Four Programs of Excellence funded through the Water Exceptional Item

The new biennium of funding for the Research, Engineering and Extension: Development of Water Programs of Excellence, also called the Water Exceptional Item, has kicked off. Each submission went through a panel review process, and four projects were selected by Texas A&M AgriLife Research, Texas A&M AgriLife Extension Service and Texas A&M Engineering Experiment Station (TEES).

The Water Exceptional Item is funded by state appropriations from U.S. Congress to AgriLife Research and is administered by the Texas Water Resources Institute (TWRI). Through this funding, the three Texas A&M University System agencies have provided $1,796,308 in funding for 24 months across fiscal years 2022 and 2023.

Each project team was required to be multidisciplinary, including at least one representative from each of the three agencies. These projects are expected to lead to forward-thinking water research and extension activities and should position teams to successfully secure large, competitive, extramural resources.

“The purpose of this initiative was to invest in multidisciplinary teams, or Programs of Excellence, to assist in positioning teams to be leaders in emerging fields and successfully secure the extramural resources that advance water management in Texas,” said Allen Berthold, Ph.D., TWRI associate director, who administers the exceptional item.

Priority areas included data science sustaining water management, increasing the value of water to support agricultural production and increasing economic and social water resilience in urban and/or rural communities.

These projects began September 1, 2021, and each team has coordinated and begun their efforts. The following information highlights the research areas and goals of each project according to the abstract submitted in their application.

Remote sensing and crop modeling models for crop production with limited water supplies

This project is led by Juan Enciso, Ph.D., principal investigator, with Jaehak Jeong, Ph.D., and Girisha Ganjegunte, Ph.D., of AgriLife Research; Samuel D. Zapata, Ph.D., of AgriLife Extension; Shuiwang Ji, Ph.D., of TEES; and Nithya Rajan, Ph.D., and Robert Hardin, Ph.D., of Texas A&M.

The team proposed to develop a yield-predicative analytic system using computation simulation models combined with remote sensing tools to potentially pave the way for making more marginal quality water available for crop production to improve farm profitability.

Multiple planting locations will be included, using various water quality sources, amounts and tools to manage and forecast productivities per unit of water.

Key innovations expected are 1) accurate estimation of crop yield using unmanned aerial systems (UAS) imagery, 2) a custom neural network algorithm to process UAS spatially distributed derived phenotypic traits, 3) accurately forecast yield with crop modeling and UAS derived data as inputs, and 4) coupling yield estimation algorithms and forecasting UAS models into a crop yield prediction and simulation tool.

The team’s central hypothesis is that the combined biomass simulation models and remote sensing tools can be used to improve management strategies for using saline water and deficit irrigation strategies.

The relevance of developing these tools is that they will conserve freshwater resources, improve the management of limited and saline water supplies, and enhance the sustainability of U.S. agriculture and food systems.

Photocatalytic degradation of per- and polyfluoroalkyl substances (PFAS) in water by two novel visible-light responsive photocatalysts

This project is led by Xingmao Ma, Ph.D., principal investigator, of TEES; Anish Jantrania, Ph.D., of AgriLife Extension; and June Wolfe, Ph.D., of AgriLife Extension. Collaborators are Vierender K. Sharma, Ph.D., of the Texas A&M School of Public Health, and Hongcai (Joe) Zhou, Ph.D., of the Texas A&M Department of Chemistry.

This team proposed to investigate the efficacy of two highly robust and visible light sensitive photocatalysts for their removal of PFAS.

Objectives of the project include 1) investigating the removal efficiency of a range of historic and emerging PFAS by these two photocatalysts separately and in combination; 2) determining the effect of various natural water constituents on the effectiveness of these two photocatalysts; and 3) demonstrating the efficiency of photocatalytic treatment in a pilot study.

Because photocatalysis has been widely applied in water treatment as a sustainable and economic treatment technology, the technologies explored in this study can be readily transferred to the field scale.

This project is anticipated to provide a novel, effective and economically viable solution to remove PFAS from water by demonstrating the efficacy of two novel photocatalysts.

Development of a UAS-based system to improve water use efficiency of cotton by monitoring crop water use and biomass accumulation

This project is led by Murilo Maeda, Ph.D., principal investigator, of AgriLife Extension; Nick Duffield, Ph.D., of TEES; and Mahendra Bhandari, Ph.D., Craig Bednarz, Ph.D., and Juan Landivar, Ph.D., of AgriLife Research. Collaborators are Paxton Payton, Ph.D., and James Mahan, Ph.D., of the U.S. Department of Agriculture’s Agricultural Research Service; Anjin Chang, Ph.D., of Texas A&M Corpus Christi; and Jian Tao, Ph.D., of TEES.

The team proposed to develop a UAS-based crop monitoring system that calculates crop water use for irrigation scheduling and increased water use efficiency. To do this, the team’s system will take the advantage of big data analytics and artificial intelligence (AI) on the UAS-derived phenotypic data and infield weather data to calculate actual crop evapotranspiration and biomass accumulation and determine the timing and quantity of irrigation water needed.

A field study will be conducted in 2022 and 2023 in Lubbock and Bushland, Texas where the team will measure crop water use, biomass accumulation and a suite of drone-derived crop data to determine the empirical relationships needed for the UAS-based system to operate.

Simple, reliable and scalable-on-demand remediation of emerging contaminants in water

This project is led by Sreeram Vaddiraju, Ph.D., principal investigator, of TEES; Terry Gentry, Ph.D., of AgriLife Research; and Juan Anciso, Ph.D., of AgriLife Extension.

The project team plans to build upon their prior work in photocatalytic water disinfection to completely revamp the way it is currently implemented.

The team plans to develop easily recoverable, regeneratable and reusable photocatalyst foams and photocatalyst foam-ultraviolet (UV) LED hybrids to both enhance the kinetics of the water treatment process and make the process easily scalable on demand. These photocatalyst foams and photocatalyst foam-UV LED hybrids could be added to either existing UV treatment facilities for the photocatalytic treatment of water or could be added to water stored in reservoirs or other open areas to provide for residual treatment of water (using sunlight for activation).

The proposed process improvements also aid in building small-scale disinfection systems at point-of-sale by supermarkets for removal of harmful bacteria from produce and prevent expensive food recalls.

The team plans to generate preliminary results for this high-risk and high-payoff strategy using these funds and to reduce any perceived risk associated with seeking extramural funding for further research and development of photocatalysis.

“We are excited about each of these projects and have high expectations for positive outcomes that will help in advancing water management in Texas,” Berthold said.

Authors

As a grant administrator for TWRI, Danielle Kalisek manages proposal and budget development and facilitates the submission process, serving as a liaison between the institutes and Texas A&M’s Sponsored Research Services.

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