898 resultados para artificial eutrophication


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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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Pós-graduação em Medicina Veterinária - FMVZ

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

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The aim of this study was to analyze the effect of flushing on the reproductive performance of Morada Nova (MN) and Santa Inês (SI) ewes submitted to fixed time artificial insemination (TAI). Twenty seven SI and 24 MN supplemented with concentrate (1% of live weight, on average), for 75 days during the breeding season. After 30 days of supplementation, ewes were synchronized with the aid of a hormonal protocol (HP) based on progesterone, eCG and cloprostenol. The estrus observation was conducted at 12, 24, 36 and 48 h after the end of HP with the aid of two ruffians. TAI was done 55 h after the end of HP. From 20 to 45 days after the beginning of the HP ewes were exposed to rams (natural breeding). The pregnancy diagnosis was evaluated 70 days after TAI. We analyzed the weight, body condition score, estrus rate, pregnancy rate and prolificacy testing the effects of race, week of supplementation and body condition score class. The weight and body conditions of ewes varied according to the week of supplementation, with higher values in the first two weeks following TAI. The estrus rate was 88.2% and 43.2% of the ewes showed estrus up to 24 hours of the end of the HP. The pregnancy rate per TAI was 31.3% and the pregnancy rate after natural breeding was 50.0%. It was observed that body condition score classes interfered in pregnancy rates. There was a higher percentage of multiple births by pregnancy by TAI than by natural breeding. It was concluded that the flushing resulted in weight gain and better body conditions ensuring the standardization of the herd for breeding season, which therefore improved reproductive performance. The HP used advanced the onset of estrus and increased prolificacy, but was inefficient in the synchronization of woolless sheep.

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In extensive animal husbandry, natural or artificial ponds allow direct access of cattle to water but result in degradation of water quality and in increased health risks. Under such circumstances eutrophication occurs and consequently algal bloom, among them toxigenic cyanobacteria. The present study aimed to report the occurrence of cyanobacteria in the drinking water of cattle and to describe their physical and chemical parameters, as pH, temperature and dissolved oxygen. Nineteen samples of natural ponds or water troughs formed predominantly as result of rainfall from six farms located in the Southeast and Midwest regions of Brazil were analyzed for the presence of cyanobacteria, and pH, temperature and dissolved oxygen was measured. Microcystis and/or Merismopedia were detected in two ponds; one of them was covered with intense flowering. The values of pH, temperature and dissolved oxygen in 19 collections were pH 7.2-9.7, 31-34ºC and 7.8-30mg/l respectively. Also non-pathogenic algae of several genera were detected besides the occurrence or not of cianogenics. Under these conditions, the common practices of drinking water supply for extensively raised cattle and the possibilities of eutrophication and cyanobacterial growth bring potential risks for animal health.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science