Simone Savoia1,2, Andrea Albera3, Alberto Brugiapaglia4, Liliana Di Stasio4, Alessio Cecchinato5, Giovanni Bittante5. 1. Associazione Nazionale Allevatori Bovini di Razza Piemontese, strada provinciale Trinita' 32/A, 12061, Carrù, CN, Italy. simone.savoia@anaborapi.it. 2. Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova (Padua), viale dell'Università 16, 35020, Legnaro, PD, Italy. simone.savoia@anaborapi.it. 3. Associazione Nazionale Allevatori Bovini di Razza Piemontese, strada provinciale Trinita' 32/A, 12061, Carrù, CN, Italy. 4. Department of Agricultural, Forest and Food Sciences, University of Torino, Via L. Da Vinci 44, 10095, Grugliasco, TO, Italy. 5. Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova (Padua), viale dell'Università 16, 35020, Legnaro, PD, Italy.
Abstract
BACKGROUND: The possibility of assessing meat quality traits over the meat chain is strongly limited, especially in the context of selective breeding which requires a large number of phenotypes. The main objective of this study was to investigate the suitability of portable infrared spectrometers for phenotyping beef cattle aiming to genetically improving the quality of their meat. Meat quality traits (pH, color, water holding capacity, tenderness) were appraised on rib eye muscle samples of 1,327 Piemontese young bulls using traditional (i.e., reference/gold standard) laboratory analyses; the same traits were also predicted from spectra acquired at the abattoir on the intact muscle surface of the same animals 1 d after slaughtering. Genetic parameters were estimated for both laboratory measures of meat quality traits and their spectra-based predictions. RESULTS: The prediction performances of the calibration equations, assessed through external validation, were satisfactory for color traits (R2 from 0.52 to 0.80), low for pH and purge losses (R2 around 0.30), and very poor for cooking losses and tenderness (R2 below 0.20). Except for lightness and purge losses, the heritability estimates of most of the predicted traits were lower than those of the measured traits while the genetic correlations between measured and predicted traits were high (average value 0.81). CONCLUSIONS: Results showed that NIRS predictions of color traits, pH, and purge losses could be used as indicator traits for the indirect genetic selection of the reference quality phenotypes. Results for cooking losses were less effective, while the NIR predictions of tenderness were affected by a relatively high uncertainty of estimate. Overall, genetic selection of some meat quality traits, whose direct phenotyping is difficult, can benefit of the application of infrared spectrometers technology.
BACKGROUND: The possibility of assessing meat quality traits over the meat chain is strongly limited, especially in the context of selective breeding which requires a large number of phenotypes. The main objective of this study was to investigate the suitability of portable infrared spectrometers for phenotyping beef cattle aiming to genetically improving the quality of their meat. Meat quality traits (pH, color, water holding capacity, tenderness) were appraised on rib eye muscle samples of 1,327 Piemontese young bulls using traditional (i.e., reference/gold standard) laboratory analyses; the same traits were also predicted from spectra acquired at the abattoir on the intact muscle surface of the same animals 1 d after slaughtering. Genetic parameters were estimated for both laboratory measures of meat quality traits and their spectra-based predictions. RESULTS: The prediction performances of the calibration equations, assessed through external validation, were satisfactory for color traits (R2 from 0.52 to 0.80), low for pH and purge losses (R2 around 0.30), and very poor for cooking losses and tenderness (R2 below 0.20). Except for lightness and purge losses, the heritability estimates of most of the predicted traits were lower than those of the measured traits while the genetic correlations between measured and predicted traits were high (average value 0.81). CONCLUSIONS: Results showed that NIRS predictions of color traits, pH, and purge losses could be used as indicator traits for the indirect genetic selection of the reference quality phenotypes. Results for cooking losses were less effective, while the NIR predictions of tenderness were affected by a relatively high uncertainty of estimate. Overall, genetic selection of some meat quality traits, whose direct phenotyping is difficult, can benefit of the application of infrared spectrometers technology.
Authors: H Soyeurt; F Dehareng; N Gengler; S McParland; E Wall; D P Berry; M Coffey; P Dardenne Journal: J Dairy Sci Date: 2011-04 Impact factor: 4.034