Nocturnal Activity of Adults of Six Lepidopterous Pests of Cotton as Indicated by Light-Trap Collections

1964 ◽  
Vol 57 (3) ◽  
pp. 328-332 ◽  
Author(s):  
H. M. Graham ◽  
P. A. Glick ◽  
D. F. Martin
Keyword(s):  
Light Trap ◽  
Nocturnal Activity

scholarly journals Identification of insects associated with ebony (Diospyros celebica Bakh.) as an endemic tree to Sulawesi

2021 ◽  
Vol 886 (1) ◽  
pp. 012037
Author(s):  
Sitti Nuraeni ◽  
Marwan Rajab ◽  
Tumanan ◽  
Diky Wahyudi
Keyword(s):  
Data Analysis ◽  
Functional Role ◽  
Light Trap ◽  
University Education ◽  
Pitfall Traps ◽  
Transient Species ◽  
Nocturnal Activity ◽  
South Sulawesi ◽  
Index Value ◽  
Richness Index

Abstract The population of ebony trees in Sulawesi has decreased and has been included in Appendix II Cites, which means it can only be traded based on quotas. Insect studies on ebony stands are still limited, especially in South Sulawesi. This study aims to determine the diversity and association of ebony with insects found in ebony stands in the Hasanuddin University Education Forest, Maros Regency. This activity was carried out in June 2021. Sampling was carried out using the light trap method for winged insects with nocturnal activity and pitfall traps for insects crawling on the ground. Data analysis to determine the diversity of insect species was carried out using the Shannon-Wiener (H') species and the Margalef index. The results showed that the insects found were 8 orders, 20 families, and 28 species from 128 individuals. Based on analysis of their functional role, the insect complexes consist of 34% herbivores, 50% predators, 8% parasitoids, 14% detritivores and 2% transient species. The diversity of species was classified as moderate, namely 2.71, while the richness index value of 5.56, which was classified as high richness in Ebony Stands.

scholarly journals In search of the spectral composition of an effective light trap for the mushroom pest Lycoriella ingenua (Diptera: Sciaridae)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sándor Kecskeméti ◽  
András Geösel ◽  
József Fail ◽  
Ádám Egri
Keyword(s):  
Light Intensity ◽  
Spectral Sensitivity ◽  
Fungal Pathogens ◽  
Light Trap ◽  
Spectral Composition ◽  
Wavelength Dependence ◽  
Crop Damage ◽  
Photon Flux ◽  
Compound Eyes ◽  
Behavioural Experiments

AbstractCertain fungus gnats, like Lycoriella ingenua are notorious pests in agriculture, especially in mushroom production. While larvae cause mainly direct crop damage, adults are vectors of several dangerous fungal pathogens. To promote the development of pesticide-free management methods, such as light trapping, we measured the spectral sensitivity of L. ingenua compound eyes with electroretinography and performed two different behavioural experiments to reveal the wavelength dependence of phototaxis in this species. The spectral sensitivity of the compound eyes is bimodal with peaks at 370 nm (UV) and 526 nm (green). Behavioural experiments showed that attraction to light as a function of wavelength depends on light intensity. In our first experiment, where the minimal photon flux (105–109 photons/cm2/s) needed for eliciting a phototactic response was determined wavelength by wavelength, phototaxis was strongest in the green spectral range (~526 nm). In the other behavioural experiment, where wavelength preference was tested under a higher but constant light intensity (~1013 photons/cm2/s), the highest attraction was elicited by UV wavelengths (398 nm). Our results suggest that both UV and green are important spectral regions for L. ingenua thus we recommend to use both UV (~370-398 nm) and green (~526 nm) for trapping these insects.

scholarly journals An Efficient Alternative to the CDC Gravid Trap for Southern House Mosquito (Diptera: Culicidae) Surveillance

2020 ◽  
Author(s):  
Timothy D McNamara ◽  
Thomas A O’Shea-Wheller ◽  
Nicholas DeLisi ◽  
Emily Dugas ◽  
Kevin A Caillouet ◽  
...  
Keyword(s):  
United States ◽  
Mosquito Species ◽  
Red Light ◽  
Light Trap ◽  
The United States ◽  
Light Traps ◽  
Efficient Alternative ◽  
Gravid Trap ◽  
Trapping Trials

Abstract West Nile virus (WNV) is the most prevalent arbovirus found throughout the United States. Surveillance of surface breeding Culex vectors involved in WNV transmission is primarily conducted using CDC Gravid traps. However, anecdotal claims from mosquito abatement districts in Louisiana assert that other trap types may be more suited to WNV surveillance. To test the validity of these assertions, we conducted a series of trapping trials and WNV surveillance over 3 yr to compare the efficacy of multiple trap types. First, we compared the CDC Gravid trap, CO2-baited New Standard Miniature Blacklight traps, and CO2-baited CDC light traps with either an incandescent light, a red light, or no light. We found that the CDC Gravid trap and CO2-baited no-light CDC Light trap collected the most mosquitoes. Second, we conducted additional, long-term trapping and WNV surveillance to compare these two trap types. We found that CO2-baited no-light CDC traps collected more of the local WNV vector, Culex quinquefasciatus (Say, Diptera, Culicidae), and detected WNV with greater sensitivity. Finally, we conducted trapping to compare the physiological states of Cx. quinquefasciatus and diversity of collected mosquitoes. CO2-baited no-light CDC light traps collected more unfed Cx. quinquefasciatus while Gravid traps collected more blooded Cx. quinquefasciatus; both traps collected the same number of gravid Cx. quinquefasciatus. Additionally, we found that CO2-baited no-light CDC light traps collected a larger diversity of mosquito species than Gravid traps.

