USDA · USDA-117 · record R1415

Vegetation Specifications Suite (VegSpec)

Department of Agriculture · Farm Production and Conservation

Overview

Development stage: PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2024-12-31 (day precision)Source: 12/31/2024
Withheld from public reporting: Not reported

Mission

Topic area: Service Delivery
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Consistent technical expertise is lacking in the development of conservation practices for producers that need to implement emergency and disaster assistance conservation programs, as well as other voluntary conservation programs

Expected benefits

Empowers producers to make informed decisions on plant materials used in their operations for conservation, disaster recovery, or production purposes. Consistent and tailored specifications with cost estimations.

System outputs

Reports generating seed mixes, bare root specifications, recommendations, and estimated costs for projects.

Technology

AI classification: Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s): Vegetation Specification Suite (VegSpec)
Custom-developed code: Yes
Public source code: Not reported

Sourcing

How it was built: Contract and in-houseSource: c) Developed with both contracting and in-house resources
Vendor (as reported): Precision Sustainable Agriculture Group, North Carolina State University
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: vegspec.org ↗
Authorization to Operate: Yes
Demographic features: k) None of the above
Training and evaluation data: Datasets are developed using publicly available technical materials from, Soil Survey Geographic Database (SSURGO), National Soil Information System (NASIS), Plant List of Attributes, Names, Taxonomy, and Symbols (PLANTS), Major Land Resource Assessment (MLRAs) areas National Resources Conservation Service (NRCS) plant materials centers and NRCS state resources
Federal Data Catalog: websoilsurvey.nrcs.usda.gov ↗

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported