Table 1 Topic areas identified by the AG2PI Steering Committee and Scientific Advisory Board as being most critical to furthering AG2P science, in no particular order

Phenotyping technology development

In vivo/low-to-moderate throughput versus remote/high throughput measurement tools, integration of these

Predictive analytics development

Advancing big data tools, integrating statistics with machine learning techniques and artificial intelligence

Democratizing access to technology

Increase fluency in statistical/computational approaches, community investment in flexible software solutions, subsidize new tech testing

Convergence science

Facilitating collaborations across disciplines, integration of disciplinary approaches

Standardizing research methods and tools

Terminology, data collection, data storage and re-use, pipelines, maximize data interoperability

Advancing genomic research

Pangenomics, statistical models, and methods for fully leveraging low-pass sequencing data, data and support systems for predicting variant effect on phenotype

Advancing plant and animal breeding

Re-analyzing past selection programs with modern tools, Identifying areas for synergies, support for integrating genomic and phenomic data to optimize breeding decisions

Diversifying engagement

Learn from the approaches of indigenous and urban farmers, building translational validation studies broad enough for diverse producer types to participate