A Fuzzy Logic based Agricultural Decision Support System for Assessment of Crop Yield Potential using Shallow Ground Water Table

Agricultural research is aimed towards increasing the productivity and food quality at reduced expenditure and with increased profit. One of the main challenges of this approach is to equip farmers with adequate and affordable information and control technology; as for higher crop yields, they need advanced expert knowledge to take proper decisions during land preparation, sowing, fertilizer management, irrigation management, integrated pest management, storage etc. In an effort to provide a methodology for better assessment on the functional outcome of this research area, an online fuzzy logic based agricultural decision support system is developed and presented in this paper. The aim of this system is to assist farmers in taking proper decisions for having a better crop production with less cost, despite the adverse nature of the soil on their farming area. Our proposed system focuses on utilizing abundant surface ground water available at the end of the wet season while benefiting from timely access to shallow groundwater from the process of capillary rises so that the farmers can have a better crop yield with or even without the expensive irrigations. The experiment was carried out in the northern and southern (coastal areas) regions of Bangladesh. Fuzzy logic is used in this case to