Digital image analysis in food technology

Title : Digital image analysis in food technology

Abstract:

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, acrylamide levels, and adulterants in food products such as milk and ethanol-based beverages. Additionally, DIA aids in grading dried figs, predicting moisture content in drying processes, and estimating live animal weights without invasive methods. 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.

Biography:

Youssef Nagaty is a Teaching Assistant at the Department of Food Science and Technology, Faculty of Agriculture, Alexandria University. He earned his Bachelor of Science in Food Science and Technology (English Section) with honors in July 2023, graduating with a GPA of 3.55. With a strong interest in innovation and interdisciplinary learning, Youssef has completed a series of certified online courses through edX, offered by leading institutions such as Harvard University, Stanford University, Wageningen University, and Utrecht University. These courses covered a range of topics in Food science. In February 2025, Youssef participated as a speaker in the 5th International Conference on Food Safety, held at the Triumph Hotel in New Cairo. He delivered a lecture titled “Digital Image Analysis in Food Technology”.