Fuzzy logic based prediction of micronutrients demand for harumanis mango growth cycles

Abstract

Abstract Harumanis is a famous green eating mango cultivar that has been commercially cultivated in Malaysia’s state of Perlis. A variety of nutrients are found in soil, all of which are necessary for plant growth. Micronutrients such as Nitrogen (N), Phosphorus (P), and Potassium (K) are essential for Harumanis mango (Mangifera Indica) to growth. The importance of soil fertility in achieving high plant productivity and quality cannot be overstated. It should be used in a moderate amount and in a balanced manner. Predicting appropriate nutrients and the right timing to satisfy the tree’s demands is critical. The aim of this study is to create for Harumanis mango a fuzzy logic-based system to analyse the results of soil tests for nitrogen (N), phosphorus (P), and potassium (K) in the Harumanis mango orchard. The interpreted data are used to estimate N-P-K nutrient levels and indicate the optimal fertilizer solution and application timing for each Harumanis growth stages. The system utilizes Fuzzy Logic Control (FLC) to predict the nutrients demand for Harumanis mango growth. Results shows the system able to calculate and predict values of required N-P-K fertilizer for optimal growth. Thus, assist farmers in predicting the proper amount of N-P-K to apply to Harumanis mango soil.