| Literature DB >> 29533812 |
Lida Barba1, Davinia Sánchez-Macías2, Iván Barba3, Nibaldo Rodríguez4.
Abstract
Guinea pig meat consumption is increasing exponentially worldwide. The evaluation of the contribution of carcass components to carcass quality potentially can allow for the estimation of the value added to food animal origin and make research in guinea pigs more practicable. The aim of this study was to propose a methodology for modelling the contribution of different carcass components to the overall carcass quality of guinea pigs by using non-invasive pre- and post mortem carcass measurements. The selection of predictors was developed through correlation analysis and statistical significance; whereas the prediction models were based on Multiple Linear Regression. The prediction results showed higher accuracy in the prediction of carcass component contribution expressed in grams, compared to when expressed as a percentage of carcass quality components. The proposed prediction models can be useful for the guinea pig meat industry and research institutions by using non-invasive and time- and cost-efficient carcass component measuring techniques.Entities:
Keywords: Carcass component; Carcass quality; Guinea pig; Prediction model
Mesh:
Year: 2018 PMID: 29533812 DOI: 10.1016/j.meatsci.2018.02.019
Source DB: PubMed Journal: Meat Sci ISSN: 0309-1740 Impact factor: 5.209