Location: Plant Stress and Germplasm Development Research
Project Number: 3096-21000-023-013-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: May 15, 2026
End Date: May 14, 2029
Objective:
1. To conduct research on crop (cotton, sorghum and peanut etc.) stress resilience including a fundamental understanding of agronomic, physiological, canopy architectural, genetic, and biochemical mechanisms controlling qualitative and quantitative yield gains and penalties.
2. To use remote sensing and machine learning tools to phenotype traits related to stress resilience in the target crop species, improving the efficiency and precision of data collection
3. Identify new germplasm and develop management systems for target nvironments, using strategies for optimizing production in rain-fed conditions in the Southern Great Plains.
4. Identify crop biochemical traits such as volatile organic compounds and metabolites that may elucidate resilience to crop stress.
Approach:
Crop stresses and their combined effects are having immense impact on producers’ needs to increase productivity of major crops of economic importance in the Southern Great Plains (SGP). With diminishing available agricultural water from the Ogallala aquifer, high temperatures, and erratic in-season precipitation, enhancing crop resilience using a multi-disciplinary research approach will be key to addressing current challenges facing farmers of the SGP. This proposed research is part of a collaborative effort between USDA-ARS, PA, CSRL, Lubbock, TX and Texas Tech University, Davis College, Plant and Soil Science Department, Lubbock, TX, to support research for enhancing resilience to abiotic stress in major crops of economic importance of the SGP. This research includes a fundamental understanding of agronomic, physiological, genetics, and biochemical mechanisms controlling crop resilience and adaptability, and the development of new germplasm/technologies for optimizing production in rain-fed production systems. The project will include laboratory, controlled chambers, producer's field, and greenhouse studies. Experiments elucidating variations in combined abiotic stresses on plant volatile organic compounds and metabolites will be conducted using advanced instrumentation and specialized crop growth chambers at Texas Tech University. In addition, remote sensing tools such as unmanned aerial systems (UAS) will be deployed to collect high-resolution multispectral, thermal, and structural data related to crop performance and key traits of interest across controlled and field environments. These datasets will support high-throughput phenotyping efforts and enable spatial and temporal monitoring of stress responses. Machine learning models will be integrated into the workflow to enhance data processing efficiency, identify complex trait–environment interactions, and improve predictive capacity for crop resilience under variable SGP conditions. Trait responses from controlled chambers, greenhouse, and field evaluations will be analyzed using appropriate statistical tools in JMP, SAS, and SPSS. Field evaluations will use randomized complete block design with 4 replications. In addition, this project will provide goods and services necessary to carry out research of mutual interest to stakeholders, the Agency, and University on the SGP. An integrative part of the project will be training of graduate students.