Location: Plant Science Research
Project Number: 5062-21500-001-038-R
Project Type: Reimbursable Cooperative Agreement
Start Date: Oct 1, 2025
End Date: Aug 14, 2028
Objective:
1. Identify QTLs or genes associated with yield, low-pH, and high-Al tolerance across different environments.
2. Identify the top five germplasm for each region based on differential acid soil performance index taking into consideration regional adaptation, forage yield and sustainability traits.
3. Pre-Breeding to create new populations and novel germplasm, and incorporate low pH tolerance in elite germplasm.
4. Improve stakeholder knowledge and awareness of challenges and management to grow productive alfalfa on acidic soils and the value of low pH tolerant cultivars by developing regional workshops and field days, extension publications, and online media.
Approach:
The project will employ a multi-faceted strategy to achieve its objectives. The team will integrate field experiments, controlled environment studies, and advanced data analytics to evaluate crop performance under varying environmental conditions. Cooperators will establish replicated trials across diverse locations to capture variability in soil, climate, and management practices. These trials will include standardized protocols for planting, irrigation, and nutrient management to ensure consistency across sites. Phenotypic data will be collected using high-throughput methods, including imaging and sensor-based technologies, to monitor growth, stress responses, and yield components. Cooperators will implement sampling schedules to capture temporal dynamics of plant development. Data will be curated and stored in a centralized system for subsequent analysis. Genomic and transcriptomic approaches will be applied to identify genetic markers associated with resilience traits. Cooperators will conduct bioinformatic analyses to integrate multi-omic datasets, enabling identification of candidate genes and pathways. These insights will inform predictive models for trait selection and breeding strategies. Controlled environment experiments will complement field studies by isolating specific stress factors such as drought and heat. Cooperator will utilize growth chambers and greenhouse facilities to simulate conditions and validate findings from field trials. Physiological measurements, including photosynthetic efficiency and water-use metrics, will be recorded to understand mechanisms underlying stress tolerance. Statistical and machine learning models will be developed to analyze complex datasets and predict genotype-by-environment interactions. Outcomes will guide decision-making for breeding programs and management practices aimed at improving crop resilience. The project emphasizes stakeholder engagement and knowledge dissemination. Cooperators will organize workshops and develop outreach materials to share findings with producers, extension specialists, and policy makers. These activities will ensure that research outputs translate into practical solutions for agricultural sustainability.