Pangenomics and AI-Assisted Crop Breeding for Combating Plant Diseases

The rising threat of plant diseases, intensified by climate change and evolving pathogen resistance, necessitates innovative approaches in crop breeding to ensure global food security. Finding core and accessory genes linked to disease resistance is made possible by pangenomics, which examines the whole gene sets within a species and provides unmatched insights into genetic variation. When combined with artificial intelligence (AI) models, this method transforms the identification and use of crop disease-resistant characteristics. This chapter examines how AI and pangenomics might work together to tackle plant diseases, with a focus on how they can speed up breeding initiatives. Large genomic datasets can be analyzed more easily thanks to AI techniques like machine learning and deep learning, which allow for accurate trait prediction and selection for hardy crop types. The chapter uses case studies to show how AI-driven technologies have streamlined the production of disease-tolerant crops by improving genomic selection, optimizing breeding pipelines, and identifying resistance genes. The integration of pangenomics with AI not only increases the efficiency of crop improvement but also addresses key challenges, such as managing big data, ensuring model accuracy, and considering ethical implications. This chapter outlines a revolutionary route for sustainable agriculture by fusing cutting-edge computational techniques with genomic technology, enabling scientists and breeders to successfully reduce plant diseases. These thorough insights provided open the door to utilize the potential of cutting-edge technology to protect the world’s food systems from the impending dangers of plant diseases and shifting environmental circumstances.