Sewage sludge is an organic matter-rich material with abundant fractions of nitrogen and other macro and micronutrients, essential for plant growth and development such as Acacia mangium Willd. (Fabales: Fabaceae) used in recovering actions of degraded areas. The objective of this study was to evaluate over 24 months the abundance and diversity of chewing and pollinator insects and arthropod predators on A. mangium plants and the mass production and soil coverage by this plant, fertilized with dehydrated sewage sludge, in a degraded area. The experimental design was in randomized blocks with two treatments (with and without dehydrated sewage sludge) and 24 replications. The number of leaves per branch and branches per plant, defoliation percentage by chewing insects, soil cover and abundance of chewing and pollinator insects and arthropod predators were higher on A. mangium plants fertilized with dehydrated sewage sludge. Nasutitermes sp. (Blattodea: Termitidae) and Trigona spinipes F. (Hymenoptera: Apidae) were the most observed insects on trunks and leaves, respectively, of A. mangium plants fertilized with dehydrated sewage sludge. The A. mangium fertilization increases the populations of different insect and spider groups on this plant.

Galling insects are a highly sophisticated herbivore group on Caryocar brasiliense, a tree that represents the main income source for many communities. The effect of architectural diversity of C. brasiliense trees on galling insect community diversity and abundance was studied. The abundance of adult insects and galled leaves were seven and 1.6 times higher in trees with a greater height/width of canopy (RHW) ratio, respectively. Gall parasitoid richness was 1.8 times greater on trees with higher RHW. Zelus armillatus (Lepeletier & Serville) (Hemiptera: Reduviidae) and ant numbers were 5.8 and 2.7 higher on trees with the largest and smallest RHW, respectively. More complex plant architectures favored species diversity for galling insects and their natural enemies. The competition among four galling insect species for space and feeding and the evidence of “prudence strategy” were, for the first time, observed for galling insects in the Brazilian Cerrado biome.

Sweet potato is one of the most cultivated tuberous roots in tropical and subtropical regions permitting several ways of use. Despite its potential use, sweet potato has been little studied. We evaluated the performance of sweet potato roots, forage productivity and its silage at different harvesting times and cultivation environments and we identified the most superior clones under different soil and climatic conditions. Six sweet potato clones (BD-38, BD-45, BD-25, BD-31TO, BD-15 and BD-08) belonging to germplasm bank of UFVJM in addition to two standard cultivars Brazlândia Rosada and Princesa were grown in two cultivation sites (JK campus and Forquilha farm). The trial was conducted in split plots in randomized block design with three harvest times (120, 150 and 180 days after planting). The mean root weight obtained from Forquilha farm was on average 30.2% higher than those obtained from JK campus. Regardless the site, harvesting at 150 days after planting was the optimal time for maximizing root production. The irregularity of root shape increased when the harvesting date was postpone, probably due to greater exposure to environmental factors. Crude protein, fibers, ash and starch, were not affected by local x cultivar interaction except for starch content that depended on the clone and site interaction.

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.

