Virginia Tech project selected for national AgriProspects workforce development award
AI-powered training tools help loggers practice complex bucking decisions before entering the field.
Hardwood forests are a cornerstone of Virginia’s rural economy, yet one of its most critical operational decisions, log bucking, remains under-supported in workforce training.
A step toward supporting that training comes from a grant of $200,000 from the AgriProspects Workforce Development Network will help be used by Virginia Tech to provide artificial intelligenceAI-based training tools for loggers.
Known as bucking, the process determines how a tree stem is segmented into logs, directly influencing product grade, marketability, and financial return. These decisions require complex judgments that balance species, defects, grade, and shifting market conditions, often under time pressure and physical constraints.
Despite its complexity and economic impact, loggers often have no formal training related to bucking decisions. Current training methods rely heavily on static classroom instruction and limited field demonstrations that offer little opportunity for loggers to practice real-time decision-making or receive feedback on value recovery outcomes.
This initiative, led by Pipiet Larasatie, a Virginia Cooperative Extension specialist and assistant professor in the Department of Sustainable Biomaterials, is titled Logging Smarter: AI-Enhanced Hardwood Bucking Training for Adult Workforce Development. This gives the university and its partners in Extension a scalable way to strengthen rural labor pipelines and modernize one of the state’s foundational industries.
Larasatie’s project will apply artificial intelligence, computer vision, and image generation to create interactive training modules that simulate the complexity of real field conditions. These tools are designed to help trainees evaluate different cutting choices, understand their economic impacts, and strengthen their decision-making skills. The project will be integrated into the SHARP Logger Program, which provides continuing education for logging professionals in Virginia.
The proposal was developed with assistance from Brian Bond, a professor and associate dean for Extension, Outreach, and Engagement in the College of Natural Resources and Environment, and Associate Professor Scott Barrett, both of whom also serve as Extension specialists. Additionally, Chris Thomas, an assistant professor with Virginia Tech’s Sanghani Center for Artificial Intelligence and Data Analytics will manage part of the project.
This work represents an early, collaborative initiative of the newly established Sustainable Forest Supply Chain Collaborative, laying the groundwork for integrated research and Extension activities and technology‑enabled solutions across forest supply chains.
Traditional training emphasizes safety and compliance but lacks tools for developing the strategic thinking needed for optimal bucking, particularly regarding timeliness and variety of decision making that can be covered during allowed training time. This project will address cognitive skill development in high-stakes decisions gap in adult agricultural and forestry workforce development.
By modernizing the learning environment with digital tools, the project aims to support workforce readiness in rural communities where forestry plays a central economic role. While developed with Virginia’s hardwood sector in mind, the interactive training system is intended to be adaptable to logging operations in other regions. The project will also produce open-source resources that can be scaled beyond the state.
