Location: Subtropical Horticulture Research
Project Number: 6038-21000-026-012-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: May 1, 2024
End Date: Apr 30, 2029
Objective:
This study employs genomics and phenomics tools to characterize subtropical horticulture and ornamental germplasm collections and demonstrate their value to stakeholders and growers in Southeast Asia and the nation. Using cutting-edge methodologies enables us to identify these collections' genetic and phenotypic traits, critical to effectively managing and conserving natural resources. Through this investigation, we seek to provide valuable insights to growers and stakeholders, enabling them to make informed decisions and optimize resource utilization in subtropical horticulture and ornamental germplasm cultivation.
Approach:
This study aims to generate high-quality data on soil structure and microbiome across the Subtropical Horticulture Research Station location. The USDA-ARS in Miami and Florida International University (FIU) scientists will collaborate to generate the data, which will be analyzed using bioinformatics tools and a contemporary analytical pipeline at FIU. The FIU team will perform SFR and wet lab analysis of soil and microbiome analysis.
Achieving the goals of this project will strengthen and enhance the research programs of both entities by increasing their understanding of the role of plant genetic diversity in supporting better soil structure and enhancing beneficial microorganisms. This research affirms our mutual interest in cooperative research programs and exchanges, benefiting both parties and the people of the United States.
Roles and responsibilities: Drs. Singh and Bhaskar will be responsible for planning the project and executing this research with team members. PI and CO-PI from USDA-ARS, Co-PIs from UF will oversee and supervise the research associate recruited to achieve the project's goal. The research outcome will be shared equally, leading to publication(s). PI and Co-PIs will be co-accountable for data generation and quality research.
