ARIMAX Model for Mango Price Prediction System Using Image Processing

The Nigeria agriculture sector, which contributes 10% of GDP, relies on fruit cultivation. Farmers, particularly mango farmers, face unpredictable crop demands, affecting their economy and causing excess food waste. This is due to inadequate education, outdated traditional beliefs, and a lack of understanding of customer consumption trends. Establishing a proper mango price prediction system is crucial to address these issues. Farmers face financial losses due to plant issues, including illnesses and insect infestations, limiting growth and affecting yield. Manual identification is challenging, and limited availability of agricultural experts leads to delays, insufficient problem recognition, and insufficient understanding of fertilizers and pesticides. Mango fruit in Nigeria has high market value, but farmers lack knowledge on harvest quality. This study aims to identify factors affecting these areas and develop a mobile app with price predictor, pest and disease identification, fertilizer suggestion, and mango quality predictor. The system aims to guide users towards effective resource sharing and high-quality decision-making.