Greenhouse optical learning framework for enhanced crop monitoring
GOLF utilizes low-cost 3D multispectral cameras mounted on greenhouse equipment to create high-fidelity digital twins of cropping areas. This integrated platform offers real-time monitoring, accelerating resource efficiency and stress detection in field trials.
Overview
The Greenhouse Optical Learning Framework (GOLF) is an innovative solution leveraging Fotenix's 3D multispectral camera systems to enhance crop monitoring in greenhouses. By mounting these affordable cameras on existing harvest and spray trolleys, GOLF creates high-fidelity digital twins of cropping areas. This allows for cost-effective, real-time monitoring and rapid stress detection, significantly improving resource efficiency in agricultural trials. The platform's unmatched spatial resolution enables the early detection of biotic and abiotic stresses, accelerating the development and deployment of new crop varieties.
Technical specifications
Key features:
- Utilizes 3D multispectral cameras capturing ultraviolet, visible, and near-infrared light
- Provides high signal-to-noise, non-destructive, automated crop monitoring
- Capable of mounting on static or moving greenhouse equipment for flexible deployment
- Offers spatial resolution of less than 30 micrometers per pixel
- Supports hardware provision, software access, and technical support with API integration for seamless data management
Technology readiness level
The technology is currently at TRL 5, indicating it has been validated in relevant environments. Future validation plans include comprehensive greenhouse trials to further demonstrate the platform's efficacy and integration potential.
About FOTENIX
Fotenix is an agri-tech company that provides AI-driven crop monitoring and analytical solutions designed to improve farm profitability and sustainability. The company’s core technology utilizes three-dimensional multispectral imaging and machine learning to analyze crop health, enabling early detection of pest and disease outbreaks, nutrient deficiencies, and plant stress. By integrating this non-destructive imaging hardware with a cloud-based platform, Fotenix allows growers to transition from reactive management to precise, data-driven interventions. The system is designed to be easily installed and integrated into existing agricultural workflows, supporting applications such as automated quality control, crop scouting, and smart resource targeting for machinery like sprayers and harvesters.
These tools address critical challenges in modern agriculture, including labor shortages for manual monitoring, high operational costs, and the need to reduce chemical inputs. By providing actionable insights that improve resource efficiency and quality, Fotenix helps farmers increase productivity while minimizing environmental impact. Founded in 2018 as a University of Manchester spinout, the company has partnered with various agricultural organizations and research centers to scale its operations. It has secured support through government grants, venture capital, and industry-led programs to advance its product development and expand its presence in the horticulture and plant breeding markets.
delivered to your inbox.