Novel Energy Efficient UVC Autonomous Robotics Platform for Sustainable Strawberry Fungal Management

Project Overview

Project Type: Graduate Student
Funds awarded in 2022: $16,496.00
Projected End Date: 08/31/2024
Grant Recipient: Middle Tennessee State University
Region: Southern
State: Tennessee
Graduate Student:
Major Professor:
hongbo zhang
Middle Tennessee State University


  • Fruits: berries (strawberries)


  • Pest Management: integrated pest management, physical control, robotics, technology

    Proposal abstract:

    The objective of the research is to build an energy-efficient autonomous UVC robotics platform for strawberry fungal management.  The proposed autonomous robotics platform is expected to enable non-chemical fungal treatment thus sustainable organic strawberry farming. Crucially, our research will address the critical challenges faced by strawberry growers when using UVC for fungal management.

    The major challenge of the conventional UVC solution is the low energy efficiency thus poor affordability for strawberry farmers. We will use UVC LED known 95% more energy efficient than the UVC lamp to improve the energy efficiency of the system [1]. We will further optimize the distance between the UVC LED and strawberry plant to increase energy efficiency. Our research proposes a smart LED light intensity computation method to precisely control its individual UVC LED for smart energy-efficient fungal management. 

    Another major challenge of the conventional UVC fungal treatment solution is UVC safety. UVC poses significant radiation risks to human skin and eyes. Our research proposes a smart grower detection method thus to protect growers from harmful UVC radiation to improve the adoption of the technology.

    The autonomous robotics platform is affordable to strawberry growers, especially for socially disadvantaged farmers. The user-friendliness features of the platform enable socially disadvantaged farmers to use the platform for organic strawberry fungal management.

    Project objectives from proposal:

    Goal 1: Energy-efficient UVC Platform Development. Novel high throughput close proximity UVC source will be developed for effective fungal management. With the solution, the energy-efficient UVC LED will be used, which is 80 - 95% more energy efficient than the UVC lamp [1]. Furthermore, we will also shorten the distance between the light source and the plant to increase energy efficiency. In contrast to the UVC lamp, the UVC LED source is miniature in size therefore it is able to be used in close proximity to the plant. The intensity of each individual LED will also be controlled based on the severeness of fungal for precise control of fungal diseases.

    Goal  2: Smart Fungal Recognition and Analysis Pipeline Development.  The importance of big data and artificial intelligence in sustainable agriculture has been well demonstrated [23, 24]. For this, we will build a smart data analysis pipeline for autonomous fungal disease recognition in order to precisely deliver UVC radiation to each individual plant. Specifically, modern deep learning computer vision algorithms will be built for the precise detection of fungal diseases to determine the needed dose for the treatment of fungal diseases. We will also develop a user-friendly GUI application for reporting the results of the UVC fungal treatment.

    Goal 3: Affordable and Safe Robotics Platform Development. In particular, we will build an affordable robotics platform for small to medium-sized farms and socially disadvantaged farmers to enable them to better implement sustainable strawberry fungal control. The proposed platform will cost about 5,000$, making it affordable to the majority of strawberry growers. The autonomous robotics platform will make the UVC handling safe for strawberry growers. The UVC chamber will be equipped with infrared cameras to detect the presence of growers. Human detection computer vision algorithms will be developed to detect growers with high accuracy. The UVC light will be automatically turned off upon the detection of the growers close to the UVC chamber to ensure UVC safety.

    Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.