CORDIS Project
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This project focuses on developing xSeedScore, a machine learning technology designed to enhance the climate resilience of crops. By improving resource efficiency in agriculture, it aims to support plant breeders in creating stable, value-added products that can help address global food security challenges.
Global food security challenges, due to exposure to more frequent and intense climate extremes, are threatening to erode and reverse gains made in ending hunger and malnutrition globally, and to shake the foundations of crop production locally.
Therefore, plant breeders are under pressure to tackle climate resiliency and resource efficiency.
Machine learning-based technologies have the potential to address these challenges and enable breeders to produce stable, value-added products, which contri…
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