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Platform for Multi-modal, Multi-scale Data Integration for Sustainable Agriculture

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-SC0020558
Agency Tracking Number: 249781
Amount: $200,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: 01a
Solicitation Number: DE-FOA-0002145
Solicitation Year: 2020
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-02-18
Award End Date (Contract End Date): 2020-11-17
Small Business Information
2750 Rasmussen Road Suite 201
Park City, UT 84098-6261
United States
DUNS: 081365875
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Nicola Falco
 (510) 486-4703
Business Contact
 John McEntire
Phone: (512) 426-4612
Research Institution
 Lawrence Berkeley National Laboratory
 Haruko Wainwright
1 Cyclotron Road
Berkeley, CA 94720-8099
United States

 (510) 495-2038
 Federally Funded R&D Center (FFRDC)

Technologies for terrestrial ecosystem management – in the area of precision agriculture and ecosystem restoration – have made significant advances recently for more sustainable practices by optimizing water, nutrients, and fertilizers Many of these technologies include monitoring and imaging of plants, soil, and crop harvest as well as their interactions, using in situ sensors, remote sensing, and geophysics Their development is mostly industry-driven focused on the local-scale information In parallel, there have been significant efforts by the US Department of Energy (DOE) to establish public databases for quantifying ecosystem functions in regional and national scales, including greenhouse gas (GHG) fluxes, evapotranspiration (ET), soil biogeochemistry, and microbial genomics through Ameriflux, KBase, and ESS- Dive, and soon the National Microbiome Data Collective (NMDC) The DOE’s databases and user facilities are powerful in such assessments – yet, they have been rarely used for ecosystem management In this project, we will develop an open, scalable software system for multi-scale, multi-modal data integration; focused on coupling local-scale datasets from managed ecosystems with DOE’s regional-scale datasets on GHG fluxes, plant genotypes, and soil microbiome (Ameriflux, KBase and ESS-Dive) We will evaluate the impact of local and regional-terrestrial heterogeneity based on different sensing technology, such as remote sensing for plant phenology, and geophysical sensors that capture the spatial heterogeneity of soil properties LBNL has extensive expertise characterizing soil-plant interactions and other terrestrial ecosystem properties across scales Arva has developed machine learning capabilities in integrating multi-modal data to investigate the relationships between soil-plant interactions and crop yield, funded in part by a prior DOE SBIR In Phase I, we will develop prototype software and demonstrate its utility through three tangible applications: (1) water management based on in-situ soil sensors, geophysics and UAV images coupled with the ET estimates derived by Ameriflux; (2) the evaluation of farm practices (tilling/no-tilling, water manipulation) on GHG fluxes (carbon, methane) in rice fields based on high-resolution imagery and Ameriflux; (3) the identification of soil biogeochemical properties and the link to soil functional types through Kbase and ESS-Dive

* Information listed above is at the time of submission. *

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