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A batata-doce (Ipomoea batatas) é uma hortaliça que se destaca pela facilidade de cultivo, rusticidade, ampla adaptação a diferentes tipos de solo e clima, alta tolerância à seca e baixo custo de produção. Pode ser empregada na alimentação humana e animal e como matéria-prima nas indústrias de alimentos, tecidos, papel, cosméticos, preparação de adesivos e álcool carburante (Cardoso et al., 2005).A maior parte da produção mundial de batata-doce (98,6%) concentra-se em países em desenvolvimento onde, em virtude do nível de tecnologia empregado, a produtividade média está bem abaixo do potencial para a cultura, que pode ser superior a 40 t ha -1 e, onde níveis de 25 a 30 t ha -1 podem ser facilmente obtidos em 4 a 5 meses de cultivo (Miranda et al., 1987; Andrade Júnior et al., 2009), com tecnologia minimamente apropriada.No Brasil, a batata-doce é a quarta hortaliça mais cultivada, sendo produzidas, em 2010, 495,2 mil toneladas em 41.999 ha, com produtividade média de 11,8 t ha -1 de raízes (IBGE, 2012). O Rio Grande do Sul é o estado com a maior área plantada (12.600 ha), com uma produção de 154.071 toneladas e rendimento médio de 12,5 t ha -1 . No estado de Minas Gerais foram produzidas em 2010, 37.632 t de batata-doce, com área cultivada de 2.330 ha e rendimento mé-dio de 16,2 t ha -1 (IBGE, 2012). Baixas produtividades podem ser ocasionadas pelo desconhecimento de práticas culturais adequadas, e atribuídas à ANDRADE JÚNIOR VC; VIANA DJS; PINTO NAVD; RIBEIRO KG; PEREIRA RC; NEIVA IP; AZEVEDO AM; ANDRADE PCR. 2012. Características produtivas e qualitativas de ramas e raízes de batata-doce. Horticultura Brasileira 30: 584-589.Características produtivas e qualitativas de ramas e raízes de batata-doce RESUMOA batata-doce é uma hortaliça que se destaca pela versatilidade no uso, podendo ser empregada tanto na alimentação humana como animal. Seu cultivo é relativamente fácil e barato, o que, juntamente com sua adaptabilidade a variadas condições edafo-climáticas, viabiliza sua produção pelos agricultores familiares. Objetivou-se avaliar a produção de massa verde e massa seca da parte aérea para utilização na alimentação animal e a produtividade e a qualidade das raízes tuberosas de clones de batata-doce para utilização na alimentação humana. O delineamento experimental utilizado foi em blocos casualizados, com doze clones e quatro repetições. Foram avaliados clones de batata-doce pertencentes ao banco de germoplasma da UFVJM juntamente com as cultivares comerciais Brazlândia Roxa e Brazlândia Rosada, colhidos aos seis meses após o plantio. Foram avaliadas a produção de massa verde e massa seca da parte aérea e a produtividade e qualidade das raízes tuberosas. O clone BD-45 destacou-se na produção de massa verde, produção de massa seca e nas produtividades total e comercial de raízes com valores de 19,7; 3,3; 32,9 e 29,5 t ha -1 , respectivamente. A maioria dos genótipos avaliados apresentou raízes com formato próximo ao ideal para comercialização e boa resistência a insetos de solo com valores de notas próximos a ...

Genetic parameters, dissimilarity and performance of pumpkin accessionsPumpkin is very important in human and animal food, especially concerning family farms. The germplasm bank of vegetables of Universidade Federal de Viçosa (Federal University of Viçosa, UFV-BGH), Brazil, has several pumpkin accessions with wide genetic variability. All this genetic variability is of great importance for plant breeding. However, little is known about the true potential of BGH-UFV, because there are few scientific papers published with information on these accessions. The objective was to obtain information on genetic parameters, dissimilarity and performance of BGH-UFV pumpkin accessions. We evaluated 11 morphological descriptors of 55 accessions and three cultivars. The genetic parameters, expected gain with selection, phenotypic, genotypic and environmental correlations were estimated. For the dissimilarity study, the Tocher test was carried out and graphic dispersion of the canonical variables was evaluated. There was genetic variability among accessions, with a predominance of genetic effects over the environment. Higher gain selection for mass per fruit, plant appearance and location of the first male flower node are expected. The commercial cultivars Butternut and Tetsukabuto have excelled due to the lower mass per fruit and precocity of flowering, but they had the worst results in terms of phytosanitary aspect. There are negative correlation estimates between the phytosanitary aspect and growth habit, length and growth rate of the main stem, indicating that compact plants may have greater phytossanitary problems. Crossing accession BGH-7003 or cultivar Butternut with accessions BGH-1946 or BGH-7765 can generate progenies with potential for breeding.

Estimating cactus pear yield is important for the planning of small and medium rural producers, especially in environments with adverse climatic conditions, such as the Brazilian semi-arid region. The objective of this study was to evaluate the potential of artificial neural networks (ANN) for predicting yield of ‘Gigante’ cactus pear, and determine the most important morphological characters for this prediction. The experiment was conducted in the Instituto Federal Baiano, Guanambi campus, Bahia, Brazil, in 2009 to 2011. The area used is located at 14° 13’ 30” S and 42° 46’ 53” W, and its altitude is 525 m. Six vegetative agronomic characters were evaluated in 500 plants in the third production cycle. The data were subjected to ANN analysis using the R software. Ten network architectures were trained 100 times to select the one with the lowest mean square error for the validation data. The networks with five neurons in the middle layer presented the best results. Neural networks with coefficient of determination (R2) of 0.87 were adjusted for sample validation, assuring the generalization potential of the model. The morphological characters with the highest relative contribution to yield estimate were total cladode area, plant height, cladode thickness and cladode length, but all characters were important for predicting the cactus pear yield. Therefore, predicting the production of cactus pear with high precision using ANN and morphological characters is possible.