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AI and Genetics in Fertilizer Optimization by dd is a document available to read on EtoBox.

NYU researchers have developed a process that combines plant genetics and machine learning to improve nitrogen use efficiency in corn, a major cash crop in the U.S. This approach aims to reduce fertilizer costs for farmers and mitigate environmental impacts caused by nitrogen pollution. By identifying and ranking nitrogen-responsive genes, the research seeks to enhance agricultural sustainability.

Author

dd

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EN