The efficacy of bioacoustics in detecting the presence of adult beetles inside the grain mass was evaluated in the laboratory. A piezoelectric sensor and a portable acoustic emission amplifier connected with a computer were used. Adults of the most common beetle pests of stored wheat have been detected in varying population densities (0.1, 0.5, 1, and 2 adults per kilogram of wheat). The verification of the presence of the insect individuals was achieved through automated signal parameterization and classification. We tried out two different ways to detect impulses: 1) by applying a Hilbert transform on the audio recording and 2) by subtracting a noise estimation of the recording from the spectral content of the recording, thus allowing the frequency content of possible impulses to emerge. Prediction for infestation was rated falsely negative in 60-74%, 48-60%, 0-28%, and 0-4% of the cases when actual population density was 0.1, 0.5, 1, and 2 adults per kilogram, respectively, irrespective of pest species. No significant differences were recorded in positive predictions among different species in almost all cases. The system was very accurate (72–100%) in detecting 1 or 2 insects per kilogram of hard wheat grain, which is the standard threshold for classifying a grain mass “clean” or “infested.” Our findings are discussed on the basis of enhancing the use of bioacoustics in stored-product IPM framework.
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