Digital Image Analysis (DIA) has emerged as a transformative tool in food science, particularly in quality control, safety, and analysis. DIA techniques allow for non-destructive testing, rapid assessments, and remote accessibility, addressing the industry's growing demand for efficiency and accuracy. This technology converts visual data into computer-readable formats, enabling detailed analysis of food characteristics through pixel grids. Various DIA applications include detecting pesticide residues in grapes, acrylamide levels in Potato chips, and adulterants in food products such as milk and ethanol-based beverages. Additionally, DIA aids in grading dried figs, predicting moisture content of bell pepper in drying processes, estimating live animal weights without invasive methods and detecting nitrite in food samples. This paper explores the key components of DIA, such as image acquisition, feature extraction, and processing, alongside their practical applications in food quality control, illustrating the potential for DIA to enhance food safety and efficiency across the food industry.
Nagaty, Y. (2025). Digital Image Analysis (DIA) in Food Technology. Alexandria Journal of Food Science and Technology, 22(2), 29-34. doi: 10.21608/ajfs.2025.340104.1062
MLA
Youssef Ehab Nagaty. "Digital Image Analysis (DIA) in Food Technology", Alexandria Journal of Food Science and Technology, 22, 2, 2025, 29-34. doi: 10.21608/ajfs.2025.340104.1062
HARVARD
Nagaty, Y. (2025). 'Digital Image Analysis (DIA) in Food Technology', Alexandria Journal of Food Science and Technology, 22(2), pp. 29-34. doi: 10.21608/ajfs.2025.340104.1062
VANCOUVER
Nagaty, Y. Digital Image Analysis (DIA) in Food Technology. Alexandria Journal of Food Science and Technology, 2025; 22(2): 29-34. doi: 10.21608/ajfs.2025.340104.1062
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