## 1 Introduction  
China is a major agricultural producer, and agriculture is the foundation of a powerful country. Agricultural issues are related to people's livelihoods and are one of the fundamental issues in China. In the global agricultural system, China has always been a major export country. Crop disease is one of the main agricultural disasters in China, characterized by multiple types, significant impacts, and frequent outbreaks [1]. Its scope and severity often cause significant losses to the national economy, especially agricultural production. There are several examples of apple leaf lesions. (1) Alternaria blotch mainly damages leaves, petioles, annual branches, and fruits. It is one of the important diseases that causes early leaf drop in apples, resulting in weakened tree vigor and reduced fruit yield and quality. (2) Brown spot mainly damages leaves, followed by fruits and petioles. It is one of the most important diseases, causing early defoliation of apples, and it is also the most common and serious disease which causes defoliation of apple trees. (3) Grey spot mainly damages leaves, but also branches, petioles, shoots, and fruits. The affected leaves generally do not turn yellow and fall off, but severely affected leaves may appear scorched. (4) Mosaic mainly damages leaves, causing discoloration, ring rot, distortion, and shrinkage of leaves on severely affected trees. The disease slows down the growth of affected trees, sometimes leading to reduced yields and quality of early leaves. Affected fruits are not durable in storage and are prone to inducing other diseases. (5) Rust mainly damages leaves, but can also affect young branches, young fruits, and fruit stems, often causing early defoliation, weakening tree vigor, and affecting yield. The hazards of early fallen leaves mainly include the following aspects: a decrease in leaf area leads to a decrease in photosynthetic products, which in turn affects the accumulation of sugar in the fruit, resulting in color differences and poor flavor. If there is no leaf cover, a large amount of fruit will be sunburned, further affecting the quality of the fruit. Insufficient nutrition in the flower buds can lead to poor differentiation or degeneration, and there may be no flowers or fruits the following year. The storage material of fruit trees decreases in winter, and the leaves and branches are thin and weak in spring, making them susceptible to cold and freezing damage. The early shedding of leaves can easily lead to secondary flowering, further affecting the yield of flowers and fruits the following year. The early shedding of leaves can seriously affect the vitality of trees, making them more susceptible to other diseases and posing a threat to the health of fruit trees. Disease problems have become a major factor limiting the growth of agricultural production. As agricultural production becomes increasingly dependent on refined management, manual disease treatment has become very cumbersome and unsustainable. In recent years, deep learning technology has been applied in many fields, especially in computer vision. Deep learning's effectiveness in image segmentation has been widely researched and confirmed. In the agricultural field, deep learning can be used for agricultural image segmentation problems, such as distinguishing disease areas in disease detection. This article will introduce the application of deep learning in agricultural disease spot image segmentation. Firstly, the article will discuss the relationship between disease detection and agricultural production, as well as the challenges they present. Next, it will explain the principles of deep learning and the basic concepts of image segmentation. Then, it will discuss how to apply deep learning to agricultural disease spot image segmentation and verify its accuracy and effectiveness through experiments. Finally, the potential value and future development direction of deep learning in agricultural production will be explored. Contribution of this article:  
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