Challenges and opportunities: computational biology and the future of agriculture

<h4>Motivation</h4>The world of agriculture is rapidly changing with advances in artificial intelligence and demands for greater feed and food security considering environmental and sustainability challenges. The 30th Conference on Intelligent Systems in Molecular Biology (ISMB) held in July 2022 featured an invited session on the role of computational biology in Digital and Precision Agriculture. This session featured presentations by experts from various subdisciplines on novel research discoveries and a panel discussion on Digital Agriculture at Scale. Topics discussed during the session included genetics, epigenetics, and genomics of agriculturally relevant species; foodborne pathogen genomics and epidemiology; plant and animal phenomics; AI/machine learning; image analysis; remote sensing; educational innovations; discoveries resulting from public-private partnerships; data sharing and findable, accessible, interoperable, and reproducible (FAIR) data standards; biotechnology; and soil microbial ecology and biogeochemistry.<h4>Results</h4>We present several of the current and future challenges and opportunities for computational biology in agriculture including why these challenges are important to address, what barriers exist, and what skills and competencies are required to be successful as a computational biologist in agriculture. We intend this summary to engage the computational biology community and attract them to the opportunities available for interesting and impactful work toward ensuring sustainable food security.