Microbiome, Food, and Artificial Intelligence: Advancing Innovation and Sustainability

The interplay between microbiomes, food systems, and artificial intelligence (AI) represents a rapidly evolving area of research with profound implications for health, sustainability, and innovation. The microbiome—the diverse community of microorganisms inhabiting various ecosystems—plays a crucial role in food production, safety, and human health. Advances in sequencing technologies and multi-omics approaches have significantly expanded our understanding of these microbial communities. Simultaneously, AI and machine learning techniques have emerged as powerful tools to analyze complex microbiome datasets, predict microbial interactions, and develop innovative applications in food science. From improving food safety and personalized nutrition to reducing food waste and enhancing sustainable practices, this interdisciplinary field holds the promise of addressing pressing global challenges. This Research Topic seeks to capture the latest advancements and foster collaboration across microbiology, food technology, and AI to drive innovation and impactful solutions.

The goal of this Research Topic is to address the critical need for innovative solutions at the intersection of microbiome science, food systems, and AI. Despite significant progress, challenges remain in harnessing microbiome data to improve food safety, quality, and sustainability. The complexity of microbiome datasets, coupled with the intricacies of food matrices and human health interactions, calls for advanced AI tools and interdisciplinary collaboration. Recent advances in high-throughput sequencing, machine learning, and predictive modeling provide unprecedented opportunities to decode the microbiome’s role in food systems. By integrating microbiome insights with AI technologies, researchers can develop targeted interventions, such as precision microbial management, personalized nutrition strategies, and AI-driven food safety systems. This Research Topic aims to provide a platform for showcasing these advancements, fostering cross-disciplinary dialogue, and inspiring actionable solutions to global challenges in food security, health, and sustainability.

This Research Topic aims to bring together cutting-edge research and advancements at the nexus of microbiome science, food technology, and AI. With the increasing recognition of the microbiome's role in food safety, quality, nutrition, and human health—coupled with the rapid development of AI technologies—this interdisciplinary field holds enormous potential for innovation and societal impact. Key objectives of this Research Topic include:

• Showcasing innovative applications of AI in microbiome research related to food
• Exploring how microbiome data can improve food safety, preservation, and personalized nutrition
• Bridging the gap between microbiome research and practical applications in the food industry

We invite submissions of original research articles, reviews, perspectives, and case studies on topics including, but not limited to:

• AI-driven microbiome analytics
• Microbiome and food safety
• Personalized nutrition and the microbiome
• Sustainable food systems and microbiome science
• Emerging technologies and data integration

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: food and health, food security, food nutrition, personalized nutrition, data science, Society Affiliation RT

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.