Morphological analysis of the forewings of eighteen species of noctuids (Lepidoptera: Noctuoidea) based on relative warp analysis
Author of the article:CAI Xiao-Na1** AN Feng-Jiao1 HAN Zhu-Hua1 ZHOU Zhou2 PAN Peng-Liang2***
Author's Workplace：1. School of Statistics and Data Science, Hebei Finance University, Baoding 071000, China; 2. College of Agronomy, Xinyang Agricultural and Forestry University, Xinyang 464000, China
Key Words：noctuid; moth wings; relative warp analysis; geometric morphology
Abstract：[Aim] To evaluate the potential for the digital classification of 18 species of noctuid moths based on geometric, morphological characteristics of their forewings. [Methods] Initially, Procrustes superimposition analysis was employed to eliminate the influence of non-shape factors, thereby obtaining distribution maps of landmark points for each species of noctuid. Subsequently, one-way ANOVA was used to verify the variability of the landmark point data. Relative twist analysis was then used to analyze the geometric morphology of the moth wings, and relative twist matrices were obtained as parameters for the identification and classification of each species. Principal component analysis was utilized to analyze morphological differences among moth wings. Finally, discriminant analysis was employed to construct a classification function and identify test samples. [Results] Procrustes superimposition analysis visually demonstrated the distribution of landmark points after superimposition for each species of noctuid. Relative twist analysis facilitated the visualization of interspecific differences among species. The twist plots revealed subtle differences in the wing morphology of the 18 noctuid species, and revealed longitudinal differences in the intersection points of the elbow veins Cu1, Cu2, and the hind vein 2A, with the outer edge of the wing among the same species. The accuracy of the discriminant results for the test samples was 91.11%. [Conclusion] Relative twist analysis not only effectively revealed differences and similarities in the forewing morphology of noctuid moths, but also serves as a parameter indicator for digital classification, providing a richer basis for automated insect classification.