A Multi-Stage Maize Leaf Image Dataset for Classification of Spodoptera exigua damage

Maize is a crop of paramount importance for global food and feed production, yet its growth is frequently threatened by insect pests. Among these, the beet armyworm (Spodoptera exigua) is a major pest that inflicts severe damage during the seedling stage. Accurate recognition and grading of pest leaf damage are essential for effective precision control. To support the development of intelligent agriculture, we established a field-based image dataset targeting Spodoptera exigua damage on maize leaves. Images were collected under natural light and complex field backgrounds across three critical seedling stages (V4, V6, and V8).