Department of Food Quality and Sensory Science, Teagasc Food Research Centre, Ashtown, Dublin 15, Ireland; School of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland.
School of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland.
Meat Sci. 2020 Jan;159:107915. doi: 10.1016/j.meatsci.2019.107915. Epub 2019 Aug 16.
The aim of this study was to calibrate chemometric models to predict beef M. longissimus thoracis et lumborum (LTL) sensory and textural values using visible-near infrared (VISNIR) spectroscopy. Spectra were collected on the cut surface of LTL steaks both on-line and off-line. Cooked LTL steaks were analysed by a trained beef sensory panel as well as undergoing WBSF analysis. The best coefficients of determination of cross validation (RCV) in the current study were for textural traits (WBSF = 0.22; stringiness = 0.22; crumbly texture = 0.41: all 3 models calibrated using 48 h post-mortem spectra), and some sensory flavour traits (fatty mouthfeel = 0.23; fatty after-effect = 0.28: both calibrated using 49 h post-mortem spectra). The results of this experiment indicate that VISNIR spectroscopy has potential to predict a range of sensory traits (particularly textural traits) with an acceptable level of accuracy at specific post-mortem times.
本研究旨在利用可见-近红外（VISNIR）光谱技术对牛肉背最长肌（LTL）的感官和质地值进行化学计量模型校准。在在线和离线条件下对 LTL 牛排的切面采集光谱。对经过烹饪的 LTL 牛排进行训练有素的牛肉感官小组分析以及进行 WBSF 分析。本研究中交叉验证（RCV）的最佳决定系数（RCV）适用于质地特性（WBSF=0.22；纤维状=0.22；易碎质地=0.41：所有 3 个模型均使用死后 48 小时的光谱进行校准）和一些感官风味特性（脂肪口感=0.23；脂肪后效=0.28：均使用死后 49 小时的光谱进行校准）。该实验结果表明，在特定的死后时间内，VISNIR 光谱技术具有预测一系列感官特性（特别是质地特性）的潜力，且具有可接受的准确度。
