Field-scale digital twin platform for maize trait development using 3D multispectral imaging
Develop a cost-effective digital twin platform that uses 3D multispectral cameras for high-resolution field monitoring in maize trait development. The system supports real-time in-field diagnostics to improve efficiency in crop trials and enables integration of high-fidelity monitoring data via a custom API for downstream analysis workflows.
Overview
A digital twin platform for maize trait development that delivers laboratory-grade resolution and quality at field scale. The solution uses cost-effective 3D multispectral camera systems mounted on ATV booms to perform high-fidelity monitoring of cropping areas. The approach is intended to improve trial efficiency by delivering precise, comprehensive field data through a custom API, supporting trait exploration and resource allocation.
Technical specifications
Key features:
- Utilizes 3D multispectral cameras combining ultraviolet, visible, and near-infrared light for detailed crop analysis
- Capable of non-destructive, automated monitoring with high signal-to-noise ratios
- Flexible mounting options on static or mobile equipment such as gantries or ATV booms
- Provides real-time diagnostic coverage to identify biotic and abiotic stress hotspots
- Custom API ensures data compatibility with downstream analysis formats
Technology readiness level
The platform is currently at Technology Readiness Level 6, indicating validation in relevant environments and ongoing trials and data collection. The project includes a structured validation plan covering manufacturing, setup, calibration, and data collection phases to ensure system precision and efficacy.
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.
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