Suppliers of fresh produce need to make fast, significant, and complex decisions. There are many complexities in supply and production planning in fresh produce systems with many variables to consider for accurate forecasting of yield, including changing weather patterns.
Planning the supply of fresh produce to align with demand and market expectations is complicated, and with variable data can be costly in term of profitability. Variations in forecast yield can result in supply shortages or excess.
Australian green bean growers need to know when beans can be harvested and what is the likely yield. Managing green bean supply continuity is also important for enhancing brand reputation, value, and growth potential.
An accurate predictive growth model that can predict harvest timing, yield and quality will enhance production and sales throughout the entire business, ensuring customer satisfaction.
This research project used data science and real-world testing to create accurate predictive models that will help the green bean industry to meet market demand.
The project team created a dedicated green bean modelling tool for Mulgowie Farming Company by identifying and building on existing crop planting, yield, and location data.
The tool was then commercially tested and further refined throughout the 12 month hyper-care period.
The predictive model will help Mulgowie Farming Company and the green bean industry to make better production and sales decisions based on harvest timing, yield, and quality, while supporting marketing, promotion and pricing.
The collaborative nature and commercially focused and implemented outputs from this research demonstrates the potential for problem solving across other agricultural sectors and within individual business and business group
This initiative assists and enhances all aspects of the Mulgowie farming Companies production operations across all their Australian production and packing sites.
Innovation Manager, Food Agility CRC
Senior Horticulturist, Department of Agriculture and Fisheries Queensland
Associate Professor in Operations Research, Science and Engineering Faculty, School of Mathematical Sciences, Queensland University of Technology
Project Lead, Mulgowie Farming Company