Predicting green bean yield using the power of predictive models

November 30, 2020
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News

Predicting green bean yield using the power of predictive models

A new project will use the power of predictive models to forecast the harvest and yield of green beans.

November 30, 2020
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Every day, suppliers of fresh produce need to make difficult decisions in a short amount of time with imperfect data, in order to plan supply and satisfy market expectations.

For Australian green bean growers, managing supply continuity is important for business growth and can boost revenue significantly. With so many variables to consider for planning planting and sales, one would hope for a crystal ball to be able to predict when to harvest and how much the crop is going to produce.

A Food Agility Cooperative Research Centre project is aiming to do just that by using the power of predictive models to forecast the harvest and yield of green beans. The project is a collaboration between the Department of Agriculture and Fisheries Queensland (DAF), Queensland University of Technology (QUT) and Mulgowie Farming Company.

Supply and production planning in fresh produce systems has many variables to consider for accurate forecasting of yield, including changing weather patterns. Therefore, planning the supply of fresh produce to align with demand and market expectations is complicated and if it is off the mark can be costly. Variations in yield forecasts can also result in either supply shortages or excess.

Predicting yield with science

Predictive growth models that are accurate can predict harvest timing, yield and quality, and in turn enhance production and sales planning throughout the entire business – a win for the producer, the retailer and the consumer.

The research team will be developing a dedicated green bean modelling tool for Mulgowie Farming Company by identifying and building on existing crop planting, yield, and location data. The model will be tested in the ‘real’ world to ensure accuracy and reliability and to further refine predictive capacity. Additionally, a user interface tool will be created for use by the Mulgowie team.

Amanda Woods, project lead from Mulgowie Farming Company said, “We see this as a significant benefit for the green bean industry. The predictive model will aid in better aligning supply and demand while also supporting marketing, promotion and pricing decisions.”

The value of these innovative predictive tools to the green bean industry as a whole could be worth between $2.5 - $5 million per year by 2021.

For further information visit the Food Agility project page for Predicting Green Bean Harvest and Yield.

Amanda Woods from Mulgowie Farming Company is part of the project team.

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