Automatic Monitoring of Pest Insects Traps Using Image Processing

Upadhyay, Akash J.; Ingole, Prashant V.

doi:10.11591/telkomnika.v12i8.6272

Cited by 2 publications

(6 citation statements)

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“…To facilitate the observer, image processing algorithms can be used to provide identification and automatic counts of the insects (Silveira and Monteiro 2009;Priya et al 2013;Kang et al 2014;Upadhyay and Ingole 2014;Wen et al 2015;Ding and Taylor 2016;Bjerge et al 2020). In some cases, the accuracy of the automatic count needs to be verified and validated by a human expert.…”

Section: Insect Pest Identification and Countmentioning

confidence: 99%

Insect pest monitoring with camera-equipped traps: strengths and limitations

2020

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Integrated pest management relies on insect pest monitoring to support the decision of counteracting a given level of infestation and to select the adequate control method. The classic monitoring approach of insect pests is based on placing in single infested areas a series of traps that are checked by human operators on a temporal basis. This strategy requires high labor cost and provides poor spatial and temporal resolution achievable by single operators. The adoption of image sensors to monitor insect pests can result in several practical advantages. The purpose of this review is to summarize the progress made on automatic traps with a particular focus on camera-equipped traps. The use of software and image recognition algorithms can support automatic trap usage to identify and/or count insect species from pictures. Considering the high image resolution achievable and the opportunity to exploit data transfer systems through wireless technology, it is possible to have remote control of insect captures, limiting field visits. The availability of real-time and on-line pest monitoring systems from a distant location opens the opportunity for measuring insect population dynamics constantly and simultaneously in a large number of traps with a limited human labor requirement. The actual limitations are the high cost, the low power autonomy and the low picture quality of some prototypes together with the need for further improvements in fully automated pest detection. Limits and benefits resulting from several case studies are examined with a perspective for the future development of technology-driven insect pest monitoring and management.

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Section: Insect Pest Identification and Countmentioning

confidence: 99%

Insect pest monitoring with camera-equipped traps: strengths and limitations

2020

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“…In this study we counted the captured moths manually, like in Guarnieri et al (2011) and Rassati et al (2016), from the images taken daily. But in most of the other studies, the pests were counted automatically by image processing software (Okuyama et al, 2011;Fukatsu et al, 2012;Priya et al, 2013;Upadhyay and Ingole, 2014;Ding and Taylor, 2016;Goldshtein et al 2017). Manual counting has an advantage of accuracy in the results with no doubt.…”

Section: Population Development Of Lobesia Botrana In Hadim and Taşkentmentioning

confidence: 99%

“…Since the discovery of the first insect pheromone by researchers in Germany, approximately 60 years have passed and there has been much progress in their development and use in insect pest management over the last three decades (Jones, 2014). In crop protection, one of the most important steps is monitoring pest insect populations, especially monitoring with traps is prevalent in pest management programs worldwide (Lopez et al, 2012;Priya et al, 2013;Upadhyay and Ingole, 2014;Raphael and Maheswari, 2016;Goldshtein et al, 2017). In particular, for monitoring the flight activity of fruit moths, sex pheromone traps are basic devices.…”

Section: Introductionmentioning

confidence: 99%

“…This is a labor-intensive, time consuming and expensive implementation, especially for large orchards/vineyards or fields hard to reach. So, to find an affordable system performing this duty in a more efficient way would give great advantage while monitoring insect pest populations (Tirelli et al, 2011;Lopez et al, 2012;Priya et al, 2013;Upadhyay and Ingole, 2014;Raphael and Maheswari, 2016;Potamitis et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…To minimize these efforts, some studies have brought into focus on the potential using of cameras for monitoring insect pest in recent decades (Jiang et al, 2008;Martin et al, 2008;Guarnieri et al, 2011;Fukatsu et al, 2012;Lopez et al, 2012;Priya et al, 2013;Selby et al, 2014;Upadhyay and Ingole, 2014;Azfar et al, 2015;Ding and Taylor, 2016;Raphael and Maheswari, 2016;Rassati et al, 2016;Goldshtein et al 2017). In these studies, the pests were counted either automatically by software (Fukatsu et al, 2012;Priya et al, 2013;Upadhyay and Ingole, 2014;Potamitis and Rigakis, 2015;Ding and Taylor, 2016;Goldshtein et al 2017) or manually by human experts (Guarnieri et al, 2011;Rassati et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Remote Monitoring of European Grapevine Moth, Lobesia botrana (Lepidoptera: Tortricidae) Population Using Camera-Based Pheromone Traps in Vineyards

Ünlü

Akdemïr

Öğür

et al. 2019

Turkish JAF Sci.Tech.

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This study presents a new sex pheromone trap for European Grapevine Moth, Lobesia botrana, to monitor its field population without direct field observations in Turkey. The study was conducted in Hadim and Taşkent (Konya) districts in 2016. Viticulture has been carried out for many years in both districts where the maximum vineyards are located. Due to the distance to the center and the difficulty of transportation to these districts, there has not been conducted any detailed studies until today. Therefore, this study about L. botrana, which is harmful in these vineyards, was planned. In order to monitor the pest population, the cameras were placed onto the pheromone traps, and it was tried to get information about the population development of the pest via internet without going to the vineyards. For this purpose, four locations in Hadim and one location in Taşkent district were selected and one pheromone trap was established in each location before the bud burst in vineyards. The camera was placed on each pheromone trap and was linked with vMEyeIPC program via internet. The time of first adult flight and the population development of adult L. botrana were determined. The first adult flight began at the beginning (7/4/2016) and in the middle of April (15/4/2016) in Hadim and Taşkent, respectively. The number of offspring and the maximum number of pest individuals caught in traps were recorded in vineyards in both districts.

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Automatic Monitoring of Pest Insects Traps Using Image Processing

Cited by 2 publications

References 0 publications

Insect pest monitoring with camera-equipped traps: strengths and limitations

Insect pest monitoring with camera-equipped traps: strengths and limitations

Remote Monitoring of European Grapevine Moth, Lobesia botrana (Lepidoptera: Tortricidae) Population Using Camera-Based Pheromone Traps in Vineyards

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