scholarly journals Effects of the COVID-19 Lockdown on Urban Light Emissions: Ground and Satellite Comparison

2021 ◽  
Vol 13 (2) ◽  
pp. 258
Author(s):  
Máximo Bustamante-Calabria ◽  
Alejandro Sánchez de Miguel ◽  
Susana Martín-Ruiz ◽  
Jose-Luis Ortiz ◽  
José M. Vílchez ◽  
...  
Keyword(s):  
Economic Activity ◽  
Primary Source ◽  
Clear Correlation ◽  
Light Pollution ◽  
Nocturnal Activity ◽  
Empirical Expression ◽  
Anthropogenic Aerosol ◽  
The Earth ◽  
Sky Brightness ◽  
The City

‘Lockdown’ periods in response to COVID-19 have provided a unique opportunity to study the impacts of economic activity on environmental pollution (e.g., NO2, aerosols, noise, light). The effects on NO2 and aerosols have been very noticeable and readily demonstrated, but that on light pollution has proven challenging to determine. The main reason for this difficulty is that the primary source of nighttime satellite imagery of the earth is the SNPP-VIIRS/DNB instrument, which acquires data late at night after most human nocturnal activity has already occurred and much associated lighting has been turned off. Here, to analyze the effect of lockdown on urban light emissions, we use ground and satellite data for Granada, Spain, during the COVID-19 induced confinement of the city’s population from 14 March until 31 May 2020. We find a clear decrease in light pollution due both to a decrease in light emissions from the city and to a decrease in anthropogenic aerosol content in the atmosphere which resulted in less light being scattered. A clear correlation between the abundance of PM10 particles and sky brightness is observed, such that the more polluted the atmosphere the brighter the urban night sky. An empirical expression is determined that relates PM10 particle abundance and sky brightness at three different wavelength bands.

scholarly journals Phylogenetic Complexity of Morphologically Identified Anopheles squamosus in Southern Zambia

Insects ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 146
Author(s):  
Jordan Hoffman ◽  
Ilinca Ciubotariu ◽  
Limonty Simubali ◽  
Twig Mudenda ◽  
William Moss ◽  
...  
Keyword(s):  
Phylogenetic Relationships ◽  
Catchment Area ◽  
Control Strategies ◽  
Light Trap ◽  
Current Control ◽  
Control Measures ◽  
Morphological Identification ◽  
The Past ◽  
Blood Meal Source ◽  
Residual Malaria Transmission

Despite dramatic reductions in malaria cases in the catchment area of Macha Hospital, Choma District, Southern Province in Zambia, prevalence has remained near 1–2% by RDT for the past several years. To investigate residual malaria transmission in the area, this study focuses on the relative abundance, foraging behavior, and phylogenetic relationships of Anopheles squamosus specimens. In 2011, higher than expected rates of anthropophily were observed among “zoophilic” An. squamosus, a species that had sporadically been found to contain Plasmodium falciparum sporozoites. The importance of An. squamosus in the region was reaffirmed in 2016 when P. falciparum sporozoites were detected in numerous An. squamosus specimens. This study analyzed Centers for Disease Control (CDC) light trap collections of adult mosquitoes from two collection schemes: one performed as part of a reactive-test-and-treat program and the second performed along a geographical transect. Morphological identification, molecular verification of anopheline species, and blood meal source were determined on individual samples. Data from these collections supported earlier studies demonstrating An. squamosus to be primarily exophagic and zoophilic, allowing them to evade current control measures. The phylogenetic relationships generated from the specimens in this study illustrate the existence of well supported clade structure among An. squamosus specimens, which further emphasizes the importance of molecular identification of vectors. The primarily exophagic behavior of An. squamosus in these collections also highlights that indoor vector control strategies will not be sufficient for elimination of malaria in southern Zambia.

scholarly journals An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 343
Author(s):  
Kim Bjerge ◽  
Jakob Bonde Nielsen ◽  
Martin Videbæk Sepstrup ◽  
Flemming Helsing-Nielsen ◽  
Toke Thomas Høye
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Vision System ◽  
Low Cost ◽  
Light Trap ◽  
Automatic Monitoring ◽  
Light Sources ◽  
Monitoring Methods ◽  
Computer Vision System ◽  
Substantial Investment

Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the monitoring data, which hampers the ecological interpretation. This paper presents a portable computer vision system capable of attracting and detecting live insects. More specifically, the paper proposes detection and classification of species by recording images of live individuals attracted to a light trap. An Automated Moth Trap (AMT) with multiple light sources and a camera was designed to attract and monitor live insects during twilight and night hours. A computer vision algorithm referred to as Moth Classification and Counting (MCC), based on deep learning analysis of the captured images, tracked and counted the number of insects and identified moth species. Observations over 48 nights resulted in the capture of more than 250,000 images with an average of 5675 images per night. A customized convolutional neural network was trained on 2000 labeled images of live moths represented by eight different classes, achieving a high validation F1-score of 0.93. The algorithm measured an average classification and tracking F1-score of 0.71 and a tracking detection rate of 0.79. Overall, the proposed computer vision system and algorithm showed promising results as a low-cost solution for non-destructive and automatic monitoring of moths.

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