Artificial intelligence in food quality assessments

• Main Author: Hashim, Norhashila
• Format: Conference or Workshop Item
• Language: English
• Published: 2023
• Online Access: http://psasir.upm.edu.my/id/eprint/111482/1/Short%20communication%20note%202023.pdf; http://psasir.upm.edu.my/id/eprint/111482/
• Institution: Universiti Putra Malaysia

The agricultural and food industries have witnessed significant transformation in recent decades due to the rapid growth of science and technology. Technological innovations have improved and increased the efficiency of food production to meet the continuously growing demand due to the increasing population. Food loss and spoilage, low-quality food items supply, manufacturing contamination, unauthorized addition of preservatives and additives, food fraud and adulteration are just a few of the threats faced by food security (Hu et al., 2019; Tan & Xu, 2020). Poor monitoring techniques of food quality contribute to the threat received by food safety which leads to high spoilage and wastage. Food deterioration is detrimental to people’s health and the nation’s economy (Arshad et al., 2023). To abate the health complications and hazards due to food quality deterioration, the rapid assessment of food quality is brought into the limelight and developed into a major area of interest for researchers and industrial food producers. This sets Artificial intelligence (AI) on the right track in promoting rapid food quality assessment by integrating it with high-capacity sensors, vast databases, and computing techniques such as soft computing, internet computing and the Internet of Things (IoT). AI is essential to expedite the advancement of reliable and improved food quality assessment with hastened response capability and delivers results with high precision and repeatability during the process (Addanki et al., 2022). AI does not only improve time efficiency but also serves as the benchmark for state-of-art non-invasive food quality assessment techniques.