While accurate flowering predictions are essential for orchard management, and have consequences for pest control and pollination, traditional data collection has been limited both geographically and botanically, often missing the broader variability of flowering across regions.
Now, a new study published in Horticulture Research shows how the FruitWatch project, conducted by the University of Reading and Oracle Corporation, is helping to expand research to incorporate a more diverse range of data, improving the precision and relevance of predictive models for enhanced orchard management
The innovative FruitWatch platform collects widespread data contributions from the public, improving the prediction of flowering onset times for various fruit trees in Great Britain, with a focus on real-time and geographically diverse data acquisition. Analysing data from 2024 for four main fruit tree cultivars, the study identified notable latitudinal delays in flowering times.
As a result, those behind the project claim that it has significantly refined and enhanced phenological models, offering growers precise, location-specific predictions, essential for optimising agricultural planning and interventions. This not only addresses significant gaps in data but also boosts the precision and accuracy of predictions, facilitating superior orchard management based on robust, real-time data.
Dr Chris Wyver, the lead researcher, commented, “Incorporating citizen science into phenological predictions marks a major leap forward for agricultural science. Engaging the community broadens our data pool, enabling more detailed and actionable insights for both farmers and researchers.”