Farming isn’t normally a sector that comes to mind when you think of AI, but a UK Gov & Microsoft backed Agri-tech Centre has developed AI that predicts crops’ shipment window 3x earlier than previously possible – showing the impact tech is having on every sector of industry. The first proof-of-concept promises to save just one leading farming business more than £6m a year alone, equivalent to 15% increase in gross profit.
Delayed harvests are an expensive problem for international farming. Overseas crops are grown to a specified shipment window, which provides retailers with a constant supply of fresh produce. If windows are missed, growers are generally responsible for making up the shortfall.
Purchasing produce from a third-party supplier or airfreight are the most common ways to do this. Both are expensive. Costs for one of the UK’s leading food and farming business run to £120k per week – just for sweetcorn. However, these costs can be reduced substantially if a grower knows in good time that a shipment will be missed. The more time the grower has to source and negotiate alternatives, the lower the cost will be.
“This was the catalyst for creating our Harvest Timing Prediction AI,” explains Anna Woodley, Head of Sales at Agrimetrics. “We realised that increasing the notice period by even a couple of weeks would result in huge savings. To put this in perspective, one customer estimates savings of more than £6m per year. That’s equivalent to a 15% increase in gross profit.”
Agrimetrics are currently predicting the correct shipment window for sweetcorn crops with up to 93% accuracy, which can be done 4 weeks in advance. They claim that accuracy and timeframes can be increased given access to more data.
“Given the right data, we can improve the accuracy and widen the applications of our AI to cover more fields, more supply chains, more crops,” concludes Anna.
Anna will be presenting a case study and describing the applications and workings of their predictive AI during a webinar on Wednesday 1st July. You can sign up here.
You can also view an infographic summarising this work.