153 resultados para máquina agrícola


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The chemical and physical degradation of the soils by salinity and sodicity problems constitutes a serious obstacle in productive irrigated areas in arid and semi-add regions. In order to eval mate the effect of gypsum on electrical conductivity, pH, exchangeable sodium percentage, sodium, calcium and magnesium content in saturation extract and exchangeable sodium of two saline-sodic soils: one from irrigated Perimeter Engenheiro Arco Verde in the municipality of Condado and another from irrigated Perimeter of São Gonçalo, in the municipality of Sousa both in the Paraiba State Brazil, an experiment was carried out in green house of the Departamento de Solos e Engenharia Rural, Centro de Ciências Agrárias, Universidade Federal da Paraíba, Areia, Brazil, in a factorial design 2 × 5 referring the two soils and five gypsum levels equivalent to 0; 3.2; 6.3; 9.4 and 12.5 g kg-1 to each soil. The gypsum application exercised positive effects on reduction of salinity and sodicity. The values of electrical conductivity, exchangeable sodium percentage, pH and contents of soluble and exchangeable sodium in relation to data of the soils before application of treatments with gypsum in both the soils were found to decrease.

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The objective of this study was to evaluate the dynamic performance of an agricultural tractor utilizing distilled biodiesel (50% ethylic + 50% methylic) as a function of the proportion of biodiesel and diesel of petroleum (0 and 100%, 5 and 95%, 15 and 85%, 25 and 75%, 50 and 50%, 75 and 25% and 100 and 0%), respectively. This research was done in the area of the Department of Rural Engineering of the Paulista State University (UNESP), Jaboticabal Campus, SP, located in the latitude 21° 14′ 28″ S and longitude 48° 17′12″ W. A tractor 4 x 2 FWA was used, with a 73.6 kW (100 HP) motor and a ballast tractor. The biodiesel used was produced from spent oil from food frying. The experimental design was entirely randomized, with 7 treatments and 5 repetitions, totaling 35 observations. The results showed that the biodiesel and diesel blend significantly influenced the hourly volumetric consumption, hourly mass consumption, fuel consumption per worked area and specific fuel consumption variables. When the tractor operated with 100% of biodiesel (B100) the specific fuel consumption increased 18% on average in relation to diesel (B0).

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Sugarcane is one of the most important crops of the Brazilian agribusiness and this importance justifies the use of techniques that allow the implementation of cultivation systems capable of reducing the variability of soil characteristics and the establishment of efficient agricultural planning. The aim of the present work was the planning and implementation of cultivation systems for sugarcane using geostatistical techniques, in the Pereira Barreto region, SP. An area of 505 ha was mapped using the global positioning system (GPS) and a Digital Elevation Model was elaborated (MDE). Soil samples were collected for 0-0.25 m depth, in each 7 ha, for their chemical attributes and texture characterization. Data were analyzed by descriptive statistics and geostatistics. The determination of the spatial distribution of soil granulometric and chemical attributes allowed the allocation of the studied sugarcane varieties according to soil fertility and clay content. The kriging maps of soil granulometric and chemical attributes brought useful information to the establishment of production environments with different soil and crop managements. The identification of different environments by means of geostatistical techniques allowed the precise planning of the sugarcane cultivation, as well as the adequacy of fertilization practices and the allocation of suitable sugarcane varieties adapted to the conditions imposed by differences in the soil attributes.

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Soil use for the development of activities as agriculture and livestock has been causing great alterations in the environment, mainly when these are practiced intensively, disrespecting the fragility and aptitude of the natural resources. Therefore, it is essential that the planning of the agricultural activities is done, taking into consideration the several environmental criteria involved in the decision-making process. Thus, this study aimed to analyze the agricultural aptitude classes of lands from a watershed through geographical information system (GIS). The Arroio Ajuricaba watershed is located in the Municipality of Marechal Cândido Rondon - PR among the coordinates UTM 787309m E and 793892m E; 7275026m N and 7281310m N, in the Spindle 21, presenting an area of 1681ha. Soil maps, in semi detail scale, was the digital cartographic base used. The results allowed to conclude that 42.41% of the basin presented a good aptitude for farming in handling level of high technology (handling level C), regular aptitude for B, and restricted aptitude for A [class 1(a)bC] and that 12% of the area had regular aptitude for farming in the three handling levels (class 1abc). The watershed lands (14.24%) presented regular aptitude for farming in handling level C, restricted aptitude for B, and inapt for A [class of aptitude 2(b)c]; 15.85% presented good aptitude for planted pasture (class 4P) and 12.21% were considered without aptitude for agricultural use (class 6). We can say that 71.94% of the lands has aptitude for farming, although they present different degrees of limitations that request different treatments for its conservation.

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This paper aims to analyze the geographical dynamics of work from the spread of formal employment in the agricultural sector in Northeast Brazil. In recent years the region has had highlighted a growing movement to produce fruit for export, resulting in the promotion of important sociospatial transformations arising from the formation of a capitalist labor market. Data about the increase in the number of formal jobs show the impact of fruit growing agribusiness in the establishment of a new social and territorial division of labor. However, our study draws attention to the existence of a framework dominated for the vulnerability of the labor market by the persistence of seasonality and precarious working conditions.

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This work combines symbolic machine learning and multiscale fractal techniques to generate models that characterize cellular rejection in myocardial biopsies and that can base a diagnosis support system. The models express the knowledge by the features threshold, fractal dimension, lacunarity, number of clusters, spatial percolation and percolation probability, all obtained with myocardial biopsies processing. Models were evaluated and the most significant was the one generated by the C4.5 algorithm for the features spatial percolation and number of clusters. The result is relevant and contributes to the specialized literature since it determines a standard diagnosis protocol. © 2013 Springer.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Agronomia (Ciência do Solo) - FCAV

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Ciências Sociais - FFC