Non-destructive monitoring of potato quality properties in storage by laser light backscattering imaging | ||
| تحقیقات سامانهها و مکانیزاسیون کشاورزی | ||
| Articles in Press, Accepted Manuscript, Available Online from 03 August 2026 | ||
| Document Type: Original Article | ||
| DOI: 10.22092/amsr.2026.372864.1536 | ||
| Authors | ||
| Mansoureh Mozaffari Gonbari* 1; Bahareh Jamshidi2; Jaber Soleymani3; Parisa zargaripour4 | ||
| 1Assistant professor, Agricultural Engineering Research Department, East Azarbaijan Agricultural and Natural Resources Research and Education center, AREEO, Tabriz, Iran | ||
| 2Associate professor, Smart Agricultural Research Department, Agricultural Engineering Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran | ||
| 3Assistant professor of Agricultural Engineering Research Department, East Azarbaijan Agricultural and Natural Resources Research and Education center, AREEO, Tabriz, Iran. | ||
| 4Agricultural Engineering Research Department, East Azarbaijan Agricultural and Natural Resources Research and Education center, AREEO, Tabriz, Iran. | ||
| Abstract | ||
| Monitoring the properties of potatoes during storage plays a crucial role in determining the chain of consumption, timely product supply and reducing waste. In this research, the non-destructive monitoring system of potato properties was developed using laser light backscatter imaging technology in the range of visible and near-infrared light and evaluated. Imaging was performed during product storage under cold storage at temperatures of 4°C and 7°C, as well as traditional storage. Two potato varieties, Agria and Jelly, were used in the experiments. Product properties, including moisture content, starch level, total soluble solids and texture firmness, were determined during storage. Features based on intensity and texture analyses of images were extracted. An artificial neural network model was employed to establish the relationship between the mentioned properties and image features. Based on the obtained results, the 680-nanometer wavelength was effective in predicting moisture content, while the 880-nanometer wavelength was better for predicting firmness. The combination of both wavelengths performed well in predicting starch content and total soluble solid content. The highest correlation coefficients were obtained for predicting moisture content, total soluble solid content, firmness, and starch percent were 0.76, 0.82, 0.71 and 0.73 respectively. These findings demonstrate the possibility of using laser backscattering imaging system for assessing the attributes of stored potatoes. | ||
| Keywords | ||
| Light scattering; Non-destructive tests; Quality monitoring; Storage | ||
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