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AI in resource management and agricultural production

Updated: Oct 17, 2023


neXus member Prof Francisco Blasques is working on predicting crop yield and

optimising usage of water, fertilisers and pesticides. The project also involves forecasting demand for agricultural products in a multi-product assortment environment with time-series econometrics models featuring trend-seasonality-cycle decomposition and structural breaks.



One of the aims of the project is to focus explicitly on responsible and sustainable use of water, fertilisers and pesticides. Helping both the environment and agricultural communities.


The AI team is also tasked with obtaining long terms forecasts for sales of agricultural products at multiple levels of granularity. Ensuring internal consistency between forecasts at sku level, seed type, segment, country, and specificity. Deploying time-series classification methods to ensure correct targeting of sub-groups of time-series with trends, seasonal effects, breaks, etc.

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