Biobanks have become vital resources for modern biomedical research, providing biological samples and associated data for the exploration of health and disease. The field has witnessed remarkable advancements in biobanking methods, including innovations in sample collection, preservation, and data management techniques. These improvements have not only enhanced the quality and accessibility of biobanks but also fostered collaboration among researchers across various disciplines, thereby expanding the potential for biomarker discovery and population health studies.

Enhancing biobank methodologies is crucial for the future of biomedical research, as it allows for more comprehensive and reproducible studies. Recent developments in high-throughput biobanking, data integration, and informatics have improved our capacity to analyze vast datasets, enabling researchers to glean insights from omics data and other biological information. Furthermore, integrating artificial intelligence and machine learning into biobank processes holds the promise of streamlining data management and improving the precision of biomarker identification, ultimately leading to more effective health interventions. Additionally, special attention will be dedicated to pediatric biobanks that support virtual, longitudinal cohorts for studying childhood disorders, accelerating the discovery and validation of biomarkers and therapeutic targets while maintaining rigorous ethical oversight.

Continued research and innovation in biobanking could lead to transformative advancements in precision medicine, enabling more personalized treatment strategies tailored to individual patients. Future studies may unlock new biomarkers linked to diseases, improve longitudinal data collection methods, and foster improved data sharing practices, thereby promoting transparency and collaboration in the scientific community.

Proposed topical themes of interest may include (but are not limited to):

• Innovations in biobank informatics
• Sample preservation techniques in biobanks
• High-throughput biobanking methods
• Data integration and sharing in biobanks
• Role of AI and machine learning in biobanking
• Ethical and societal considerations in advances in biobank methods and data sets including specific considerations regarding biobanking for children

This Collection supports and amplifies research related to SDG 3 Good Health and Well-being, SDG 9 Industry, Innovation and Infrastructure, SDG 12 Responsible Consumption & Production, and SDG 17 Partnerships for the Goals.

All manuscripts submitted to this journal, including those submitted to collections and special issues, are assessed in line with our editorial policies and the journal’s peer review process. Reviewers and editors are required to declare competing interests and can be excluded from the peer review process if a competing interest exists.

Reliable surveillance of crop pests and pathogens depends on well-documented, accessible datasets, yet the infrastructure for collecting, sharing, and reusing that data across agricultural systems remains inconsistent. Modelling and decision‑support tools play a critical role in pest management, early‑warning systems, and cross‑regional assessments of plant health.

We invite researchers to share datasets relevant to crop pest and disease monitoring, including field observations and controlled experiments, remote sensing, participatory programs, and modelling frameworks. how they are used to generate insights through modelling, forecasting, and early warning systems. Contributions from any geographic region, cropping system, or scale of observation are welcome.

We also welcome work that examines what makes datasets genuinely useful. Including labelling consistency, metadata completeness, and repository interoperability, particularly where these affect reproducibility and practical application of the datasets in question.

Topics relevant to this collection include:

• Field, glasshouse, and laboratory datasets supporting plant pathogen detection, identification, and quantification
• Remote sensing and imaging datasets applied to disease symptom mapping, canopy health assessment, or insect pressure monitoring
• Citizen science and participatory datasets from distributed pest and disease surveillance programs
• Phenotyping and disease resistance datasets, including trait quantification and screening outputs
• Epidemiological and population dynamics datasets, incorporating spatial, temporal, and environmental variables
• Open dataset infrastructure for crop health monitoring, including metadata standards, licensing, and repository design
• Integrated pest management datasets connecting field monitoring, environmental conditions, and intervention records
• Data harmonization and cross-platform integration

We invite researchers to submit their work to this Collection, which will showcase research, including, but not limited to, the topics listed above.

This Collection supports and amplifies research related to SDG 2: Zero Hunger, SDG 6: Clean Water and Sanitation, SDG 12: Responsible Consumption & Production and SDG 13: Climate Action, and SDG 15: Life on Land

All manuscripts submitted to this journal, including those submitted to collections and special issues, are assessed in line with our editorial policies and the journal’s peer review process. Reviewers and editors are required to declare competing interests and can be excluded from the peer review process if a competing interest exists.