Pu Yuan-Yuan, Sun Da-Wen
Food Refrigeration and Computerized Food Technology (FRCRT), School of Biosystems Engineering, University College Dublin, National University of Ireland, Agriculture and Food Science Centre, Belfield, Dublin 4, Ireland.
Food Refrigeration and Computerized Food Technology (FRCRT), School of Biosystems Engineering, University College Dublin, National University of Ireland, Agriculture and Food Science Centre, Belfield, Dublin 4, Ireland.
Food Chem. 2015 Dec 1;188:271-8. doi: 10.1016/j.foodchem.2015.04.120. Epub 2015 Apr 27.
Mango slices were dried by microwave-vacuum drying using a domestic microwave oven equipped with a vacuum desiccator inside. Two lab-scale hyperspectral imaging (HSI) systems were employed for moisture prediction. The Page and the Two-term thin-layer drying models were suitable to describe the current drying process with a fitting goodness of R(2)=0.978. Partial least square (PLS) was applied to correlate the mean spectrum of each slice and reference moisture content. With three waveband selection strategies, optimal wavebands corresponding to moisture prediction were identified. The best model RC-PLS-2 (Rp(2)=0.972 and RMSEP=4.611%) was implemented into the moisture visualization procedure. Moisture distribution map clearly showed that the moisture content in the central part of the mango slices was lower than that of other parts. The present study demonstrated that hyperspectral imaging was a useful tool for non-destructively and rapidly measuring and visualizing the moisture content during drying process.
使用内部配备真空干燥器的家用微波炉对芒果片进行微波真空干燥。采用两个实验室规模的高光谱成像（HSI）系统进行水分预测。佩奇模型和双项薄层干燥模型适用于描述当前干燥过程，拟合优度R(2)=0.978。应用偏最小二乘法（PLS）将每个切片的平均光谱与参考水分含量相关联。通过三种波段选择策略，确定了与水分预测对应的最佳波段。将最佳模型RC-PLS-2（Rp(2)=0.972，RMSEP=4.611%）应用于水分可视化过程。水分分布图清楚地表明，芒果片中心部分的水分含量低于其他部分。本研究表明，高光谱成像是在干燥过程中无损、快速测量和可视化水分含量的有用工具。
