Food is an essential part of human life and can be defined as the end product of agricultural activity, produced after processing the different products produced by farmers. The food industry plays a very pivotal role in both a country’s economy and the global economy, and so to ensure the quality of products and safety of food items, artificial intelligence (AI)-based smart solutions are much needed. Therefore, it is necessary to explore and use AI-based smart solutions in the food industry to fulfil societal needs, as by using these techniques farmers can produce more food grains at a lesser cost and can raise their income rapidly.

Artificial intelligence (AI) is now widely used in almost every aspect of life, enabling us to optimise and automate the manufacturing industry, revolutionising food production. With the help of an intelligent system, farmers can analyse and ensure the optimum conditions, such as seed and crop choice, water use, and temperature, so that food quality can be improved. AI technology also plays an important role in food processing, storage, and delivery of food items. Robots, intelligent machines, and drones can all play important roles in saving cost in terms of packaging and delivery of food items, in the completion of tasks in hazardous conditions, and in the production of quality food. To determine the performance of various AI models and algorithms for the food sector, there is a need to study various mathematical and statistical techniques, and the correlations between the various food industry parameters responsible for higher growth.

The aim of this Special Issue is to demonstrate new developments and application of artificial intelligence in food quality improvement. Our goal is to promote research and development in the use of AI in food quality improvement by publishing high-quality research papers in this interdisciplinary field that can profoundly impact the future of the food industry. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• Artificial intelligence for improving food quality
• Machine learning and AI in the food industry
• Modelling techniques used to improve food quality
• Food inspection and grading using artificial intelligence
• Machine learning techniques for increasing the productivity of high-quality food products
• The use of different image recognition technologies for improving food safety
• Application of AI techniques in fertiliser management to ensure safe food products
• The use of pesticide management using AI
• The use of robots for safety of food and food warehouses
• Food security through smart technologies
• Food safety information sharing mechanisms