# YOLOv8-GO: A Lightweight Model for Prompt Detection of Foliar Maize Diseases
## 2 Materials and Methods  
### Maize Disease Profiles and Datasets  
Despite the availability of numerous disease-resistant maize varieties and stringent planting and treatment protocols, diseases continue to evolve. The replacement of maize varieties, climate change, and the promotion of no-till and shallow tillage practices have led to the emergence of new subspecies of diseases or their transmission from other crops back to maize. This has resulted in previously minor diseases becoming more severe or formerly controlled diseases re-emerging. In northern China, major diseases affecting maize at the maturity stage include Northern Leaf Blight, Gray Leaf Spot, and Rust. Northern Leaf Blight (as shown in Figure 1) exhibits various physiological subspecies and has undergone significant changes in its population structure. It has been observed in several major production areas. In the early stage of the disease, spots appear as large, yellow, or blue-gray water-soaked ovals on the leaves. In the middle stage, these spots evolve into spindle-shaped, elongated, or irregular patches. In the late stage, black and gray mold often grows on the patches [24]. Spring maize typically develops this disease from July to August. Gray Leaf Spot (as shown in Figure 2) was once widespread in Liaoning and the Huang-Huai-Hai region, with particularly severe outbreaks in parts of Liaoning from 2003 to 2004. In the early stages, the disease causes light brown spots on the leaves, which later develop into elongated gray-brown or gray lesions with brown edges. These spots are typically parallel to the leaf veins and range in size from 0.5 to 20 mm in length and 0.5 to 2 mm in width [25]. The main period of onset is from July to August, especially under conditions of high humidity or prolonged water film on the ground. Figure 1: Early and middle-stage lesions of Northern Leaf Blight. Rust (as shown in Figure 3) is a widespread disease affecting various production areas worldwide, including China. Notably, Southern Rust, which was previously confined to regions south of the Yangtze River, has progressively moved northward due to climate change. A severe outbreak occurred in 2007 in Liaoning and the Huang-Huai-Hai region, leading to significant losses. Initially, Rust manifests as greenish, creamy-white, or yellowish spots on maize. As the disease progresses, these spots develop into yellowish-brown or reddish-brown herpes-like spore masses, which threaten maize throughout its entire life cycle [26]. Although disease spots vary in size, shape, and color, early-stage symptoms are often subtle, while later stages typically result in extensive leaf necrosis, making them challenging for machine vision methods to distinguish. Mid-stage features are clearer and more recognizable; however, the spots are randomly distributed, with blurred edges, and may overlap, complicating the identification process. Therefore, preparing a comprehensive dataset is essential for improving the accuracy and effectiveness of disease recognition systems. The training dataset primarily utilizes data on three types of maize diseases from the Plant Village Dataset. The dataset has two key characteristics. First, the images are captured  
Figure 3: Rust disease spots. Figure 2: Gray Leaf Spot disease spots. at medium to close distances, with the diseased areas on the leaves occupying most of the frame, classifying them as large targets. However, each disease spot is small, making them small targets. This poses challenges for the model in terms of feature fusion and cross-scale recognition. Second, the dataset was collected in a laboratory setting, which generally lacks background information. Therefore, this study selected photos with field backgrounds from the dataset provided by Jiamusi Academy of Agricultural Sciences to expand the training dataset. Data annotation and bounding box adjustments were conducted under expert guidance.