Artificial Intelligence in Agro-Food Systems: From Farm to Fork

Area of Science:

• Food Science and Technology
• Agricultural Science
• Computer Science

Background:

• Consumer demand drives focus on food quality, nutrition, and processing.
• Variability in food processing presents significant challenges.
• Artificial intelligence (AI) and machine learning (ML) offer interdisciplinary solutions.

Purpose of the Study:

• To review AI applications across diverse food industry sectors.
• To explore AI's role in enhancing food quality, safety, and processing.
• To examine advancements in 3D printing technology for the food industry.

Main Methods:

• Literature review of AI and ML applications in food processing.
• Analysis of AI integration in agriculture, bakery, beverage, dairy, and more.
• Exploration of 3D printing advancements and future perspectives.

Main Results:

• AI and ML are successfully applied in various food sectors, including packaging, sorting, and drying.
• Significant advancements are noted in improving food quality, safety, and shelf life.
• 3D printing technology shows potential for innovation in food manufacturing and service.

Conclusions:

• AI and ML are crucial for addressing food processing variability and enhancing industry performance.
• Continued integration of AI and ML promises further advancements in food quality and efficiency.
• Emerging technologies like 3D printing offer new avenues for food industry innovation.