Acoustical Comparisons of Calling Songs from Anastrepha Species in Brazil

Mankin, Richard W.; Malavasi, Aldo; Aquino, Cléber

doi:10.1201/9780367812430-9

Cited by 9 publications

(3 citation statements)

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“…The Butterworth approximation was used to calculate the filter, since it has a flat frequency response in the passband without the presence of ripple at the cut-off frequency. This characteristic is important because of the close-up of the cut-off frequency of the high-pass filter (70 Hz) with the lowest frequency of interest 89.1 ± 4.5 Hz (fundamental frequency of the wing beat signal of the A. fraterculus [ 6 ]). The order of the implemented filter was determined experimentally by evaluating the noise generated by the electric network (60 Hz) that is close to the cut-off frequency (70 Hz).…”

Section: Methodsmentioning

confidence: 99%

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Development of an Optoelectronic Sensor for Detecting and Classifying Fruit Fly (Diptera: Tephritidae) for Use in Real-Time Intelligent Traps

Moraes

Nava

Scheunemann

et al. 2019

Sensors

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Fruit flies (Diptera: Tephritidae) cause losses to world fruit growing. For a fast and effective control of the pest, it is necessary to identify the species and their populations. Thus, we developed an infrared optoelectronic sensor using phototransistors to capture the signal of the partial occlusion of the infrared light caused by the beating of the fly wings. Laboratory experiments were conducted using the sensor to capture the wing beat signal of A. fraterculus and C. capitata. The captured signals were used to obtain the characteristics of the flies’ wing beats frequency and for a production of a dataset made available as one of the results of this work. For the passage detection, we developed the algorithm of detection of events of passage (PEDA) that uses the root mean square (RMS) value of a sliding window applied to the signal compared to a threshold value. We developed the algorithm of detection of events of passage (CAEC) that uses the techniques of autocorrelation and Fourier transform for the extraction of the characteristics of the wings’ beat signal. The results demonstrate that it is possible to use the sensor for the development of an intelligent trap with detection and classification in real time for A. fraterculus and C. capitata using the wing beat frequency obtained by the developed sensor.

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Section: Methodsmentioning

confidence: 99%

“…This variation of light is processed and determines the frequency of the beating of the insect wings. According to [ 6 ], this frequency depends on the physiological characteristics of the species and can be used for its identification.…”

Section: Introductionmentioning

confidence: 99%

Development of an Optoelectronic Sensor for Detecting and Classifying Fruit Fly (Diptera: Tephritidae) for Use in Real-Time Intelligent Traps

Moraes

Nava

Scheunemann

et al. 2019

Sensors

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“…The frequency of insect wing beating can also be used for identification, as it depends on the physiological characteristics of each fruit fly species [112]. Therefore, Potamitis et al [59] developed an electronic trap as a modification of the classical trap for fruit flies (McPhail trap).…”

Section: Fruit Flies (Tephritidae Drosophilidae)mentioning

confidence: 99%

Automatic Pest Monitoring Systems in Apple Production under Changing Climatic Conditions

et al. 2022

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Apple is one of the most important economic fruit crops in the world. Despite all the strategies of integrated pest management (IPM), insecticides are still frequently used in its cultivation. In addition, pest phenology is extremely influenced by changing climatic conditions. The frequent spread of invasive species, unexpected pest outbreaks, and the development of additional generations are some of the problems posed by climate change. The adopted strategies of IPM therefore need to be changed as do the current monitoring techniques, which are increasingly unreliable and outdated. The need for more sophisticated, accurate, and efficient monitoring techniques is leading to increasing development of automated pest monitoring systems. In this paper, we summarize the automatic methods (image analysis systems, smart traps, sensors, decision support systems, etc.) used to monitor the major pest in apple production (Cydia pomonella L.) and other important apple pests (Leucoptera maifoliella Costa, Grapholita molesta Busck, Halyomorpha halys Stål, and fruit flies—Tephritidae and Drosophilidae) to improve sustainable pest management under frequently changing climatic conditions.

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