Department of Bioresource Engineering, McGill University, Macdonald Campus, 21,111 Lakeshore Road, Ste-Anne-de-Bellevue, QC H9X 3V9, Canada.
Department of Bioresource Engineering, McGill University, Macdonald Campus, 21,111 Lakeshore Road, Ste-Anne-de-Bellevue, QC H9X 3V9, Canada.
Meat Sci. 2021 Jun;176:108458. doi: 10.1016/j.meatsci.2021.108458. Epub 2021 Feb 13.
The fibrous structure of meat muscle makes it an anisotropic optical material. As such, spectral information varies with the orientation of the muscle. In this study, spectral data from pork cuts were obtained by a transverse scan (TRANSCAN), radial scan (RADISCAN), and longitudinal scan (LONGSCAN) by using hyperspectral imaging. The information was used to develop and compare the prediction models for intramuscular (IMF) content prediction by partial least square regression (PLSR), support vector machines regression (SVMR), and backpropagation artificial neural network (BPANN). The three modeling algorithms showed equal capability for modeling IMF in pork. The accuracy of the prediction models from the three scans was in the order of TRANSCAN ≥ RADISCAN ≥ LONGSCAN. Successive projection algorithm reduced the wavelengths to 93%. The reduced wavelengths were used to build new models that showed similar accuracy to the models of the original wavelengths. This study shows that muscle orientation influences the accuracy of the prediction models.
肉肌肉的纤维结构使其成为各向异性光学材料。因此，光谱信息随肌肉的方向而变化。在这项研究中，使用高光谱成像技术通过横切扫描（TRANSCAN）、径向扫描（RADISCAN）和纵向扫描（LONGSCAN）获得猪肉切片的光谱数据。利用这些信息，通过偏最小二乘回归（PLSR）、支持向量机回归（SVMR）和反向传播人工神经网络（BPANN）建立并比较了用于预测肌内脂肪（IMF）含量的预测模型。三种建模算法在建模猪肉 IMF 方面表现出相同的能力。三种扫描的预测模型的准确性顺序为 TRANSCAN≥RADISCAN≥LONGSCAN。连续投影算法将波长减少到 93%。减少的波长用于建立新模型，这些模型与原始波长模型的准确性相似。本研究表明，肌肉方向会影响预测模型的准确性。
