ANDFO: Soil Nutrient Assessment and Fertilizer Dosage Recommendation for Efficient Crop Nutrient Management

Abstract

Effective management of nutrients of soils is critical towards enhancing the productivity of agriculture and long-term sustainability of agriculture. Nevertheless, uncontrolled fertilizers application without regard to the soil-specific nutrient statuses usually results in an imbalance, low yield, and environmental influence. This research is an attempt to come up with an intelligent system that can accurately detect nutrient deficiency and recommend the optimal dosage of fertilizers. To achieve this, the proposed Adaptive Nutrient Deficiency Fertilizer Optimization (ANDFO) algorithm examines the following essential soil parameters Nitrogen (N), Phosphorus (P), Potassium (K), and pH and compares it to the ideal nutrient needs of crops. The approach unites the deficiency identification, the recommendation of the type of fertilizers, dosage estimation, and the analysis of estimation of growth into a single approach. The feasibility of the proposed model is proven in experimental results where the proposed model gets the accuracy of 0.99 % and this is better than the current methods. The system is useful in that, it helps to enhance nutrient balance, the health of soils, and performance of crops following application of fertilizers. To conclude, the ANDFO framework is a valid, economical, and feasible solution to implement precision agriculture through minimizing the unnecessary use of fertilizers, maximizing productivity, and sustaining productivity.