Location: Plant Physiology and Genetics Research
2025 Annual Report
Objectives
Objective 1: Characterize the molecular and physiological mechanisms governing crop response to heat and drought, including interactions, to use the information to identify and verify new genes and molecular markers useful for plant breeding.
Sub-objective 1A: Characterize the physiological and genetic mechanisms governing
wax content and composition and heat shock proteins in cotton, under heat and
drought conditions.
Sub-objective 1B: Characterize the physiological and genetic mechanisms governing
wax content and composition and aquaporins in oilseeds, under heat and drought
conditions.
Objective 2: Develop and validate field-based, high-throughput phenotyping strategies for rapid assessment of crop responses to heat and drought, including evaluation and validation of sensors, proximal sensing vehicles, and methods of data capture, storage, analysis, and interpretations.
Sub-objective 2A: Develop and deploy novel sensing platforms, sensor calibration
devices, and sensor validation protocols for field-based high-throughput
phenotyping.
Sub-objective 2B: Develop a database that can be queried, and a geospatial data processing pipeline for proximal sensing and imaging data collected from terrestrial platforms for field-based high-throughput phenotyping.
Objective 3: Characterize the molecular mechanisms of oil accumulation in agriculturally important plants under various inclement conditions, including heat and drought conditions, to identify and verify new genes and molecular markers to increase oil yields in both food and bioenergy crop plants.
Sub-objective 3A: Characterize the molecular and physiological mechanisms governing
seed number, size, and weight for oilseeds and biofuel crops in response to heat and
drought stress conditions.
Sub-objective 3B: Characterize the function of lipid droplet-associated proteins (LDAPs) and identify new genes involved in abiotic stress responses and oil production pathways in plants.
Sub-objective 3C: Use transgenic and gene-editing approaches to increase oil content and abiotic stress tolerance in crop plants.
Approach
A variety of experimental approaches including phenomics and associated “big data” management, field studies of cotton and camelina, genomics, and the molecular and biochemical studies of the model plant Arabidopsis, as well as camelina, Brassica napus, and cotton are involved.
Objective 1: To characterize the physiological and genetic mechanisms governing crop response to heat and drought, cotton and Brassica napus plants will be examined for genetic variability of these traits using conventional and high-throughput phenotyping approaches to determine canopy temperature, cuticular wax content and composition, and leaf chlorophyll content. A transcriptomics approach will be used to determine if known genes involved in wax or chlorophyll biosynthesis are underpinning the observed phenotypes, and ribonucleic acid (RNA) sequencing will be conducted with either PacBio or Illumina HiSeq technology.
Objective 2: To develop and validate field-based high-throughput phenotyping (FBHTP) strategies for assessment of crop responses to heat and drought, novel platforms and sensor arrays, including carts, small robots and imagery, will be tested in cotton fields grown under high heat or drought stress. The FB-HTP collected traits will be assessed for accuracy and consistency using in-field calibration targets and ground truthing measurements. Semi-automated pipelines and databases will be developed to process and manage the data for statistical analysis of crop response to the environmental conditions.
Objective 3: To characterize the molecular and physiological mechanisms governing seed development and lipid-droplet-associated proteins (LDAPs) in biofuel crops, candidate gene-based and transgenic approaches will be used to examine the model system Arabidopsis and camelina. Gene function will be characterized using a combination of forward and reverse genetic approaches, coupled with cellular and biochemical studies of protein activity. Oil production in response to abiotic stress tolerance will be studied by examining the function of LDAPs and other lipidrelated proteins in leaves and seeds of plants. Transgenic approaches will be used to increase oil content and abiotic stress tolerance in camelina.
Progress Report
This is the final report for the expiring bridge project 2020-21000-014-000D, Molecular Genetic and Proximal Sensing Analyses of Abiotic Stress Response and Oil Production Pathways in Cotton, Oilseeds, and Other Industrial and Biofuel Crops, which will be replaced by a new bridging project 2020-21000-015-000D, with the same title. The OSQR Ad Hoc review for an updated project was delayed due to project vacancies and uncertainty. The following progress was achieved under Objective 1.
Fieldwork was conducted in Maricopa, Arizona, where ARS researchers are studying crop variety responses to reduced soil moisture in high-temperature environments. Due to personnel limitations, efforts were focused on physiological data collection at peak flowering and post-harvest traits. Soybean varieties and commercial cotton varieties were planted, with soybean exposed to three irrigation treatments and cotton to four irrigation treatments. At peak flowering (around 60 days for soybean and 75 days for cotton), researchers gathered physiological data to better understand how photosynthesis was impacted by the irrigation treatments. Researchers also assessed irrigation treatment impacts with post-harvest traits. Field experiments are ongoing, and data analysis is awaiting the final year of data collections.
ARS researchers in Maricopa, Arizona, developed an artificial intelligence model to predict seed traits using hyperspectral images of crop seeds. The project has entered the final testing phase, refining predictive capabilities for enhanced accuracy and reliability. A manuscript detailing the hyperspectral imaging methods and python code to generate the predictive model is currently being drafted. Work has begun to acquire hyperspectral data from seed of a cotton mapping population, focusing on extracting seed size metrics that can be linked to genetic markers.
ARS researchers quantified plant pigments from soybean samples cultivated in Missouri and Arizona. ARS scientists in Maricopa, Arizona, have completed analyses using an updated quantification method, and data analysis is currently in progress to evaluate each variety’s ability to sustain pigment levels.
Finally, ARS researchers have begun assembling and cultivating cotton variety panels in Maricopa, Arizona. These panels include a wide-ranging collection of cotton cultivars, wild accessions, and landraces, serving as a key resource for genome-wide association studies. Initial selections were planted and harvested in FY24. Plantings in FY25 further increase seed for these varieties and additional selections will be made.
Accomplishments
Review Publications
Thompson, A.L., Thorp, K.R., Herritt, M.T. 2025. Identifying seed cotton yield and abiotic stress response in cotton (Gossypium hirsutum L.) grown in the Arizona low desert. Crop Science. 65(2). Article e70058. https://doi.org/10.1002/csc2.70058.
Thorp, K.R., Thompson, A.L., Herritt, M.T. 2024. Phenotyping cotton leaf chlorophyll via in situ hyperspectral reflectance sensing, spectral vegetation indices, and machine learning. Frontiers in Plant Science. https://doi.org/10.3389/fpls.2024.1495593.