, conducted on the field in randomized blocks and 5 repetitions. Dry matter content, green mass and dry mass yield (DMY), leaf and stem ratio of branches and total and commercial root production (CRP) were determined. Gotten the hays, were evaluated the characteristics: DM, CP, NDF, ADF, lignin, starch, soluble sugars, macro and micronutrients. The genetic divergence among the sweet potato clones was estimated. The UFVJM-54 clone allied high CRP with bigger DMY. The hay presented content of CP ranging from 11.99% to 15.09%, NFD 47.22 to 55.55%, ADF 22.92 to 28%, and 6.87 to 13.72% of LIG. In a general way, the contents of minerals in hays were satisfactory. The clones were separated into 5 different groups. The sweet potato branches can be used for the hay production. The UFVJM-37, UFVJM-46 and UFVJM-54 clones are recommended for crossing with the other genotypes.