Abstract Adenium obesum belongs to the Apocynaceae family and is characterized as a succulent shrub with a multitude of botanical and morphological features of ornamental interest. The aim of this study was to evaluate the genetic dissimilarity of 28 accessions of A. obesum using morphological descriptors and multivariate techniques with the aim of pre-selecting the genotypes with the greatest ornamental potential. The distribution of the number of flowers throughout the year showed two flowering peaks in January and September. Twenty-one petal pigmentation patterns were identified, and 50% of the accessions had double-petal arrangement. The Gower’s algorithm and the UPGMA-generated dissimilarity matrix indicated the formation of three groups. While Tocher’s clustering method separated the accessions into eight groups showing greater ability to distinguish the evaluated genotypes. In conclusion, the multivariate analyses applied were effective in accessing the genetic diversity among the 28 accessions evaluated. The accessions ICA001, ICA005, ICA006, ICA018, ICA019, and ICA027 were preselected to compose the germplasm collection due to their high ornamental potential.

Resumo Adenium obesum, conhecida popularmente como rosa-do-deserto, pertence à família Apocynaceae e caracteriza-se por ser um arbusto suculento, com uma infinidade de aspectos botânicos e morfológicos de interesse ornamental. Objetivou-se no presente estudo avaliar a dissimilaridade genética de 28 acessos de A. obesum por meio de descritores morfológicos e técnicas multivariadas com objetivo de pré-selecionar os genótipos com maior potencial ornamental. A distribuição do número de flores durante os meses do ano demonstrou dois picos de florescimento em janeiro e em setembro. Vinte e um padrões de pigmentação petalar foram identificados e 50% dos acessos apresentaram 10 pétalas por flor (arranjo petalar duplo). Considerando os dados mistos, o algoritmo de Gower juntamente com a matriz de dissimilaridade gerada pelo método UPGMA indicou a formação de três grupos. O agrupamento de Tocher separou os acessos em oito grupos. Conclui-se as análises multivariadas aplicadas foram eficazes em acessar a diversidade genética entre os 28 acessos avaliados. Os acessos ICA001, ICA005, ICA006, ICA018, ICA019 e ICA027 foram pré-selecionados para comporem a coleção de germoplasma por apresentarem alto potencial ornamental.

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.

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 As ramas de batata-doce apresentam potencial de utilização na alimentação animal, na forma fresca e de silagem, sendo que a utilização de aditivos pode contribuir para a melhoria da qualidade da silagem das ramas. Objetivou-se com este estudo avaliar a qualidade da silagem de ramas de batata-doce com diferentes aditivos. Os tratamentos utilizados para a confecção das silagens foram: ramas puras; ramas + 10% de MDPS (milho desintegrado com palha e sabugo); ramas + 10% de bagaço de cana de alambique; ramas + 10% de polpa cítrica; ramas + 10% de casca de café. Foram determinadas amatéria seca, proteína bruta, fibra de detergente neutro (FDN), fibra de detergente ácido (FDA), celulose, hemicelulose, lignina, cinzas, amido, açucares solúvel, pH, população de Bactérias do ácido láctico, perdas por gases e efluentes. As silagens de ramas + MDPS, ramas + polpa cítrica e ramas + casca de café apresentaram os maiores teores de matéria seca. Na silagem de ramas + polpa cítrica foi registrada alto teor de FDN. Já na silagem de ramas + MDPS obteve-se o menor teor de FDA. O teor de lignina foi baixo nas silagens das ramas + MDPS, ramas puras e ramas + polpa cítrica. Os teores de amido, PB e populações de BAL foram adequados para todas as silagens. A silagem contendo ramas + MDPS apresentou os melhores resultados para as características avaliadas, de forma que o aditivo utilizado nesta silagem é o mais recomendado para as condições experimentadas.

ABSTRACT Sweet potato branches have potential use in animal feeding, even fresh or ensiled, and some additives may enhance their quality. This study aimed at assessing silage quality of sweet potato branches using different additives. We ensiled sweet potato branches without additive (control) and with the addition of 10% disintegrated corn with straw and corncob (DCSC), 10% sugarcane bagasse from alembic, 10% citrus pulp, and 10% coffee husk. Three samples of each plot were obtained after drying for measurements of dry matter, crude protein, neutral detergent fiber (NDF), acid detergent fiber (ADF), cellulose, hemicellulose, lignin, mineral matter, starch, soluble sugars, pH, lactic acid bacteria population, gas, and effluent losses. Silage with DCSC, citrus pulp, and coffee rusk reached the highest dry matter contents. Moreover, citrus pulp silage had a high content of NDF. In contrast, DCSC silage showed the lowest content of ADF. Lignin was low in silage with DCSC, citrus pulp, and control (without additive). Suitable amounts of starch, crude protein, and lactic acid bacteria population were found in all treatments. Silage with DCSC achieved the best results for the assessed variables. Therefore, DCSC is the most suitable additive to improve silage quality of sweet potato branches.

