Université Clermont Auvergne, INRA, VetAgro Sup, UMR Herbivores, 63122 Saint-Genès-Champanelle, France.
Université Clermont Auvergne, INRA, VetAgro Sup, UMR Herbivores, 63122 Saint-Genès-Champanelle, France.
Meat Sci. 2019 Dec;158:107910. doi: 10.1016/j.meatsci.2019.107910. Epub 2019 Aug 8.
The aim of this study was to compare visible-near-infrared spectroscopy (VIS/NIRS) models developed from fresh or freeze-dried samples for predicting the fatty acid (FA) composition of beef samples. The hypothesis tested is that the removal of water from samples could improve the VIS/NIRS model performance. A total of 454 beef samples obtained from different bovine muscles were used. No significant differences were found in the performance of VIS/NIRS models developed from fresh or freeze-dried samples for predicting both major individual FAs and families of FAs and for some FAs (16:0, 18:0, 18:1 n-9, 18:2 n-6, 20:4 n-6, 22:5 n-3, 22:6 n-3, saturated, mono-unsaturated FA, and total n-3 long chain poly-unsaturated FAs (PUFA)). In contrast, the standard error of predictions for total PUFAs, total n-3 PUFAs, total conjugated linoleic acid, 20:5 n-3, and 18:3 n-3 were improved (by 21% on average; P < .05) in freeze-dried samples compared with fresh samples.
本研究旨在比较从新鲜或冻干样本中开发的可见-近红外光谱（VIS/NIRS）模型，以预测牛肉样本的脂肪酸（FA）组成。测试的假设是，从样本中去除水分可以提高 VIS/NIRS 模型的性能。总共使用了 454 个来自不同牛肌肉的牛肉样本。结果发现，从新鲜或冻干样本中开发的 VIS/NIRS 模型在预测主要个体 FA 和 FA 家族以及某些 FA（16:0、18:0、18:1 n-9、18:2 n-6、20:4 n-6、22:5 n-3、22:6 n-3、饱和、单不饱和 FA 和总 n-3 长链多不饱和 FA（PUFA））方面的性能没有显著差异。相比之下，与新鲜样本相比，冻干样本中总多不饱和脂肪酸（PUFA）、总 n-3 多不饱和脂肪酸、总共轭亚油酸、20:5 n-3 和 18:3 n-3 的预测标准误差提高了（平均提高 21%；P<.05）。
