Objective 1. Use national collections of germplasm to identify, characterize, and exploit superior physiological traits that enhance stress tolerance and increase yield in row crops, such as cotton, maize, peanut, and sorghum, to optimize crop production strategies in water-limited management systems. • Sub-objective 1A: Evaluate a previously selected, diverse core-collection of cotton lines from the USDA germplasm collection and map developed populations for yield and fiber quality under mid- and late-season water-deficit stress and/or disease pressure. • Sub-objective 1B: Identify cotton and peanut germplasm with physiological and morphological traits important to stress tolerance and stress acclimation. • Sub-objective 1C: Characterize agro-morphological and physiological traits controlling water-deficit stress tolerance in diverse grain sorghum germplasm collections to broaden the genetic donor sources for sorghum breeding. • Sub-objective 1D: Characterize genotypic plasticity and identify genetic components of heat tolerance in maize and sorghum. • Sub-objective 1E: Isolation and genetic characterization of sorghum mutants with altered heat tolerance for major traits. Mapping and cloning the causal mutation in sorghum hs mutants and functional characterization of identified genes. • Sub-objective 1F: Physiological characterization of maize core lines for their diversity in heat stress responses. Dissection of cellular and physiological mechanisms in heat stress response in maize. (Chen) Objective 2. Develop and implement crop management systems that are most appropriate for exploiting the uniqueness or strengths of superior new varieties combined with diverse regional production practices. • Sub-objective 2A: Implementation of crop simulation models to explore the GxExM interactions in rainfed cotton and sorghum production systems. • Sub-objective 2B: Evaluation of new genetic sources of cold temperature tolerance in and development of new production schemes from planting date and in-season management to expand current season lengths and regional boundaries for sorghum production. Objective 3. Determine variability in plant environmental stress responses, and exploit the diversity by designing and evaluating genotype-specific production schemes that include assessments of environmental limitations and management interactions. • Sub-objective 3A: Advance new high-throughput, thermographic technologies for estimation of plant responses to abiotic stresses under relevant production conditions in the field. • Sub-Objective 3B: Utilize existing gene mapping technologies/tools to identify and develop new single nucleotide polymorphism markers, biomarker-trait associations, and functional genes associated with tolerance and susceptibility to abiotic and biotic stress.
Unpredictable weather patterns and insect and disease pressures continually threaten yields and quality of virtually all cropping systems. These threats, coupled with accelerating global declines in water available for irrigation and increasing reliance on production from marginal lands present substantial obstacles to achieving the goal of the ARS Grand Challenge to deliver a 20% increase in quality production at 20% lower environmental impact by 2025. The long-term goals of this research are to improve understanding of plant resilience to biotic and abiotic stresses and to develop stress-tolerant cultivars that can be used in existing and future cropping systems. The elucidation of how biological mechanisms control plant stress responses and how the environment, both natural and managed, defines and restricts crop productivity, provide the foundation for the ability to improve agricultural production in low-input systems. Significant changes in management strategies, improved selection methods, and improved germplasm will be required to meet future production demands. Genetic improvements will be derived from active, targeted selection of traits in diverse germplasm grown under relevant production scenarios. Investigations of the interactions among genetic resources, environments, and management systems provide a way to fit technologies from this research to various regional climatic zones. The proposed research is relevant to the NP 301 Action Plan, Component 1 - Crop Genetic Improvement: Problem Statement 1A, Trait discovery, analysis, and superior breeding methods and 1B, New crops, new varieties, and enhanced germplasm with superior traits; Component 2 - Plant and microbial genetic resource and information management: Problem Statement 2A, Plant and microbial genetic resource and information management; Component 3 - Crop Biological and Molecular Processes: Problem Statement 3A: Fundamental knowledge of plant biological and molecular processes; and Component 4 - Information resources and tools for crop genetics, genomics, and genetic improvement: Problem Statement 4A, Information resources and tools for crop genetics, genomics, and genetic improvement.
