Bioimpedância na predição da composição da carcaça de cordeiros e de seus cortes

• Ano de defesa: 2020
• Autor(a) principal: Moro, Anderson Bortoluzzi
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Zootecnia; UFSM; Programa de Pós-Graduação em Zootecnia; Centro de Ciências Rurais
• Palavras-chave em Português: Composição de carne; Densidade resistiva e reativa; Bioimpedância elétrica; Modelos de predição; Ovinos; Bioimpedance electrical; Meat composition; Prediction models; Resistive and reactive density; Sheep; CNPQ::CIENCIAS AGRARIAS::ZOOTECNIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/21111

Bioimpedance analysis (BIA) used to predict lamb carcass composition or their cuts is based on the different levels of opposition to the passage of an ionic current through its different constituents. Thus, the objective of this research was to evaluate the BIA potential to predict the composition of lamb carcasses and their cuts using accessory variables. Thirty-one lambs were slaughtered at predefined weights of 20, 26, 32 or 38 kg of live weight. Measurements of weight, length, resistance and reactance were collected from hot and cold carcasses and from the retail cuts (leg, rib, shoulder, and neck) and the longissimus dorsi muscle of the right half carcasses. From these measurements, other accessory variables of the BIA were calculated. The cuts were deboned to obtain the soft tissue mass (edible portion) of each cut and of the cold carcasses. Representative samples of each cut and of the longissimus dorsi muscle were chemically analyzed to obtain moisture, ash, protein, and fat masses. These compounds were used to determine the lean mass and the crude energy content of the longissimus dorsi muscle, of each cut and of the cold carcasses. The respective resistance, reactance, impedance, phase angle, bioelectric volume, resistive density and reactive density were used as independent variables to predict the composition of the longissimus dorsi muscle, the retail cuts, or the lamb carcasses. Leave-one-out cross validation was performed to assess the precision and accuracy of the predictive models. The prediction models of BIA in hot and cold carcasses resulted in 85.9% to 99.8% of the variation of the soft tissue constituents in lamb carcasses. The predictive models from the segmental BIA explained 53.3% to 99.9% of the variation of their components in the cuts and from 69.5% to 98.2% to predict the edible portion of lamb carcasses. However, the prediction models of BIA at longissimus dorsi muscle to estimate its own composition accounted for 67.5% to 99.1% in the variation of its constituents and for 82.8% to 91.7% in the variation of soft tissue constituents of the lamb carcasses. Resistive or reactive densities explained most of the variation in the prediction models obtained. These variables, together with bioelectric volume, improved the prediction models of the quantitative components either in hot as in cold carcasses. Furthermore, they were essential to estimate the composition of the edible portion of retail cuts from lamb carcasses and the compounds of the longissimus dorsi muscle. However, greater accuracy is expected with the use of BIA in cold carcasses compared to hot carcasses. Additionally, shoulder was the best predictive cut of the edible components of lamb carcasses by segmental BIA. Therefore, BIA is a simple technique, non-destructive, and it produces accurate results in predicting lamb carcass components and it might be incorporated both into research centers as in the lamb meat industry.