Quality and Technology, Department of Food Science, Faculty of Life Sciences, University of Copenhagen, Rolighedsvej 30, DK-1958 Frederiksberg C, Denmark.
Appl Spectrosc. 2012 Feb;66(2):218-26. doi: 10.1366/11-06396.
The present work describes a measurement method using spatially resolved near-infrared (NIR) spectroscopy to determine porcine carcass fat quality as a function of the distance to the skin by estimating its iodine value (IV). The new method is capable of performing on-line carcass grading at full production speed (approximately 1000 carcasses per hour). The method is demonstrated in an experiment where 35 carcasses were sampled at an abattoir, selected from three feeding groups. The NIR transmission instrument was applied on the loin of each carcass, and a parallel reference sample was removed and processed into 1.8 mm thick disks, representing a depth-of-fat profile from the loin. The disks were analyzed for fatty acid composition using gas chromatography (GC) and for IV. A principal component analysis (PCA) of the obtained GC reference values clearly showed that the feeding regimes can be differentiated. Using interval partial least squares (iPLS) regression, a model was produced that can predict the IV of the fat at a given measured depth with a root mean square error of cross-validation (RMSECV) of 1.44. The results show how the IV varies as a function of feeding regime and as a function of fat depth. The maximum variation found within a single depth profile was 10.1 IV from the skin to the innermost part of the fat layers. In the sample material investigated the average span in IV between the average values of the two porcine backfat layers was 6.4 IV (the maximum difference was 8.6 IV). The new method can provide the abattoir with new chemical information about fat quality and production quality that will open new possibilities of meat/carcass grading and product development.
本工作描述了一种使用空间分辨近红外（NIR）光谱法测量猪胴体脂肪质量的方法，该方法通过估计碘值（IV），可以确定其与皮肤的距离。新方法能够以全生产速度（约每小时 1000 个胴体）进行在线胴体分级。该方法在屠宰场进行的实验中得到了验证，在该实验中，从三个饲养组中选择了 35 个胴体进行采样。将 NIR 透射仪器应用于每个胴体的腰部，并从腰部取下一个平行的参考样品并加工成 1.8 毫米厚的圆盘，代表脂肪的深度轮廓。使用气相色谱法（GC）对圆盘进行脂肪酸组成分析，并进行 IV 分析。获得的 GC 参考值的主成分分析（PCA）清楚地表明，可以区分饲养制度。使用区间偏最小二乘（iPLS）回归，生成了一个模型，该模型可以在给定的测量深度下预测脂肪的 IV，其交叉验证均方根误差（RMSECV）为 1.44。结果表明 IV 如何随饲养制度和脂肪深度而变化。在单个深度轮廓内发现的最大变化是从皮肤到脂肪层最内层的 10.1 IV。在所研究的样品材料中，两层猪背脂平均值之间 IV 的平均跨度为 6.4 IV（最大差异为 8.6 IV）。新方法可以为屠宰场提供有关脂肪质量和生产质量的新化学信息，从而为肉类/胴体分级和产品开发开辟新的可能性。
