摘要
为研究真空冻干果蔬内部水分扩散及运移过程和规律,以茄子为研究对象,运用图像处理技术建立水分运移微位移场并以微位移量对真空冻干过程中果蔬内部水分扩散及运移规律进行表达和定量分析。使用CCD(charge coupled device)相机每隔1 h采集茄子样本在真空冻干过程中横截面图像,直至6 h冷冻干燥完成终止。用自动阈值分割法、K均值聚类算法、伪彩色图像处理法可准确提取出原始图像中未冻干区域,再用Sobel边缘检测法提取得到水分边界。将6幅边界图像叠加并以物料几何中心为原点建立微位移场,用Harris角点检测法提取水分边缘与坐标轴相交的各个角点及其坐标值,计算得到每隔1 h各角点的位移量。通过对角点位移量与物料含水率相关性分析可知,模型显著性检验概率<0.000 1,决定系数达0.999 8,说明模型检验极显著且拟合精度高。回归参数的检验结果表明,四个角点的微位移量对物料含水率平方的响应极显著,说明物料干燥水分边界微位移场变化量与含水率的关系可用该回归模型预测,物料含水率可用表达水分边界的微位移场参数来表示。该研究为果蔬冻干水分在线检测提供了一种新的方法,同时也为探索冻干机理和低能耗冻干工艺提供了参考。
Vacuum freeze-drying, which is the transformation from ice to vapor without passing through the liquid phase,has a wide application in the food industry and is now increasingly being used in the agricultural products processing because the absence of heating in this process preserves nutrients and sensory characteristics within the fruits and vegetables. However, the sublimation process makes freeze-drying operation expensive to use. Therefore, it is important to research moisture diffusion and transfer process within fruits and vegetables. This paper provides a new experimental method based on image processing technique to estimate moisture ratio of eggplant samples by analyzing moisture diffusion and transfer process. Eggplant samples were bought from local supermarket, and the experiment was carried out at the mechanics laboratory of Shanxi agricultural university in 2015. After cleaning and peeling, eggplants were cut into 10 mm ×10 mm×10 mm cube samples by a sharp self-made knife, 30 regular samples（TA） and another 30 samples（TB） were chosen and frozen in a refrigerator at-40 ℃ for 10 ~12 h. However, TB would be treated by high pulsed electric field before freezing while TA without any treatments. After that, TA and TB were dried by JDG-0.2 vacuum freeze-drying machine.Meanwhile, section images of TA and TB were captured by a CCD camera with LED light source by 1h interval until drying end for 6h, and the mass of samples were measured simultaneously for calculating moisture ratio. All images, saved in RGB color model, were segmented with K-means clustering method, pseudo-color image processing method and automatic threshold segmentation method. Three cluster images were obtained with K-Means and pseudo-color method, and only No.3cluster was fit for further segmentation. Automatic threshold segmentation method was able to extract non-freeze-drying area（white pixel） correctly. After thresholding, sobel edge detection method was used to extract the boundary of non-freezedrying area. In order to obtain a boundary whose width was one pixel, a skeletal image processing method was used for treating the boundary. After that, displacement field was used to express the displacement change of moisture boundary during vacuum freeze-drying process. Geometric center of samples as the origin point of the coordinate system was established, and the dynamic change process of moisture boundary was shown clearly by means of six images overlapping.The Harris corner detection method was used to find the corner points on the boundary, and extract coordinate values of corner points which intersect the coordinate axis, displacement of the two adjacent points was calculated by 1h interval.SAS software was carried out to analyze correlation relationship between the displacement change of moisture boundary and moisture ratio. Regression analysis results showed that significant test probabilities of moisture ratio model was less than0.000 1, and the coefficients of determination（R2） was 0.999 8, which indicated that the model test was very significant and had quite strong explain ability and high fitting accuracy on original variable. Test results of regressive coefficient showed that the displacement of the four corner points and moisture-ratio-squared of the material were very significant（P0.000 1）.In other words, moisture ratio can be expressed and predicted by the displacement field of the moisture boundary. In summary, the mentioned model not only provides a new monitoring method of moisture ratio, but also gives a foundation of monitoring moisture ratio for other drying processes.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2016年第1期304-311,共8页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家自然科学基金资助项目(30771242
31171450)
山西农业大学科技创新基金项目(2014004)
关键词
冷冻
干燥
图像处理
茄子
真空冷冻干燥
水分运移
水分检测
freezing
drying
image processing
eggplant
vacuum freeze-drying
moisture diffusion and transfer
moisture measurement
