Plant Leaf Diseases Prediction using Butterfly Optimization BO with Support Vector Machine SVM

Productivity in agriculture is important for economic expansion. The presence of illness in plants is very widespread, this is one of the factors that makes plant disease identification crucial for the agriculture sector. Given that plants are frequently afflicted by illnesses, they may die and produce fewer fruits and vegetables. By utilising various sorts of techniques and algorithms, such as image processing, the most recent and advancing technologies are applied to address such problems. Image segmentation is employed during pre-processing to reduce the noise and to separate the leaf's damaged or affected areas. This paper explores some of the difficulties that may arise when utilising machine learning to identify plant diseases and pests in real-world settings. The obtained features are then categorised using machine learning methods like Butterfly Optimization BO with Support Vector Machine SVM. The user is advised to receive treatment during the final stage. The diseases primarily have a negative impact on live plants. With this strategy, farmers should have a greater chance to maintain the health of their crops and avoid stressing the plants by using the wrong fertilisers.