Visible Near Infrared Hyperspectral (VNIH) technique to differentiate Trogoderma variabile reared on different commodities
Under Trogoderma sp, some comes major stored grain pest, which are of economic concern and most of the times accurate identification becomes very difficult. Under this study a new diagnostic system using visible nearinfrared hyperspectral (VNIH) imaging methods is developed to address identification gaps for T. variabile. This technique is useful because different materials have unique reflectance spectra, and this difference in reflectance spectra can be used to identify various constituents
... ious constituents in an image. For this study both larvae and adult were studied for T. variabile fed on wheat, maize, canola, barley, oats and rice for more than 4 generations. Each individual insects killed by ethanol were scanned using a hyperspectral imaging system from 400 to 1000nm. Matlab 2016b was used to develop predictive model for hyperspectral image classification. Deep neural network approach gave more than 90% accuracy for both larvae and adult stages fed on different commodities. From this result we can say that T. variabile on the different host can lead to difference in VNIH reflectance spectra. This is one of most fundamental factors for development of robust VNIH technique as diagnostic tool. Abstract Stegobium paniceum (L.) is a major pest for several stored products worldwide. Monitoring methods for this species, based on pheromone traps, are affected by the complexity and expensiveness of the chemical synthesis of the pheromone isomer [(2S,3R,1'R)-Stegobinone] and/or by its lost of efficacy after two weeks at room temperature. So other semiochemicals that can be exploited for monitoring this species are highly desirable. In this study was tested the behavioral response in two-choice olfactometer of S. paniceum adults to Volatile Organic Compounds (VOCs) collected from colonized substrate. The elution of the headspace collection from S. paniceum colony elicited attraction of both sexes. The GC-MS chemical analysis of the extract indicated the presence of several alkanes, alcohols, aldehydes and fatty acids, some of them already reported to attract other stored product coleopteran pests and promising candidates for further studies to test their attractiveness on S. paniceum.