Determining the sound signatures of insect pests in stored rice grain using an inexpensive acoustic system

Insect pests in storage are causes of major losses worldwide. Acoustic sensors can detect the presence of insects in grain through their sound signature, thus enabling early warning to farmers and traders. This research investigates the applicability of an affordable acoustic sensor, which uses micro-electromechanical systems (MEMS) microphone adapted to detect the sound produced by insect pests. Three major insect pests that commonly feed on paddy and milled rice (the lesser grain borer, Rhyzopertha dominica; the rice weevil, Sitophilus oryzae; and the red flour beetle, Tribolium castaneum), were collected in rice mills and grain storage warehouses in Laguna The Philippines, and reared at the International Rice Research Institute. Baseline sound recordings were replicated for each insect over three days using a completely randomized design (CRD). Recorded sounds were analysed to determine the sound profiles of each insect. Waveforms, root mean square (RMS) energy values, frequency domain, and spectrograms provided characteristics for the sound signal signature specific to each insect. Primary insect pests (R. dominica and S. oryzae) were differentiated from the secondary insect pest (T. castaneum) through signal analyses. Such data are useful to enable insect pest classification, which can be incorporated into more effective and timely postharvest pest management tools.