RESUMO
The tomato leafminer Tuta absoluta (Meyrick) is one of the most harmful pests of solanaceous crops. Its larval morphological characteristics are similar, making the distinguishing between different larval instars difficult. Accurate identification of T. absoluta instars is necessary either for population outbreak forecasting, or developing successful control programs. Although a clustering algorithm can be used to determine the number of larval instars, little is known regarding the use of density-based ordering points to identify the clustering structure (OPTICS) and determine the number of larvae. In this study, larval instars of 240 T. absoluta individuals were determined by the density-based OPTICS clustering method, based on mandible width, and head capsule width and length. To verify the feasibility of the OPTICS clustering method, we compared it with the density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm, Gaussian mixture models, and k-means. Additionally, the instars determined by the clustering methods were verified using the Brooks-Dyar rule, Crosby rule, and linear regression model. The instars determined by the OPTICS clustering method were equal to those determined by the other types of clustering algorithms, and the instar results were consistent with the Brooks-Dyar rule, Crosby rule, frequency analysis, and logarithmic regression model. These results indicated that the OPTICS clustering method is robust for determining insect larva instar phase. Moreover, it was found that three morphological indices of T. absoluta can be used for determining instars of this pest in the field, which may provide important information for the management of T. absoluta populations.
Assuntos
Algoritmos , Entomologia , Mariposas , Animais , Análise por Conglomerados , Larva , Solanum lycopersicum , Entomologia/métodosRESUMO
BACKGROUND: The potato tuber moth (PTM), Phthorimaea operculella (Zeller) (Lepidoptera: Gelechiidae), is a destructive pest of Solanaceae crops worldwide. α-solanine and α-chaconine are toxic steroidal glycoalkaloids (SGAs) in Solanaceae crops and are most abundant in potatoes (Solanum tuberosum L.), accounting for more than 95% of the total SGAs. PTM grows on potatoes with a higher concentration of SGAs. Gut bacteria play an important role in the physiology and behavior of insects. To understand the role of gut bacteria of PTM in host adaptability, we isolated and identified major SGA (α-chaconine and α-solanine)-degrading gut bacteria in the gut of PTM by a selective medium and analyzed their degradability and degradation mechanism. RESULTS: The gut Glutamicibacter halophytocola S2 of PTM with high degradation capacity to α-solanine and α-chaconine were detected by liquid chromatography mass spectrometry (LC-MS) and identified by morphological and 16S rRNA gene sequence analysis. A gene cluster involving α-rhamnosidases, ß-glucosidases, and ß-galactosidases was identified by whole-genome sequencing of G. halophytocola S2. These genes had higher expression on the α-solanine medium. PTM inoculated with the isolated G. halophytocola S2 obtained higher fitness than antibiotic-treated PTM. CONCLUSION: The G. halophytocola S2 in the gut of PTM could degrade the major toxic α-solanine and α-chaconine in potatoes. This enhances the fitness of PTM feeding on potatoes with high SGA contents. The results provide a theoretical foundation for the integrated pest management of PTM and provide an effective strain for the treatment of α-solanine and α-chaconine in potato food. © 2022 Society of Chemical Industry.