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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Sustainable Agricultural Systems Laboratory » Research » Research Project #444954

Research Project: Developing, Evaluating, and Optimizing Diversified Agricultural Systems for a Changing Environment in the Mid-Atlantic Region

Location: Sustainable Agricultural Systems Laboratory

Project Number: 8042-21600-002-000-D
Project Type: In-House Appropriated

Start Date: Aug 15, 2024
End Date: Aug 14, 2029

Objective 1: Improve quantification and accounting of fundamental ecosystem services delivered by diversified long-term grain and forage cropping systems, both organic and conventional, and explore mechanisms influencing ecosystem service provisioning. Sub-objective 1.A: Compare factors controlling crop performance in long-term organic and conventional cropping systems. Sub-objective 1.B: Evaluate soil function and ecosystem services in long-term organic and conventional cropping systems. Sub-objective 1.C: Quantify the impacts of cropping systems on geospatial distributions of soil microbial communities. Sub-objective 1.D Conduct integrated analyses to assess the impacts of cropping systems diversity on system performance and the provision of ecosystem services. Sub-objective 1.E. Test, validate, and parameterize MAIZSIM, GLYCIM, and anticipated wheat and rye CC models using long-term FSP datasets. Sub-objective 1.F: Compare factors controlling crop performance in long-term cover-crop based no-till systems. Objective 2: Develop new technologies and management strategies that improve system productivity, and resilience to changing climate and other system disruptions, and food safety and nutrition of diverse cropping and soilless systems. Sub-objective 2.A. Screen and improve grass and legume CCs for higher biomass, winter hardiness, soft seed, disease resistance, and allelopathy. Sub-objective 2.B. Aggregate data from a national on-farm research network to calibrate and validate a regional CC nitrogen calculator (CC-NCALC). Sub-objective 2.C. Improve CC performance mapping with multi-spectral and hyperspectral imagery. Sub-objective 2.D. Use a high-resolution, open-access plant image repository for CCs to train low-cost sensors for real-time, high-resolution mapping of CC species, quality, and biomass. Sub-objective 2.E. Construct web-based decision support tools that inform species selection, seeding rate recommendations, and economic assessments that are national in scope but site-specific in the application for CC management and the other 59 NRCS vegetation conservation management practices. Objective 3: Develop new technologies and management strategies that improve system productivity, food safety, and nutrition of soilless systems, and explore the microbial degradation of per- and polyfluoroalkyl substances (PFAS). Sub-objective 3.A. Develop validated methods to assess the presence of pathogens in recirculating hydroponic (HP) and aquaponic (AP) systems and the produce. Sub-objective 3.B. Determine the efficacy of physical and biological treatment technologies on pathogen control in HP and AP systems. Sub-objective 3.C. Screen and identify microorganisms and environments that enhance the degradation and reduce the half-life of per- and polyfluoroalkyl substances (PFAS).

Approaches to developing, evaluating, and optimizing diversified agricultural systems under Objective 1 include measuring crop yield, soil moisture, and carbon and nutrient dynamics at three Beltsville long-term field research projects: the Farming Systems Project, the Cover Crop Systems Project and the LTAR Lower Chesapeake Bay Cropland Common Experiment. In addition, efforts at FSP will also include measuring weed population dynamics, soil carbon fractions, greenhouse gas fluxes, soil microbiological community structure and function, and soybean nitrogen fixation, and conducting integrated analyses to evaluate overall systems performance. FSP data will also be used to test MAIZSIM and other crop growth models and will be used in long-term cross-location network analyses. Approaches under Objective 2 include 1) breeding and selecting cover crop varieties of hairy vetch, winter pea, crimson clover, and cereal rye through traditional, participatory, and marker-assisted methods; 2) calibrating the cover crop nitrogen calculator (CC-NCALC) for the Eastern US; 3) using multi-spectral imagery from satellites, combined with climate variables and plant growth models, to accurately estimate cover crop shoot biomass in the field; 4) collecting laboratory-based hyperspectral data to identify spectral regions most sensitive to cover crop characteristics and then examine how cover crop termination methods influence these spectral characteristics; and 5) constructing and publicly releasing, with NRCS, the Vegetation Planning Tool. Approaches under Objective 3 include 1) collecting samples from commercial and research-based aquaponics and hydroponics systems: water from all compartments, plant roots, and biofilter solids and analyzing samples for generic E. coli, Listeria spp., aerobic plate counts, microbiomes, and standard water quality parameters; 2) conducting inoculated challenge studies with phytopathogens and surrogate bacterial contaminants in non-commercial research aquaponics and hydroponics systems; 3) measuring pathogen control using nanobubble, plasma-activated water, UV light, and biocontrols separately or in combinations in recirculating aquaponics and hydroponics systems; and 4) identifying microorganisms and environments that enhance the degradation and reduce the half-life of PFAS.