Andre Luis Finkler da Silveira

Consumo e digestibilidade de feno de baixa qualidade suplementado com nitrogênio não protéico em bovinos

The objective of this work was to evaluate the effect of nonprotein nitrogen supplementation levels on the digestibility of low-quality hay (Cynodon dactylon), which was offered ad libitum to Hereford bulls aging 17 months and weighing 220 kg. The evaluated treatments were: hay + no urea supplement; hay + supplement with 0.28 g urea kg -1 BW 0.75 ; hay + supplement with 0.55 g urea kg -1 BW 0.75 ; hay + supplement with 0.83 g urea kg -1 BW 0.75 and hay + supplement with 1.11 g urea kg -1 BW 0.75 . Hay composition presented 3.86% of crude protein and 84.66% of neutral detergent fiber. Digestibility of organic matter, organic matter of forage, neutral detergent fiber, cellulose and hemicellulose were not affected by nonprotein nitrogen level; total intake of these components showed a quadratic response to nonprotein nitrogen supplementation. Organic matter metabolic fecal excretion was not affected by supplementation, suggesting a simultaneous increase in both passage (intake increase) and digestion rates (stable digestibility). The digestible organic matter intake showed a quadratic response with the increase of urea supplementation levels. The relationship between rumen degradable protein intake and digestible organic matter intake showed a maximization point, when rumen degradable protein intake was equivalent to 8.1% of digestible organic matter intake.

Incorporação de uréia encapsulada em suplementos protéicos fornecidos para novilhos alimentados com feno de baixa qualidade

A trial was accomplished with the objective to verify the effect of the coated or common urea supplementation on the utilization of low quality hay in steers. The treatments were: hay + mineral supplement; hay + protein supplement with common urea; hay + protein supplement with coated urea formula 1; hay + protein supplement with coated urea formula 2. Tifton (Cynodon dactylon L.) hay of low quality (CP: 4.62%, NDF: 83.46%) was used. The measures were: digestibility, intake and digestive kinetics. The relation between degradable intake protein and digestible organic mater intake was highest (P 0.05) when compared the supplemented or not supplemented diets with DIP and in the same way, when compared the non-protein nitrogen sources. The ruminal degradable protein supplementation was not effective for modifying the studied parameters, as well as, the coated urea sources showed to be similar to the common urea.

Surface electromyography measurements for ingestive behaviour identification on goats

Monitoring grazing ruminants ingestive behaviour has applications in measuring animal welfare, animal diseases detection and animal production system modelling. Current monitoring methods are mostly laborious, time expensive or invasive. In this work, it is presented a non-invasive method for chewing activity identification on goats by masseter muscle surface Electromyography (sEMG). Short-term chewing/resting time and chewing count were successfully predicted on male goats comparing to visual observation.

Surface electromyography segmentation and feature extraction for ingestive behavior recognition in ruminants

Abstract This work presents a method to identify the ingestive behavior in ruminants using Surface Electromyography (sEMG) of the masseter muscle. The main hypothesis tested is whether the rumination and food eaten can be recognized from sEMG signal features using machine learning techniques. Also, a novel segmentation technique was explored and applied to automatically subdivide the chewing movement signal. Seven classifiers were evaluated using eight features extracted from the signal and combined into five sets. The three scenarios investigated were: differentiation between rumination and grazing (IR), food identification for four different foods (FC) and both situations combined (FCR). The segmentation window size effect on the accuracy was also investigated. We found an accuracy over 70% for IR and FC and nearby 60% for FCR using a Multilayer Perceptron Neural Network (MLP-NN). Highlighted features were the Cepstrum coefficients (CEPS) and the signal Wavelength (WL). Segments between 600 and 1000 ms proved to be suitable. The segmentation technique and the proposed scheme are reliable for application although there is room for improvement.