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Do Different LED Colours Influence Sand Fly Collection by Light Trap in the Mediterranean?

Gabriella GaglioEttore NapoliFrancesca ArfusoJessica Maria AbbateSalvatore GiannettoEmanuele Brianti
Published in: BioMed research international (2018)
Light traps represent the most used attractive system to collect and monitor phlebotomine sand flies. Recent studies have suggested that light traps can be easily upgraded by the use of light-emitting diode (LED) with positive effects on trap design, weight, and battery life. However, scant data on the effect of different LED colours on the attractiveness to phlebotomine sand fly species are available in literature. In this study, the capture performances of light traps equipped with different LED colours on phlebotomine sand fly species indigenous in the Mediterranean area were evaluated. Phlebotomine sand fly collections were performed using a classical light trap (CLT), equipped with a traditional incandescent lamp, and five Laika 4.0 light traps supplied, each with LED of different colours and wavelengths: (i) white; (ii) red; (iii) green; (iv) blue; (v) UV. Light traps were set for three consecutive nights fortnightly from May to October 2017 and climate data recorded using a meteorological station. A total of 411 phlebotomine sand flies (191 males and 220 females), belonging to three different species, namely, Phlebotomus perniciosus (n= 298, 141 males and 157 females), Sergentomyia minuta (n=110, 48 males and 62 females), and Phlebotomus neglectus (n=3, 2 males and 1 females) were collected. Abundance of capture was influenced by colours of LED and time. The highest number of phlebotomine sand flies was captured on June (P<0.01) and by UV LED (P<0.01). As regard to species, P. perniciosus was mainly captured by UV LED on June (P<0.01). No effect of time (P>0.05) or LED colour (P>0.05) was recorded for S. minuta and P. neglectus. According to the results of the present study light trap equipped with UV LED can represent an effective tool for the capture of sand fly species in the Mediterranean area.
Keyphrases
  • light emitting
  • drinking water
  • drosophila melanogaster
  • systematic review
  • physical activity
  • body mass index
  • climate change
  • machine learning
  • weight loss
  • deep learning
  • big data
  • artificial intelligence