Objective 1. Sub-objective 1A. Objective 3. Sub-objective 3C. A replicated deficit irrigation trial (2 irrigation levels) with 110 recombinant inbred lines (RILs) derived from a cross between cultivars Alcala NemX and Acala SJ-2 was planted at ARS Lubbock, Texas, and is currently being evaluated for growth and phenology. In addition, 14 improved advanced breeding lines derived from a cross between Phytogen 72 x NM67 and Phytogen 72 x Stoneville 474 were sent to breeders and planted in South Carolina, Louisiana, and West Texas to further test and validate yield and fiber quality traits for the possibility of public germplasm release. For disease evaluations, 140 Upland entries deposited in the USDA-ARS cotton collection and approximately 300 Upland breeding lines developed from a diverse series of cross-combinations were planted in infested Fusarium wilt race 4 (FOV4) fields in California and Texas. These entries are currently being evaluated for FOV4 tolerance/resistance and yield. Roots of two Upland (PSSJ-U77 – resistant/tolerant to FOV4 and Stoneville 474 – susceptible to FOV4) and two Pima (Pima-S6 resistant/tolerant to FOV4 and Pima-S7 susceptible to FOV4) entries were collected for proteomic analysis and root cell wall assays to examine disease resistance and drought tolerance biomarkers. Cellulose and lignin analysis are planned to determine whether these factors play a potential role in FOV resistance during pathogen infection. Objective 1. Sub-objectives C-E. Field evaluation of heat and water-deficit stress tolerance for maize and sorghum was carried out at Lubbock, Texas. Phenotyping and yield trial experiment was planted in Cropping Year 2020 and is currently being evaluated for leaf and reproductive tissue response to naturally occurring heat waves events. Targeted sorghum mutant populations were sown as part of the phenotyping and yield trial and are currently being evaluated for heat stress response to identify mutant plants with altered heat tolerance traits in leaf and panicle tissues. The seed-producing sorghum mutants identified will be harvested at the end of the growing season and verified for specific phenotypes in greenhouse in fiscal year (FY) 2021. Phenotyping data has been collected by an unmanned aerial system (UAS) and will be analyzed with yield and biomass data at the conclusion of the growing season. Objective 2. Sub-objective 2A-C. A long-term rainfed planting date (8 sowing dates across 5 months) trial was sown for the 6th consecutive growing season. The first 2 plantings were destroyed by hail but data on emergence rate and stand counts were collected. Currently, 6 planting date entries are being analyzed for growth and phenology by UAS. Additionally, and early season planting date experiment was sown to screen sorghum genotypes for cold temperature tolerance and early season seedling vigor. We have continued to develop a UAS data analytics pipeline, in collaboration with Australian partners. We have modified the OZCOT cotton growth simulation model for rainfed production systems. A user-friendly front end was developed in a Jupyter notebook framework. The results of the initial simulations are being compared to historic performance dataset for rainfed and irrigated cotton in Lubbock, Texas. Questions relating to the ability of producers to reduce yield and quality losses related to harvest and processing methodology are being addressed in terms of a “End-of-Season Value Capture Framework”. This work involves both USDA/ARS and scientists in the areas of crop physiology and fiber quality. The implementation of a canopy temperature-based irrigation management system by an Australian agricultural management company (Goanna Ag) is underway on a 50,000 acre (13 growers) irrigation district in Oklahoma.
1. Release of upland cotton varieties with improved disease resistance. Identification of 45 Upland cotton varieties as genetic sources of FOV4 tolerance and release of current data on breeding efforts for Fusarium wilt race 4 (FOV4) resistance in Upland cotton. FOV4 is an emerging problem in Upland production regions in Texas and threatens both yield and certified seed production. Scientists in Lubbock, Texas, released a comprehensive data set containing information about the FOV4 breeding efforts in Texas with critical information on selection and the germplasm entries used for FOV4 testing and pedigree information, developed progeny and breeding lines. Findings in this research already have been confirmed/validated by other groups. With the findings from this effort and findings from other groups, the vulnerability of the Upland cotton crop in the U.S. is reduced. The next step is to publicly release germplasm lines from this research.
Marla, S., Burow, G.B., Chopra, R., Hayes, C.M., Olatoye, M., Felderhoff, T., Hu, Z., Raymundo, R., Perumal, R., Morris, G. 2019. Genetic architecture of chilling tolerance in sorghum dissected with a nested association mapping population. G3, Genes/Genomes/Genetics. 9:4045-4057. https://doi.org/10.1101/622894.
Ulloa, M., De Santiago, L., Hulse-Kemp, A.M., Stellly, D.M., Burke, J.J. 2019. Enhancing upland cotton for drought resilience, productivity and fiber quality: Comparative evaluations and genetic dissection. Molecular Genetics and Genomics. 295(1):155-176. https://doi.org/10.1007/s00438-019-01611-6.
Naoura, G., Nerbewende, S., Atchozou, E., Emendack, Y., Hassan, M., Echevarria Laza, H.J., Tabo, R. 2019. Assessment of agro-morphological variability of dry-season sorghum cultivars in Chad as novel sources of drought tolerance. Nature Scientific Reports. 9:19581. https://doi.org/10.1038/s41598-019-56192-6.
Dever, J., Ayele, A., Zwonitzer, J., Kelly, C., Payton, P.R., Jones, D. 2020. Registration of CA 4007 cotton germplasm line for water-limited environment. Journal of Plant Registrations. 14:49-56. https://doi.org/10.1002/plr2.20034.
Young, A., Mahan, J.R., Dodge, W.G., Payton, P.R. 2020. Blob-based AOMS: A method for the extraction of crop data from aerial images of cotton. Agriculture. 10(1):19. https://doi.org/10.3390/agriculture10010019.