Abstract The feasibility of using NIR hyperspectral imaging technique for predicting fat and moisture contents in salmon fillets was assessed by integrating both characteristic wavelengths and image texture features. Monte Carlo-uninformative variable elimination (MC-UVE) and successive projections algorithm (SPA) were combined to extract characteristic wavelengths. Ten textural features of the principal component images were obtained using histogram statistics (HS) and gray level co-occurrence matrices (GLCMs) methods. Three types of models (PLS, MLR and LS-SVM) were established based on different types of inputs including only characteristic wavelengths, only texture parameters and combination both characteristic wavelengths and textures, respectively. Compared among all models, LS-SVM model coupled with wavelength and texture information gave the highest prediction accuracies with RP = 0.9685, RMSEP = 1.1750, RPD = 4.0162 for fat and RP = 0.9688, RMSEP = 0.8021, RPD = 4.0357 for moisture, respectively. This study showed that the prediction accuracy can be improved by combining spectral features with textural features and the fusion of characteristic wavelength and textural features had better potential than single spectral information in assessing the fat and moisture contents of salmon. Satisfactory prediction results confirmed the suitability of NIR hyperspectral imaging for quantitative prediction of fat and moisture in salmon.

中文翻译：

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使用近红外高光谱成像结合光谱和纹理特征无损测定鲑鱼（Salmo salar）鱼片中的脂肪和水分含量

摘要 通过整合特征波长和图像纹理特征，评估了使用 NIR 高光谱成像技术预测鲑鱼鱼片脂肪和水分含量的可行性。蒙特卡罗非信息变量消除（MC-UVE）和连续投影算法（SPA）相结合来提取特征波长。使用直方图统计 (HS) 和灰度共生矩阵 (GLCM) 方法获得主成分图像的十个纹理特征。基于不同类型的输入分别建立了三种类型的模型（PLS、MLR和LS-SVM），包括仅特征波长、仅纹理参数和特征波长和纹理的组合。在所有型号中比较，LS-SVM 模型结合波长和纹理信息给出了最高的预测精度，RP = 0.9685、RMSEP = 1.1750、RPD = 4.0162（脂肪）和 RP = 0.9688、RMSEP = 0.8021、RPD = 4.0357（水分）。本研究表明，结合光谱特征和纹理特征可以提高预测精度，特征波长和纹理特征的融合在评估鲑鱼脂肪和水分含量方面比单一光谱信息具有更好的潜力。令人满意的预测结果证实了 NIR 高光谱成像对鲑鱼脂肪和水分定量预测的适用性。本研究表明，结合光谱特征和纹理特征可以提高预测精度，特征波长和纹理特征的融合在评估鲑鱼脂肪和水分含量方面比单一光谱信息具有更好的潜力。令人满意的预测结果证实了近红外高光谱成像对鲑鱼脂肪和水分定量预测的适用性。本研究表明，结合光谱特征和纹理特征可以提高预测精度，特征波长和纹理特征的融合在评估鲑鱼脂肪和水分含量方面比单一光谱信息具有更好的潜力。令人满意的预测结果证实了近红外高光谱成像对鲑鱼脂肪和水分定量预测的适用性。