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Título

On-line application of visible and near infrared reflectance spectroscopy to predict chemical-physical and sensory characteristics of beef quality

AutorPrieto, Nuria ; Ross, D. W.; Navajas, E. A.; Nute, G. R.; Richardson, R. I.; Hyslop, J. J.; Simm, G.; Roehe, R.
Palabras claveNear infrared reflectance spectroscopy
Beef
Meat quality
Chemical-physical parameters
Sensory characteristics
Fecha de publicación2009
EditorElsevier
CitaciónMeat Science, 83: 96-103 (2009)
ResumenThe aim of this study was to assess the on-line implementation of visible and near infrared reflectance (Vis-NIR) spectroscopy as an early predictor of beef quality traits, by direct application of a fibre-optic probe to the muscle immediately after exposing the meat surface in the abattoir. Samples from M. longissimus thoracis from 194 heifers and steers were scanned at quartering 48 h postmortem over the Vis-NIR spectral range from 350 to 1800 nm. Thereafter, samples from M. longissimus thoracis et lumborum were analysed for colour (L*, a*, b*; 48 h postmortem), cooking loss (14 days postmortem), instrumental texture (Volodkevitch, 10 days aged meat; slice shear force, 3 and 14 days aged meat) and sensory characteristics. Vis-NIR calibrations, tested by cross-validation, showed high predictability for L*, a* and b* (R-2 = 0.86, 0.86 and 0.91; SECV = 0.96, 0.95 and 0.69, respectively). The accuracy of Vis-NIR to estimate cooking loss and instrumental texture ranged from R-2 = 0.31 to 0.54, suggesting relatively low prediction ability. Sensory characteristics assessed on 14 days aged meat samples showed R 2 in the range from 0.21 (juiciness) to 0.59 (flavour). Considering the subjective assessment of sensory characteristics the correlations of Vis-NIR measurements and several meat quality traits in the range from 0.46 to 0.95 support the use of on-line Vis-NIR in the abattoir. Improvement of predictability was achieved if only extreme classes of meat characteristics have to be predicted by Vis-NIR spectroscopy.
Descripción8 pages, 3 figures, 3 tables.
Versión del editorhttp://dx.doi.org/10.1016/j.meatsci.2009.04.005
URIhttp://hdl.handle.net/10261/22262
DOI10.1016/j.meatsci.2009.04.005
ISSN0309-1740
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