Department of Food Quality and Sensory Science, Teagasc Food Research Centre, Ashtown, Dublin 15, Ireland.
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.
Meat Sci. 2020 Sep;167:108157. doi: 10.1016/j.meatsci.2020.108157. Epub 2020 Apr 24.
Rapid prediction of beef quality remains a challenge for meat processors. This study evaluated the potential of Raman spectroscopy followed by chemometrics for prediction of Warner-Bratzler shear force (WBSF), intramuscular fat (IMF), ultimate pH, drip-loss and cook-loss. PLS regression models were developed based on spectra recorded on frozen-thawed day 2 longissimus thoracis et lumborum muscle and validated using test sets randomly selected 3 times. With the exception of ultimate pH, models presented notable performance in calibration (R ranging from 0.5 to 0.9; low RMSEC) and, despite variability in the results, promising predictive ability: WBSF (RMSEP ranging from 4.6 to 9 N), IMF (RMSEP ranging from 0.9 to 1.1%), drip-loss (RMSEP ranging from 1 to 1.3%) and cook-loss (RMSEP ranging from 1.5 to 2.9%). Furthermore, the loading values indicated that the physicochemical variation of the meat influenced the models. Overall, results indicated that Raman spectroscopy is a promising technique for routine quality assessments of IMF and drip-loss, which, with further development and improvement of its accuracy could become a reliable tool for the beef industry.
快速预测牛肉品质仍然是肉类加工商面临的挑战。本研究评估了拉曼光谱结合化学计量学预测 Warner-Bratzler 剪切力(WBSF)、肌内脂肪(IMF)、最终 pH 值、滴水损失和蒸煮损失的潜力。基于冷冻解冻后第 2 天的背最长肌和腰大肌记录的光谱,建立了 PLS 回归模型,并使用随机选择的 3 次测试集进行了验证。除了最终 pH 值外,模型在校准中表现出了显著的性能(R 范围从 0.5 到 0.9;低 RMSEC),尽管结果存在变异性,但具有有希望的预测能力:WBSF(RMSEP 范围从 4.6 到 9 N)、IMF(RMSEP 范围从 0.9 到 1.1%)、滴水损失(RMSEP 范围从 1 到 1.3%)和蒸煮损失(RMSEP 范围从 1.5 到 2.9%)。此外,载荷值表明肉的物理化学变化影响了模型。总体而言,结果表明拉曼光谱是一种很有前途的技术,可以用于 IMF 和滴水损失的常规质量评估,如果进一步开发和提高其准确性,它可能成为牛肉行业的可靠工具。