Teagasc, Ashtown Food Research Centre, D15DY05, Ashtown, Dublin 15, Ireland.
Instituto de Ganadería de Montaña (CSIC-Universidad de León), Finca Marzanas, E-24346, Grulleros, León, Spain.
Meat Sci. 2018 Aug;142:52-58. doi: 10.1016/j.meatsci.2018.04.007. Epub 2018 Apr 9.
Visible-near infrared spectroscopy (Vis-NIRS) has been suggested to have potential for authentication of food products. The aim of the present preliminary study was to assess if this technology can be used to authenticate the ageing time (3, 7, 14 and 21 days post mortem) of beef steaks from three different muscles (M. Longissimus thoracis, M. Gluteus medius and M. Semitendinosus). Various mathematical pre-treatments were applied to the spectra to correct scattering and overlapping effects, and then partial least squares-discrimination analysis (PLS-DA) procedures applied. The best models were specific for each muscle, and the ability of prediction of ageing time was validated using full (leave-one-out) cross-validation, whereas authentication performance was evaluated using the parameters of sensitivity, specificity and overall correct classification. The results indicate that overall correct classification ranging from 94.2 to 100% was achieved, depending on the muscle. In conclusion, Vis-NIRS technology seems a valid tool for the authentication of ageing time of beef steaks.
可见-近红外光谱(Vis-NIRS)在食品产品认证方面具有潜力。本初步研究的目的是评估该技术是否可用于验证来自三个不同肌肉(胸最长肌、臀中肌和半腱肌)的牛肉排的老化时间(死后 3、7、14 和 21 天)。对光谱应用了各种数学预处理方法来校正散射和重叠效应,然后应用偏最小二乘判别分析(PLS-DA)程序。最佳模型针对每个肌肉都是特定的,并且使用完整(留一法)交叉验证验证了老化时间预测的能力,而验证性能则使用灵敏度、特异性和总体正确分类的参数进行评估。结果表明,根据肌肉的不同,总体正确分类率从 94.2%到 100%不等。总之,Vis-NIRS 技术似乎是验证牛肉排老化时间的有效工具。