ABSTRACT Kale plants are usually sold “in natura” in street markets and malls. Kale leaves can have their appearance compromised by dehydration and discoloration due to increased post-harvest time exposure. We aimed to analyze the Global Stability Index (GSI) in kale accessions by means of repeated measurement analysis and curve grouping as a complementary form of superior sample identification with regard to post-harvest preservation. Thirty kale accessions were evaluated using a randomized block design with four blocks and five plants per plot. Two commercial leaves per plant were collected, and kept on workbenches in the shade at a temperature of 18 ± 1 °C. Subsequently, the degrees of discoloration and dehydration, total chlorophyll content, and accumulated fresh mass loss were evaluated over a 15-day period. From these data, the GSI was calculated for each day of evaluation. In addition, using mixed models, thirteen co-variance structures were tested. For graphical analysis, thirteen linear and non-linear models were assessed followed by curve grouping using multivariate analysis. The GSI was efficient for differentiating accessions, which became an important tool in post-harvest studies. GSI values were not equally correlated, therefore the use of mixed models became an important approach. The unstructured matrix was the best fit to model the dependence of error. The Melow I model was the best fit for studying the GSI. The accessions UFVJM-10, UFLA-1, COM-1, UFVJM-32, COM-3, UFVJM-8, UFVJM-36 and UFVJM-24, belonging to 3 and 5 clusters, are recommended for crop cultivation and as parental material in breeding programs.

The efficiency of artificial neural networks (ANN) to model complex problems may enable the prediction of characteristics that are hard to measure, providing better results than the traditional indirect selection. Thus, this study aimed to investigate the potential of using artificial neural networks (ANN) for indirect selection against early flowering in lettuce, identify the influence of genotype by environment interaction in this strategy and compare your results with the traditional indirect selection. The number of days to anthesis were used as the desired output and the information of six characteristics (fresh weight of shoots, mass of marketable fresh matter of shoots, commercial dry matter of shoots, average diameter of the head, head circumference and leaf number) as input file for the training of the ANN-MLP (Perceptron Multi-Layer). The use of ANN has great potential adjustment for indirect selection for genetic improvement of lettuce against early flowering. The selection based on the predicted values by network provided estimates of gain selection largest that traditional indirect selection. The ANN trained with data from an experiment have low power extrapolation to another experiment, due to effect of interaction genotype by environment. The ANNs trained simultaneously with data from different experiments presented greater predictive power and extrapolation.

O objetivo deste trabalho foi avaliar os parâmetros genéticos das características agronômicas e de tolerância ao florescimento precoce de onze cultivares de alface, bem como verificar a existência de associação entre as características. O experimento foi realizado em ambiente protegido, em delineamento de blocos ao acaso, com quatro repetições e doze plantas por parcela. Quarenta e cinco dias após o transplantio das mudas, foram mensuradas as seguintes características: massa de matéria fresca total e "comercial" da parte aérea, massa de matéria seca "comercial" da parte aérea, massa de matéria fresca e seca da raiz, diâmetro e circunferência da cabeça, altura de planta, número de folhas por planta e número de dias até a antese. Há variabilidade genética entre as cultivares, em todas as variáveis, exceto quanto à circunferência de planta e matéria fresca da raiz. As cultivares Regina 500, Lívia e Atração foram superiores quanto ao número de dias para o florescimento e também para as demais características avaliadas. A seleção contra o florescimento precoce ocasionou ganho em todas as características; porém, não interferiu na matéria seca da raiz. A matéria fresca da parte aérea e o diâmetro de cabeça são indicadas para a seleção indireta contra o florescimento precoce.

The objective of this study was to evaluate the genetic parameters of agronomic traits and of tolerance to early flowering of eleven cultivars of lettuce, as well as to verify the existence of an association between the characteristics. The experiment was carried out in a protected environment, in a randomized complete block design, with four replicates, and twelve plants per plot. Forty-five days after seedling transplanting, the following traits were measured: total shoot fresh mass, marketable shoot fresh mass, marketable dry shoot weight, fresh and dry weight of roots, diameter and circumference of head, plant height, number of leaves per plant, and number of days until anthesis. There was genetic variability between cultivars for all variables, except for circumference of plant and fresh weight of root. The cultivars Regina 500, Lívia and Atração were superior for number of days to flowering and also for the other characteristics. The selection against early flowering caused gain of all the characteristics, but did not affect root dry matter. Fresh matter of shoots and head diameter are indicated for indirect selection against early flowering.

O objetivo deste trabalho foi avaliar o desempenho agronômico de acessos de couve e estimar os parâmetros genéticos e a correlação entre características de interesse para o melhoramento. O experimento foi realizado em delineamento de blocos ao acaso, com 30 genótipos de couve, entre os quais, três cultivares comerciais, de diferentes empresas. Foram utilizadas quatro repetições, com cinco indivíduos por parcela. Verificou-se variabilidade genética entre os genótipos, com predominância dos efeitos genéticos sobre os ambientais, o que indica a possibilidade de se obterem ganhos genéticos representativos com o melhoramento. As características importantes para o melhoramento da espécie foram: comprimento e largura de folha, diâmetro de pecíolo, área foliar, altura de planta, número de brotações e massa de folhas secas. Os genótipos comerciais apresentaram menor área foliar, massa de matéria seca de folhas, altura de planta, comprimento e largura de folha, comprimento de pecíolo, e número de brotações e de folhas comerciais.

The objective of this work was to evaluate the agronomic performance of kale genotypes and to estimate the genetic parameters and the correlation between traits of interest for breeding. The experiment was carried out in a randomized block design, with 30 kale genotypes, with three commercial cultivars, from three different companies. It was used four replicates, with five individuals per plot. Variability was significant among genotypes, with predominance of genetic effects over environmental ones, indicating the possibility of obtaining expressive genetic gains in breeding. The most important traits for breeding purposes were: leaf length and width, stem diameter, leaf area, plant height, number of shoots, and leaf dry weight. Commercial genotypes showed smaller leaf area, dry leaf mass, plant height, leaf length and width, petiole length, and number of sprouts and commercial leaves.