Advancements in Electronic Nose Technology for the Detection, Identification, and Monitoring of Insect Infestation in Stored Agricultural Grains: A Comprehensive Review

Merve Elçiçek1*, Doğan Ergün1, Bashir Ahmad Sheikh2 and Ayşegül Esra Gölcü3

Abstract

With yearly economic losses estimated at billions of dollars, post-harvest losses from insect pest infestations in stored grains pose a serious threat to global food security.  Visual examination, trapping methods, and chemical analysis are the mainstays of traditional pest detection methods in grain storage facilities. These approaches are often labour-intensive, time-consuming, and may not identify infestations in their early stages. A possible non-destructive, quick, and affordable substitute for detecting, identifying, and tracking grain pest infestations is electronic nose (e-nose) technology.  Examining the fundamental ideas, sensor technology, pattern recognition algorithms, and field applications, this review summarises recent studies on e-nose uses in agricultural grain pest control.  We examine the performance attributes of several e-nose systems, talk about their drawbacks and restrictions, and provide suggestions for future lines of inquiry.  Sitophilus species, Rhyzopertha dominica, Tribolium species, and Oryzaephilus surinamensis are among the major grain storage pests covered in the review. It emphasises how electronic nose technology can be used to detect volatile organic compounds (VOCs) released by these pests and damaged grains.  Some methods may identify infestations at population densities as low as 1–5 insects per kilogramme of grain, according to current research, which shows detection accuracies for a variety of pest species ranging from 80–95%.  For broad commercial usage, however, issues with standardisation, environmental interference, and long-term sensor stability still need to be resolved.