There is a consensus that agriculture in general and food production in particular are the sectors where digital innovations have a deep impact. Economical drivers are pushing for a technological revolution (industry 4.0), and this is affecting different elements of the food chain including food quality assessment. The digitalization of food leads to an increasingly automated, delocalized, and informatized process of production starting at the level of agricultural inputs, with seeds and other plant genetic material being transformed into digitalized sets of information, and ending with consumers that are now subjects of data-gathering mechanisms by food corporations that employ algorithms to categorize them and generate personalized offers for food they eat.

The food industry 4.0 is shifting demand from traditional, brick-and-mortar channels in food quality assessment to digital ones. This creates completely new forms of challenges to the people that try to ensure that safe and high-quality food is delivered to consumers around the world. Artificial intelligence coupled with computer vision, biometrics, robotics, and foodomics have already been applied to assess food quality, food production, and sensory and consumer acceptability.

Based on innovative digital food quality assessment solutions published in this Special Issue, novel strategies for process control with the aim of reducing food waste and increasing profitability might be developed to make the food industry more efficient and sustainable. This Special Issue will accept applied and basic research that generates new basic knowledge, evaluates prototype solutions, and creates results for innovation. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

• Computer vision system for food quality assessment
• 3D scanning for food quality assessment
• 3D food printing quality issues
• Multispectral imaging technology for food quality evaluation
• Artificial intelligence in food quality improvement
• Biometrics as tool to monitor food quality and authenticity
• Robotics in in food processing and automatic quality detection
• Foodomics in determining the food constituents and nutrients
• Digital image analysis for food quality assessment