Organic materials subjected to a process of anaerobic digestion in a digester produce biofertilizer that can be used in agriculture as nutrient source. The objective of this study was to evaluate the effect of pig slurry biofertilizer on soil chemical properties and on corn yield and nutrient concentrations in leaves and kernels. The experiment was conducted in the field from November 2012 to April 2013, and was arranged in a randomized block design with seven treatments and four replicates. The treatments consisted of doses of pig slurry biofertilizer (0; 40; 80; 120; 160; 200 and 240 m3 ha-1), applied to the soil surface in a single application, at stage V2 of corn plants. Thirty-three days after biofertilization, soil samples were collected in each plot. Corn was harvested 129 days after sowing. Doses up to 240 m3 ha-1 of pig slurry biofertilizer applied to soil with good fertility did not influence soil chemical properties and corn yield. The use of pig slurry biofertilizer had no detectable effect on nutrient concentrations in corn leaves and kernels.

este trabalho, a criação de um modelo matemático, prático e eficiente para a previsão antecipada de safras com base em alguns atributos fenológicos da planta: altura, número de frutos no 4° e 5° internódios dos ramos plagiotrópicos, comprimento em metros das linhas de café e diâmetro medido na região inferior das plantas. O experimento foi montado nos cafezais do IFSULDEMINAS -Campus Machado, em que quatro cultivares de diferentes portes tiveram sua produtividade analisada durante a safra 2010/2011: Catucaí, Mundo Novo, Rubi e Topázio, cada uma se constituiu em unidade experimental na qual, por sua vez, foram amostradas 10 plantas aleatoriamente sendo 6 ramos amostrados em cada planta (três do lado do sol nascente e três do lado do sol poente, sendo dois no terço superior, outros dois na região intermediária e os dois últimos na região inferior de cada planta). Os dados foram colhidos no final do mês de fevereiro de 2011. O modelo que considera a proporção do volume de copa do cafeeiro tentando aproximar-se mais da arquitetura real da planta foi o mais significativo apresentando coeficiente de determinação de 0,83. Mathematical model for predicting coffee yield A B S T R A C TThe objective of this work was to create a practical and effective mathematical model for the early prediction of crops based on some phenological attributes of the plant: height, number of fruits in the 4 th and 5 th internodes of the plagiotropic branches, length in meters of the planted coffee row and diameter measured at the lower region of the coffee plants. The experiment was carried out in the coffee plantations of IFSULDEMINAS -campus Machado -where the productivity of four cultivars of different sizes were analysed during the 2010-2011 season: Catucaí, Mundo Novo, Ruby and Topaz. Each of these was an experimental unit, from which 10 plants were randomly chosen. Of these, 6 branches of each plant were sampled (three on the side of the rising sun, and three on the side of the sunset; two in the upper third, and two in the middle region, and two in the lower region of each plant). Data were collected at the end of February 2011. The model which considers the proportion of the coffee plant canopy in order to get closer to the real architecture of the plant was the most significant, with a coefficient of determination of 0.83. 2013 ISSN 1807 -1929 v.18, n.4, p.353-361, 2014 Introdução A estimativa antecipada de safra nas regiões produtoras de café movimenta o mercado interno e externo. O café é um produto que apresenta demanda inelástica e a questão da informação confiável passa a ter grande relevância. Nas Bolsas de Valores a commodity café movimenta alto volume financeiro todos os dias podendo ser afetada por diferentes fatores, o que provoca sérias instabilidades no setor. Fenômenos como geadas, estresse hídrico, pragas e doenças, nutrição e aspectos econômicos, afetam sensivelmente a produtividade da cultura do café de ano para ano ocasionando bruscas oscilações de seus preços, o que compromete a regularidade do abastecimento...

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Despite the advantages in production, mechanization may expose workers to high noise levels in the work environment, which is considered one of the main causes of workrelated hearing loss. In this sense, this study aimed to analyze the spatial variability of noise generated by a self-propelled coffee harvester in an open area to define safe zones for operators and workers involved in coffee harvesting activities. The noise source used was an Electron Auto TDI self-propelled coffee harvester (model MWM D229-4), with a cabin manufactured in 2012 and a 67-hp 4-cylinder engine, working at 1200-rpm rotation. The noise level was measured by a digital decibel meter at points distributed within a regular 2.5 x 2.5 m sampling mesh (32.5 x 35.0 m area) surrounding the harvester in operation, which was configured according to the regulatory standard. Noise level spatial dependence was analyzed through geostatistics, characterizing structure and magnitude, and mapping spatial variability. Results showed that noise levels were above the limit established by relevant legislation (i.e., 85 dB), both for operators and employees at a distance of about 5.5 m from the generating source.