Apple is one of the most cultivated and essential fruit grown worldwide. It is nutritionally active and health beneficial. Therefore, we need to increase the production and also provide better quality to the apple industry. This chapter provides the insights about apple production, production strategies and machine learning based apple disease detection methods. Furthermore, in depth knowledge is provided about Artificial Intelligence (AI) based leaf and fruit disease detection algorithms. Despite these advancements, challenges remain, including issues related to data quality, class imbalances, and the need for efficient algorithms capable of real-time processing in apple orchard. Chapter includes data regarding climate change that affects apple tree growth. Some of the diseases that appear on apple leaves and apple fruits are also presented. Finally some of the pickup points and future guidelines for the readers are provided for the better production of apple using edge cutting technologies. The practical applications of these findings are discussed, emphasizing the potential for farmers to adopt advanced detection technologies to improve disease management and minimize production losses. Additionally, we suggest areas for future research, focusing on the integration of emerging technologies to further enhance the effectiveness of apple disease detection systems. In conclusion, this chapter highlights the critical role of effective apple disease detection in ensuring sustainable agricultural practices and promoting the health of apple orchards. Highlights