8 resultados para Identificação de danos

em Repositório da Produção Científica e Intelectual da Unicamp


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Raman imaging spectroscopy is a highly useful analytical tool that provides spatial and spectral information on a sample. However, CCD detectors used in dispersive instruments present the drawback of being sensitive to cosmic rays, giving rise to spikes in Raman spectra. Spikes influence variance structures and must be removed prior to the use of multivariate techniques. A new algorithm for correction of spikes in Raman imaging was developed using an approach based on comparison of nearest neighbor pixels. The algorithm showed characteristics including simplicity, rapidity, selectivity and high quality in spike removal from hyperspectral images.

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This study had as objective the evaluation of mechanical damages occurred in banana Nanicão during the improvement process, packing and distribution, identifying the probable critical points. The mechanical damages caused by transport, first cleaning; cleanness and sorting; preservation in the packing, transport, and mature were evaluated. The studied packing had been: torito wooden packing (18 kg), wood type ½ box, (13 kg) and cardboard (18 kg). The stage of preservation and transport of the fruits to the distribution center duplicated the light defects and quintupled the serious defects, causing rottenness after the acclimatization. The cardboard packing did not support the piling up and presented deformations, that resulted in the kneading the fruits of the inferior packing, causing a significant increase of the serious defects. The fruits conditioned in the involved packing of plastic bubble had presented an inferior number of serious damages when compared with the others packing, without the plastic.

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The efficiency of swine production performance depends on the herd administration, such as good nutrition, sanitary control, facilities and appropriate environmental conditions. The concept of this production model is directly related with the reduction of selective losses and the process control. Each production segment is controlled to reach the optimization in the system totality, it is necessary to apply animals handling concepts, environmental control implementation, diseases control, nutrition control, information concerning in guaranteeing the animal welfare and individual identification. The present work presents as objective the development of the mathematical model to evaluate interactions among the internal atmosphere of the installation and the thermal animals preference, in the expectation of detecting a relationship among the frequency access to the drinking fountain and the atmosphere conditions - temperature, black globe temperature and relative humidity, using as tool the electronic identification. The results obtained by the mathematical model, allowed to conclude accurately the evaluation of the swine thermal preference correlating with the climatic variables in the pregnancy stage.

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Animal welfare has been an important research topic in animal production mainly in its ways of assessment. Vocalization is found to be an interesting tool for evaluating welfare as it provides data in a non-invasive way as well as it allows easy automation of process. The present research had as objective the implementation of an algorithm based on artificial neural network that had the potential of identifying vocalization related to welfare pattern indicatives. The research was done in two parts, the first was the development of the algorithm, and the second its validation with data from the field. Previous records allowed the development of the algorithm from behaviors observed in sows housed in farrowing cages. Matlab® software was used for implementing the network. It was selected a retropropagation gradient algorithm for training the network with the following stop criteria: maximum of 5,000 interactions or error quadratic addition smaller than 0.1. Validation was done with sows and piglets housed in commercial farm. Among the usual behaviors the ones that deserved enhancement were: the feed dispute at farrowing and the eventual risk of involuntary aggression between the piglets or between those and the sow. The algorithm was able to identify through the noise intensity the inherent risk situation of piglets welfare reduction.

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Tomatoes are one of the most important vegetable crops grown in Brazil and are among the crops that have one of the highest post-harvest losses indexes in the country. The present work aimed at evaluating impact damage observed in packing lines of fresh tomatoes as well as to determine, under laboratory conditions, quality alterations of tomato fruits submitted to impact damage in different surface types. Critical points evaluation was accomplished using an instrumented sphere. Critical transference points found showed variations in acceleration levels from 30 to 129 G (m s-2). Tests carried out under laboratory conditions showed that padded surfaces reduced up to 31% impact damage. Incidence of severe internal physical damage was evaluated by a subjective scale and increased by 79% on hard surfaces for the highest fall drop. On the other hand, it was observed an effective reduction in physical damage on fruits when padded surfaces were used. When a 10-cm drop was performed, the maximum reduction measured was 10% for hard surfaces and 5% for previously padded surfaces. For quality parameters, it was observed for high drops on hard surfaces, highest values for weight loss, total acidity, lower values for vitamin C and Soluble Solids.

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Universidade Estadual de Campinas. Faculdade de Educação Física