Journal of the Society of Agricultural Structures, Japan

Whiteflies are agricultural pests causing damage to valuable crops such as tomatoes and cucumbers, and the pesticide tolerance of whiteflies differs depending on their species and biotypes. Previously, a whitefly species and biotype identification scheme using the acoustic signatures of whiteflies was proposed, focusing on the fact that whiteflies emit a tiny acoustic signal for communication that varies depending on their species and biotypes. However, only two biotypes have been reported to have been classified so far. In this paper, we propose an advanced acoustic-based classifier to classify multiple species and biotypes [Trialeurodes vaporariorum and Bemisia tabaci (biotypes B, Q1 and Q2)] by focusing on the sound spectrogram of whiteflies. We developed a deep learning model that can classify the spectrograms of whiteflies, and we conducted experiments in an anechoic chamber. As a result, we found that the proposed classifier can classify T. vaporariorum and B. tabaci (biotypes B, Q1 and Q2) with an F-value of 96.8–100 % (mean 98.7 %) while the existing acoustic classifier can only classify them with an F value of 32.7–70.5 % (mean 60.3 %). We confirmed that the proposed classifier can classify the species and biotypes of whiteflies with almost the same accuracy as a DNA-based method.

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We examined the operational problems that arose at Rakuno Gakuen University’s biogas plant (BGP) during the period between fiscal year 2000 and fiscal year 2010 and identified adjustments necessary to attain stable operation. In the BGP, there are shutdowns due to mechanical failure of the system itself and from software failure, and we found both of these can occur even in the first year of operation. BGP operation is improved when the composition of raw organic waste (quality and volume) is stabilized because changes in condition can lead to system failure and plant shutdown. This in turn can lead to deterioration in the function and/or performance of multiple plant facilities. We found that stabilization was optimized when the use of high loading wastewater including manure and waste milk was used. It was possible to stabilize the volume of raw material in the range of 8–11 m³/d and produce a methane gas concentration of 50–57 % (daily average, 53 %). Furthermore, we proposed an effective method for determining the operational status of the BGP. Using methane production volume and BGP power consumption, which can both be easily measured, we calculated the volume of methane gas used for on-site consumption. Deviations from this value provided a simple and effective means of monitoring BGP operational status. This monitoring method can evaluate the operating condition by analyzing the mutual influence of multiple measurements. In addition, the effectiveness of the proposed monitoring method was confirmed at Rakuno Gakuen University BGP through analysis of actual measurement data combined with operational problem data.

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