应用近红外高光谱成像预测三文鱼肉的水分含量

应用近红外高光谱成像技术实现三文鱼肉水分含量的快速无损检测。采集来自不同部位的三文鱼肉共90个样本的高光谱图像，提取样本感兴趣区域(ROI)的平均光谱。随机取60个样本作为建模集，其余30个样本作为预测集。分别采用偏最小二乘回归(PLSR)和最小二乘支持向量机(LS-SVM)对全波段和水分含量建立相关性模型，并对预测集样本的水分含量进行预测。再用一种新的变量提取方法random frog选择特征波长，并基于特征波长分别建立水分检测的PLSR和LS-SVM模型。特征波长模型的预测精度虽然稍逊于全波段模型，但是仅用12个变量代替了全波段的151个变量，大大简化了模型，更便于实际应用。PLSR和LS-SVM特征波长模型的预测相关系数(R_p)分别为0.92和0.93，预测均方根误差(RMSEP)分别为1.31%和1.18%，取得了满意的结果。研究表明，近红外高光谱成像与化学计量学方法结合可以准确预测三文鱼肉的水分含量，为鱼肉品质的快速监测提供重要的参考。

Application of Near-Infrared Hyperspectral Imaging to Predicting Water Content in Salmon Flesh

Near-infrared hyperspectral imaging technique was employed in the present study to determine water contents in salmon flesh rapidly and nondestructively. Altogether 90 samples from different positions of salmon fish were collected for hyperspectral image scanning, and mean spectra were extracted from the region of interest (ROI) inside each image. Sixty samples were randomly selected as calibration set, and the remaining 30 samples formed prediction set. The full-spectrum and water contents were correlated using partial least squares regression (PLSR) and least-squares support vector machines (LS-SVM), which were then applied to predict water contents for prediction samples. A novel variable extraction method called random frog was applied to select effective wavelengths (EWs) from the full-spectrum. PLSR and LS-SVM calibration models were established respectively to detect water contents in salmon based on the EWs. Though the performances of EWs-based models were worse than models using full-spectrum, only 12 wavelengths were used to substitute for the original 151 wavelengths, thus models were greatly simplified and more suitable for practical application. For EWs-based PLSR and LS-SVM models, satisfactory results were achieved with correlation coefficient of prediction (R_p) of 0.92 and 0.93 respectively, and root mean square error of prediction (RMSEP) of 1.31% and 1.18% respectively. The results indicated that near-infrared hyperspectral imaging combined with chemometrics allows accurate prediction of water contents in salmon flesh, providing important reference for the rapid inspection of fish quality.