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Fruit farmers can predict crops using AI tool - The National Robotarium

Jun 18, 2024 - thenationalrobotarium.com
Researchers at the National Robotarium, in collaboration with partners in Chile and Spain, have developed an AI system that uses smartphone images to accurately count flowers on fruit trees, helping farmers predict harvest sizes months in advance. The system, which recognises patterns and features such as petal edges and shapes, even when partially obscured, was tested on peach orchards in Catalonia, Spain, and predicted flower counts with 90% accuracy. This is a significant improvement on current manual methods, which have error rates of 30-50%. The system could help optimise water use, resource allocation, and planning of harvesting and distribution logistics.

Dr Fernando Auat Cheein, associate professor in robotics and autonomous systems at the National Robotarium, highlighted the potential of the AI system to integrate with traditional farming practices and help farmers make more informed decisions about crop management. The technology could be adapted for other crops like apples, pears, and cherries, benefiting growers worldwide. The National Robotarium, part of the Data-Driven Innovation initiative, aims to use AI and robotics to drive sustainable and productive agriculture. The research project was developed in collaboration with the Advanced Center for Electrical and Electronic Engineering from Federico Santa Maria Technical University and Universidad Andres Bello in Chile.

Key takeaways:

  • A new AI system developed by the National Robotarium and partners in Chile and Spain can accurately count flowers on fruit trees using smartphone images, helping farmers predict harvest sizes months in advance.
  • The system was tested on peach orchards in Catalonia, Spain, and predicted flower counts with a 90% accuracy, significantly improving upon current manual methods which have error rates of 30-50%.
  • The AI system could help optimize water use, resource allocation, and planning of harvesting and distribution logistics, potentially reducing waste and increasing efficiency in the global agricultural supply chain.
  • If proven effective, the approach could be adapted for other crops like apples, pears, and cherries, benefiting fruit growers in Britain, Europe, and beyond.
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