Multi-omics and AI-integrated exploration of sugar beet endophytes for sustainable crop improvement

Sugar beet possesses a wide range of endophytic microbial populations, with the highest densities typically reported in root tissues. These endophytes are associated with symbiotic interactions that can support plant health and yield, including biological nitrogen fixation and modulation of phytohormone and growth regulator pathways. Endophytes have also been reported to synthesize bioactive secondary metabolites with antimicrobial activity, which may contribute to biocontrol of phytopathogens and support host growth and development. The sugar beet endophytic microbiome comprises diverse bacterial and fungal taxa that occupy distinct ecological and functional niches. Moreover, host–endophyte interactions are increasingly recognized as important components of sustainable agriculture, as these microbes are explored as eco-friendly alternatives to chemical pesticides and fertilizers used in crop production. Despite this potential, a holistic synthesis of sugar beet endophytes—encompassing their taxonomic diversity and functional roles—remains limited. This review addresses this gap by critically examining the diversity and plant growth–associated traits of sugar beet endophytes, along with their reported contributions to biocontrol mechanisms. It also discusses the emerging role of artificial intelligence (AI) tools in endophyte research, including machine learning (ML) approaches for microbial detection, predictive modeling of plant–microbe interactions, and AI-assisted development of biocontrol strategies. Further research integrating metagenomic, metabolomic, and AI-enabled frameworks is required to better characterize endophytic functions and identify microbial candidates for next-generation bioinoculants, with the goal of improving resilience and sustainability in sugar beet production systems. Ultimately, the integration of AI-driven analytics with microbial biotechnology holds considerable promise, but its impact will depend on rigorous validation and field-level translation, to support long-term productivity and environmental sustainability in global sugar and ethanol production systems. Fungal and bacterial endophytic diversity in sugar beet is increasingly being identified through culture-dependent and molecular approaches. Symbiotic interactions with endophytes enhance sugar beet resilience. Omics tools help decode sugar beet endophyte–host relationships. Developing microbial consortia supports sustainable cultivation. Microbial consortia improve sugar beet growth and productivity. AI integration with endophyte research offers a forward-looking research direction. Future research should emphasize field-scale validation.