Growth data and production systems for container-grown trees

Problem

Container cultivation promises what field-grown nursery stock never could: trees of predictable size, root systems that survive transplanting, and planting in any season. It also produces a stream of data that most operations throw away. Growth measurements, irrigation, substrate, temperature, and light are noted on paper, if at all, and the knowledge of what worked stays in the head of whoever was on shift.

Approach

The system described in registered patent KR 10-2273721 puts that stream into an ERP. It records growth and environmental data for container-grown landscape trees, predicts growth with deep-learning or machine-learning models, analyzes the production environment, and recommends conditions for optimal production. The by-product is what the industry lacks most: a standardized, data-based database of landscape trees.

Status

The system was built in 2021 for a grower’s operation and is registered with the Korean Intellectual Property Office. The research question we keep at Alpha Lab is one of parsimony: what is the smallest set of measurements that predicts growth well enough to schedule production?