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Bioacoustic detection of Callosobruchus chinensis and Callosobruchus maculatus in bulk stored chickpea (Cicer arietinum) and green gram (Vigna radiata)

Banga, Km. Sheetal, Kotwaliwale, Nachiket, Mohapatra, Debabandya, Giri, Saroj Kumar, Babu, V. Bhushana
Food control 2019 v.104 pp. 278-287
Callosobruchus chinensis, Callosobruchus maculatus, Cicer arietinum, Vigna radiata, bioacoustics, chickpeas, computer software, insect infestations, insects, mung beans, postharvest losses, relative humidity, temperature
Insects are one of the major reasons for post-harvest losses in stored food legumes. Real time detection at an early stage of insect infestation can overcome the foremost problem of infestation. Acoustic detection method detects the hidden as well as moving insects by amplifying and filtering their motility and feeding sounds. Crawling and feeding activities of two insects Callosobruchus chinensis and Callosobruchus maculatus in chickpea (Cicer arietinum) and green gram (Vigna radiata) were detected by using an insect detection probe placed in an acoustically insulated bin. Temperature and relative humidity were also measured through sensors mounted on the same probe. Captured sounds were pre-screened and analysed by using sound analysis software. Significant differences were found between the amplitude of two insects in both the legumes. Amplitudes of Callosobruchus chinensis were 79.32 dB and 84.01 dB for 59 ms duration in chickpea and green gram, respectively, whereas, the amplitude of Callosobruchus maculatus was 97.65 dB and 95.53 dB for 68 ms in chickpea and green gram, respectively. The detection range of the acoustic sensor was 300 mm omnidirectional. Formants (F1, F2, F3 and F4), formant bandwidth (FBW3), frequency and spectral power were observed as principal components for the detection of insects’ infestation (C. chinensis and C. maculatus) in bulk stored food legumes (chickpea and green gram). Formants of sound spectra found a specific role in the discrimination of insect and background noise. The findings of this study elucidated that acoustic detection method will provide rapid and non-destructive detection of infestation in bulk stored food legumes.