FinerForecasts - Biologically Driven Soft-Fruit Resource Optimisation, Labour & Yield Forecasts at Plant Granularity.

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FinerForecasts is a collaborative project led by FruitCast, partnered with the University of Lincoln and Chambers, a soft fruit grower in Kent, UK. The project will improve the accuracy of soft fruit crop forecasting using observation-based systems. Crop forecasting is essential for fresh produce business operations as it enables farmers to match supply and demand, set forward prices, reduce waste, plan labour, and optimise resources. Existing forecast tools range from grower intuition to models powered by machine learning, and are notoriously unreliable, leading to loss of income. FinerForecasts will develop a plant mapping system, enabling plant-level forecasting, which incorporates variability between plants, improves the overall forecast accuracy, and enables growers to optimise resources and address problem spots before yield is impacted. This extends FruitCast's current observational-based forecasting approach involves taking videos of crops and locating fruit and flowers within them to predict the age, weight, and harvest date. The project aims to achieve three objectives: (i) provide reliable yield forecasts within 15% error 3 weeks ahead for entire grower sites from a biologically regulated yield forecasting model, (ii) generate plant-level, agronomically relevant maps of forecasted yield and its variability for optimisation strategies for resource allocation, and (iii) develop a digital architecture capable of scaling the developed forecasting system across multiple sites at a per-plant resolution, ready for the UK market. FinerForecasts will produce more accurate yield forecasts, contributing up to £56m(see\_outcomes\_and\_route\_to\_market) of benefits to the current strawberry market, and the generation of new tools for growers to manage crops. The project also aims to reduce waste (currently 18KT) and the CO2 emissions (46KT CO2e), water, and pesticides embedded in that waste, reducing environmental impact, driving productivity, and securing a more resilient and sustainable fresh produce sector. FinerForecasts leverages FruitCast's ability to quickly and cheaply measure crop state from videos to make plant-level forecasts possible at commercial scales, increasing forecast accuracy. The University of Lincoln's expertise in agri-robotics and AI will contribute to the project's success, and Chambers' support will enable data collection and deployment of systems. FinerForecasts will transform the soft fruit industry by providing accurate and granular yield forecasts, reducing waste and environmental impact, optimising resources, and improving the resilience and sustainability of the fresh produce sector.