College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.
Anal Chim Acta. 2012 May 13;726:57-66. doi: 10.1016/j.aca.2012.03.038. Epub 2012 Mar 30.
Because the shape of prawn is not round, spectroscopy instruments cannot measure the spectra of the whole prawn without containing background information. In this study, an online hyperspectral imaging system in the spectral region of 380-1100 nm was developed to determine the moisture content of prawns at different dehydrated levels. Hyperspectral images of prawns were acquired at different dehydration periods. The spectra of prawns then were extracted from hyperspectral images based on 'Manual Prawn Mask' and 'Automatic Prawn Mask', respectively. Spectral data were analyzed using partial least squares regression (PLSR) and least-squares support vector machines (LS-SVM) to establish the calibration models, respectively. Successive projections algorithm (SPA) was first applied for the optimal wavelength selection in the hyperspectral image analysis. Out of 482 wavelengths, only twelve wavelengths (428, 445, 544, 569, 629, 672, 697, 760, 827, 917, 958, and 999 nm) were selected by SPA as the optimum wavelengths for moisture prediction. Based on these optimum wavelengths, a multiple linear regression (MLR) calibration model was established and used to obtain the moisture distribution of each prawn. The overall results of this study revealed the potentiality of hyperspectral imaging as an objective and non-destructive method to obtain the content and distribution of moisture of prawns whose shapes are not round.
由于对虾的形状不是圆形的，因此光谱仪器如果不包含背景信息，则无法测量整个对虾的光谱。在这项研究中，开发了一种在线在 380-1100nm 光谱区域的高光谱成像系统，以确定不同脱水水平下对虾的水分含量。在不同的脱水期采集对虾的高光谱图像。然后，分别基于“手动对虾遮罩”和“自动对虾遮罩”从高光谱图像中提取对虾的光谱。分别使用偏最小二乘回归（PLSR）和最小二乘支持向量机（LS-SVM）对光谱数据进行分析，以建立校准模型。首先在高光谱图像分析中应用连续投影算法（SPA）进行最佳波长选择。在 482 个波长中，SPA 仅选择了 12 个最佳波长（428、445、544、569、629、672、697、760、827、917、958 和 999nm），用于水分预测。基于这些最佳波长，建立了多元线性回归（MLR）校准模型，用于获取每个对虾的水分分布。这项研究的总体结果表明，高光谱成像作为一种客观，无损的方法，具有获取非圆形对虾的水分含量和分布的潜力。
