Drying is an effective method to reduce potato storage loss. However, potatoes have high porosity with high water content. Shrinkage during drying can lead to folding and cracking of the dried product form. Therefore, this study explored the correlation between the 3D morphology and temperature distribution changes of potato slices during drying, with the aim of providing a reference for the detection of quality changes. An online automatic acquisition device to obtain 3D morphology and temperature information was designed and built. Hot air-drying experiments were conducted on the potato slices. 3D morphology images and temperature images of the potato slices were acquired by 3D and temperature sensors, and the two images were registered using the random sample consensus (RANSAC) algorithm. The region of interest of each image was extracted by algorithms such as threshold segmentation, hole filling and morphological erosion, and the 3D morphology information and temperature information were obtained. The mapping, range and average of each acquisition point were calculated for correlation analysis. Spearman's rank correlation coefficients and Maximum Information Coefficient (MIC) values were selected as measures for the correlation study. The results showed that the Spearman's rank correlation coefficients between average height and average temperature were mostly above 0.7 in absolute value, and the MICs were mostly above 0.9. The average values of the 3D information and temperature information exhibited an extremely strong correlation. This paper gives a new approach to investigate the morphological changes in the drying process by quantifying the relationship between 3D morphology and temperature distribution. This can guide the improvement of potato drying and processing methods.
Keywords: 3D morphology; Correlation analysis; Drying; Potato slices; Temperature field.
© 2023 The Authors. Published by Elsevier B.V.