Abstract: To attest the feasibility of math-morphological characters (MMCs) of moth wings for classification and identification of Noctuidae, we used digital technology to acquire and process insect images. Thirteen MMCs, such as rectangularity, elongation, lobation, eccentricity, sphericity, roundness and movement invariants including Hu1 and Hu2, which are invariants to the image size and direction, were selected. The characters from right forewings of moths from six noctuid species were extracted in this study. The methods including variance analysis, stepwise discriminant analysis and cluster analysis were used to study the feasibility, reliability and importance of each MMC as classification attribute of insect classification. The kinship among the six noctuids was analyzed from the perspective of mathematical morphology. The analysis results showed that rectangularity and elongation had no significant contribution to classification and identification of the six noctuids. Therefore, 11 morphological characters were selected as the classification variables. The contribution of these variables could be ranked as follows: (eccentricity, Hu5, Hu7)＞Hu2＞roundness＞sphericity＞Hu3＞(lobation, Hu1, Hu6)＞Hu4. Classification and discrimination of the six noctuids were realized by using the character parameters of moth wings. The phylogenetic relationship of the six noctuids based on the character parameters was consistent with that based on the traditional morphological observation. The results indicate that MMCs of moth wings can be used to identify moths rapidly and will be useful in gradually realizing the automatic recognition of moths in the future.

Key words: Noctuid moths, math-morphological character (MMC), wings, digital identification, character extraction, phylogenetic relationship