Detection and quantification of the insect pest Rhyzopertha dominica (F.) (Coleoptera: Bostrichidae) in rice by qPCR

Abstract

The early detection of insects during grain storage and processing remains a major issue for the cereal industry, especially when immature stages are hidden inside the grain kernels. For this reason, we developed a qPCR method to detect and quantify one of the main pests of stored products in rice: the coleopteran internal feeder Rhyzopertha dominica. For that purpose, a specific primer set was designed to amplify artificial infestations of this pest in rice. Then, using a regression model, a standard curve was generated that correlated individuals to adult equivalent DNA quantity (inverse of the Ct value). Results revealed that the designed primer set was specific for R. dominica when tested against the other 4 common internal feeders in grain. The technique showed to be accurated (DNA was detected in more than 73% of the samples) and sensitive to insect presence (i.e. from 0.02 adults, 0.1 3rd instar to pupae or 13 egg to 2nd instar detectable per kg of rice). Moreover, the detection of R. dominica was strongly associated with a given infestation size: DNA quantity increased along with the size of the population. The use of the described qPCR protocol in grain and milling factories may enhace the critical detection and quantification of R. dominica populations in raw materials and processed food.