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The document introduces UniCrop, a universal data engineering pipeline designed to enhance crop yield prediction by automating the acquisition, harmonisation, and feature construction of multi-source agro-environmental data. It addresses the challenges of scalability and reproducibility in agricultural machine learning by providing a configuration-driven framework that integrates over 160 environmental variables from diverse sources. The effectiveness of UniCrop is validated through a case study demonstrati

Author

zhangyu111

Language

EN