The project intends to enhance the sustainability of agriculture in Central Luzon by providing deeper description and insights for different commodities. Starting with the top three commodities in terms of the area planted or from the PSA data, which will be identified depending upon its impact and production on the region, metrics such as the crop maps found on Farmers Guide Map/National Color Coded Guided Agricultural Map, Project SARAI etc. will serve as an information source in providing crop advisories/recommendations to farmers and other stakeholders. Machine learning will be utilized for prediction and data analytics for forecast and future trends and tendencies which will be very useful for policy formulation for relevant programs, projects and activities of individual concerned agencies.

Raw data of the identified technologies will be converted into a descriptive insight. Commodities past and present trends will be illustrated through the utilization of descriptive analytics, commodities’ future trends will be illustrated through the use of predictive analytics. The project aims to provide smart commodity forecasts and advisory for farmers to enhance smart decisions to ensure maximum profit and commodity value. Smart commodity forecasts will be made through prescriptive analytics.

The suitability map will provide the farmers and economic planners a bird’s eye view of the commodity/crops capability to thrive and acquire value in each specific place. Recommendations and suitability on maps will not only depend on the existing agroclimatic condition of the area but will be combined with the agroeconomic indicators of the commodity such as the Rate of Return (RR) and probability Index (P). To ensure not only the production but also the value of the produce, profit to farmers and the agroeconomic contribution it will give to enhance the development of the Region.

The suitability map will provide the farmers and economic planners a bird’s eye view of the commodity/crops capability to thrive and acquire value in each specific place. Recommendations and suitability on maps will not only depend on the existing agroclimatic condition of the area but will be combined with the agroeconomic indicators of the commodity such as the Rate of Return (RR) and probability Index (P). To ensure not only the production but also the value of the produce, profit to farmers and the agroeconomic contribution it will give to enhance the development of the Region.