Avaliação de tipos de ventilação em maternidade de suínos

Livestock facilities, where animals carry their productive cycle, must have as main characteristic, the control of influence over climatic factors on animals. The environment variations can be controlled through the use of different ventilation systems. The objective of this research was to evaluate the influence of different environment conditioning systems on swine nursery. Three treatments have been tested: natural ventilation, cooled ventilation and forced ventilation. The climatic parameters evaluated were: air temperature, relative humidity and black globe temperature. The physiological parameters analyzed were: respiratory frequency and back fat thickness. Number of born alive piglets, average weight at weaning and number of weaned piglets were also evaluated parameters. The use of cooled ventilation systems were able to decreased animal's air temperature and respiratory frequency, and the black globe temperature and humidity index (WBGT) and the radiating thermal load (RTL).

Uso de redes neurais artificiais na identificação de vocalização de suínos

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.