Determining the number of instars in potato tuber moth Phthorimaea operculella (Zeller) using density‐based DBSCAN clustering

Abstract

AbstractThe potato tuber moth (PTM), Phthorimaea operculella (Zeller), is an important pest of Solanaceae crops and especially devastating to potatoes. There is no significant difference in morphological characteristics of PTM from the first to third instar larvae; therefore, it is difficult to directly determine the number of instars of this pest based on morphology. In the present study, head capsule width and length and mandible width of 340 PTM individuals were measured. Density‐based spatial clustering of applications with noise (DBSCAN) clustering was used for instar grouping. The results of DBSCAN clustering were compared with those obtained using Gaussian mixture models and k‐means clustering; the results of the three clustering methods were verified using Brooks–Dyar rule, Crosby rule and linear regression model. The clusters obtained using the three methods were the same and comprised four PTM instars with three morphological characteristics. Moreover, the results of the three methods fit the Brooks–Dyar rule, Crosby rule, frequency analysis and logarithmic regression model well. Head capsule width was the best morphological characteristic for determining the number of instars of PTM, and this characteristic may be used for determining PTM instars in the field. These results show that the DBSCAN clustering method is a promising tool for the identification of insect instars.