Data-Driven Knowledge Agriculture: Difference between revisions

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<a href="https://globaljournals.org/GJSFR_Volume23/3-Data-Driven-Knowledge.pdf"  target=_blank><b>Data-Driven Knowledge Agriculture: A Paradigm Shift for Enhancing
[https://globaljournals.org/GJSFR_Volume23/3-Data-Driven-Knowledge.pdf"  target=_blank><b>Data-Driven Knowledge Agriculture: A Paradigm Shift for Enhancing
Farm Productivity & Global Food Security</b></a>
Farm Productivity & Global Food Security</b>]





Revision as of 22:26, 22 August 2024

[https://globaljournals.org/GJSFR_Volume23/3-Data-Driven-Knowledge.pdf" target=_blank>Data-Driven Knowledge Agriculture: A Paradigm Shift for Enhancing Farm Productivity & Global Food Security]


Data-driven Knowledge agriculture using mechanized intelligent computer-based monitoring and control systems and complex Software for machine learning and visualization for predicting a variety of parameters such as future food requirements, resource planning for higher yield, and supply chain is the future of farming. This needs to be urgently adopted by the world farming community to provide food to the growing world population, remove hunger, and at the same time sustain planet resources by judicious uses of input such as water, fertilizer, pesticide etc., as envisioned by Sustainable Development Goals 2030. This paper discusses data-driven technology for identifying trends and other insights for making informed decisions for enhanced productivity and profitability, through market research and evaluating customer needs and sentiments.