Leafcutter Bee Cocoon Preservation System
TNT Pollination seeks to develop a cost-effective and scalable solution for storing leafcutter bee cocoons under specific conditions to enhance their longevity. Based on a 2025 peer-reviewed study, (https://doi.org/10.1242/jeb.250500), maintaining cocoons in 10% oxygen and at 6°C significantly extends the bees' lifespan. The project aims to design a system capable of preserving up to 5,000 gallons of cocoons, equivalent to approximately 50 million bees, for agricultural use in the following year. This initiative will help reduce bee loss and waste, lower costs, and provide greater flexibility for pollinators. The project will involve researching existing storage technologies, designing a prototype storage system, and evaluating its feasibility for commercial implementation.
Smart Soil Moisture Sensing System for Deployment with Bee Shelters
TNT Pollination seeks to enhance agricultural productivity by developing a scalable, low-cost soil moisture sensing system. The project aims to equip each bee shelter, typically numbering 100 to 200 per field, with a durable sensor unit. These sensors will collect real-time geospatial moisture data, which will be visualized through a live dashboard. This data will aid agronomists and farmers in making informed irrigation decisions, ultimately improving field productivity. The system must integrate with farm management platforms like PollinLink via an open API, ensuring interoperability. Emphasis will be placed on ruggedness, power efficiency, and affordability to facilitate widespread deployment. The project offers learners the opportunity to apply knowledge in IoT, data visualization, and agricultural technology.
Innovative Leafcutter Bee Shelter Design
TNT Pollination is seeking a fresh design for a leafcutter bee shelter to enhance the efficiency and sustainability of their pollination services. The current shelters, while functional, lack certain features that could optimize bee health and productivity. The goal of this project is to create a new shelter design that allows for more automation of shelter placement and storage, facilitates data collection and improves bee overall health and performance. This project provides an opportunity for learners to apply their knowledge of environmental science, biology, and design principles. The team will design a new shelter based on criteria provided by TNT Pollination. The project aims to balance functionality with cost-effectiveness, ensuring the design can be easily implemented by TNT Pollination.
Leafcutter Bee Sorting Machine Design
TNT Pollination is seeking an innovative solution to enhance the efficiency of their leafcutter bee management process. The goal of this project is to design a machine that can effectively test and sort leafcutter bees based on specific criteria such as quality and purity. This machine will help streamline the process of preparing bees for pollination tasks, ensuring only the most suitable bees are utilized. The project will require learners to apply their knowledge of mechanical design, automation, and biology to create a prototype that meets the company's needs. Key considerations include the machine's accuracy, speed, and ease of use. The project will involve researching existing sorting technologies, designing a prototype, and testing its functionality.
Leafcutter Bee Pollination Data Analysis
TNT Pollination is seeking to enhance its understanding of leafcutter bee pollination patterns through a comprehensive data analysis project. The primary goal is to analyze existing datasets to identify trends, patterns, and potential areas for optimization in bee pollination. This project will allow learners to apply their statistical and data analysis skills to real-world agricultural data, providing insights that could improve pollination efficiency and crop yields. The analysis will focus on factors such as bee activity, environmental conditions, and plant health. By understanding these variables, TNT Pollination aims to refine its pollination strategies and support sustainable agricultural practices. The project will involve cleaning and organizing raw data, performing statistical analyses, and visualizing findings to communicate results effectively.