989 resultados para Precision Agriculture


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The objective of this study was to analyze different intensities of soil sampling for accuracy in geostatistical analysis and interpolation maps for precision agriculture in the sugarcane area. Soil samples were collected at two regular grids at a depth of 0.00 to 0.20m for granulometric analysis (area 1) and soil fertility (area 2). We compared soil sampling intensities: 208, 105, 58 and 24 points in Area 1 and 206, 102 and 53 points in Area 2. The data were submitted to descriptive analysis and geostatistics. The variograms constructed with 105 points didn't differ from variograms with 208 points, which doesn't occur for 58 and 24 points. The increase of sampling interval and reducing the number of points promote greater error in kriging. Samples with more than 100 points per area did not result in significant improvements in the error of kriging, or differed in the amount of fertilizer applied to the field.

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Animal behavioral parameters can be used to assess welfare status in commercial broiler breeders. Behavioral parameters can be monitored with a variety of sensing devices, for instance, the use of video cameras allows comprehensive assessment of animal behavioral expressions. Nevertheless, the development of efficient methods and algorithms to continuously identify and differentiate animal behavior patterns is needed. The objective this study was to provide a methodology to identify hen white broiler breeder behavior using combined techniques of image processing and computer vision. These techniques were applied to differentiate body shapes from a sequence of frames as the birds expressed their behaviors. The method was comprised of four stages: (1) identification of body positions and their relationship with typical behaviors. For this stage, the number of frames required to identify each behavior was determined; (2) collection of image samples, with the isolation of the birds that expressed a behavior of interest; (3) image processing and analysis using a filter developed to separate white birds from the dark background; and finally (4) construction and validation of a behavioral classification tree, using the software tool Weka (model 148). The constructed tree was structured in 8 levels and 27 leaves, and it was validated using two modes: the set training mode with an overall rate of success of 96.7%, and the cross validation mode with an overall rate of success of 70.3%. The results presented here confirmed the feasibility of the method developed to identify white broiler breeder behavior for a particular group of study. Nevertheless, more improvements in the method can be made in order to increase the validation overall rate of success. (C) 2013 Elsevier B.V. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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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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The goal of this paper was to select among the attributes surveyed soil, one with better representation to explain the variability of the technological components of sugar cane. The study was conducted at ETH Eldorado Plant in Rio Brilhante, MS, in the agricultural year 2011/2012, in a Oxisol, which was installed a geostatistical grid for data collection of soil and plant, with 80 sampling points, a 80 ha area. From the standpoint of linear and spatial TCH has been explained as a function of volumetric moisture. The volumetric moisture collected at a depth of 0.00 to 0.20 m, which had values between 0,24 to 0,270 m(3) m(-3), resulted in sites with the highest productivity of sugar cane per hectare from 64 to 70 t ha(-1). To aid future studies aimed at precision agriculture, which will use the same attributes as those of the future works, the values of ranges of spatial dependence to be used should be between 81 and 487 meters.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The number of electronic devices connected to agricultural machinery is increasing to support new agricultural practices tasks related to the Precision Agriculture such as spatial variability mapping and Variable Rate Technology (VRT). The Distributed Control System (DCS) is a suitable solution for decentralization of the data acquisition system and the Controller Area Network (CAN) is the major trend among the embedded communications protocols for agricultural machinery and vehicles. The application of soil correctives is a typical problem in Brazil. The efficiency of this correction process is highly dependent of the inputs way at soil and the occurrence of errors affects directly the agricultural yield. To handle this problem, this paper presents the development of a CAN-based distributed control system for a VRT system of soil corrective in agricultural machinery. The VRT system is composed by a tractor-implement that applies a desired rate of inputs according to the georeferenced prescription map of the farm field to support PA (Precision Agriculture). The performance evaluation of the CAN-based VRT system was done by experimental tests and analyzing the CAN messages transmitted in the operation of the entire system. The results of the control error according to the necessity of agricultural application allow conclude that the developed VRT system is suitable for the agricultural productions reaching an acceptable response time and application error. The CAN-Based DCS solution applied in the VRT system reduced the complexity of the control system, easing the installation and maintenance. The use of VRT system allowed applying only the required inputs, increasing the efficiency operation and minimizing the environmental impact.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Agricultural mechanization improved the efficiency of field operations by providing an increase in crop production. The intensified mechanization, however, has led to higher energy use mainly in the area of fuel consumption. The objective of this study was to compare the fuel consumption of tractors using two different tire pressures for two different types of soil during tillage with irrigated cotton in semi-arid regions. These tests were performed at the Maricopa Agricultural Center (MAC), an experimental farm belonging to The University of Arizona with a Case 4x2 TDA 88kW equipped with an autopilot system. The results showed lower fuel consumption using a tire pressure of 124 kPa on sandy clay loan soil.

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Currently, the efficiency in field operations and the increased productivity of crops is only possible with the use of agricultural machinery and equipment. This intensification of mechanized activities in agriculture, however, led to higher energy costs on farms mainly in the fuel consumption of agricultural tractors. The objective was to compare the fuel consumption of a tractor on tillage operations for irrigated cotton in semi-arid region varying two tire inflation pressures. The tests were conducted in Maricopa Agricultural Center (MAC), an experimental farm belonging to The University of Arizona using a 4x2 TDA Case tractor equipped with a 88kw autopilot system. The results showed lower values in the hourly fuel consumption by using the minimum tire inflation pressure of 124 kPa for all tillage equipment used.