@article{fdi:010077999,
  title = {{C}hagas disease vectors identification using visible and near-infrared spectroscopy},
  author = {{D}epick{\`e}re, {S}. and {R}avelo-{G}arcia, {A}. {G}. and {L}ardeux, {F}r{\'e}d{\'e}ric},
  editor = {},
  language = {{ENG}},
  abstract = {{C}hagas disease, caused by the parasite {T}rypanosoma cruzi, is widespread in {L}atin {A}merica, where the disease remains one of the major public health problems. {T}his condition is mostly transmitted by triatomines which are haematophagous insects all their life. {W}ith 154 species described in the world, the correct determination of the species involved in the transmission is crucial to develop efficient control strategies. {T}his can be achieved by taxonomic keys (available only for adult stages, nymphal instars must be reared), or by molecular techniques. {B}oth are time and/or money consuming, showing the needs of new identification tools, especially for nymphal instars which are the most frequently found on the field. {V}isible and near-infrared spectroscopy ({VIS}-{NIR}), used successfully these last years in various organisms' determination, was applied on a sample of three species from {B}olivia: {T}riatoma infestans, {T}riatoma sordida and {T}riatoma guasayana. {T}he spectrum of the dorsal part of the head from nymphal instars and adult stages was taken for each specimen of each species. {D}ifferent methods of preprocessing and selection of variables (wavelengths) were tested to find the best model of classification for the three species. {E}ach model was evaluated by different indices: accuracy, specificity, and {F}1 score. {T}he comparison of the performance of each model evidenced that the best results were obtained when using a short spectrum (400-2000 nm) without pre-processing. {A} total of 32 components were retained by tuning, and 933 wavelengths were kept by the backward feature selection algorithm. {A}pplying it on a new sample of insects, this model showed a global accuracy of 97.2% (95.0-98.6). {T}he {F}1 score was greater than 0.95, and the specificity greater than 0.94 for all the species. {F}or the first time, a tool is available to quickly identify and with a high accuracy nymphal instars and adults of triatomines.},
  keywords = {{S}pecies determination ; {T}riatominae ; {C}hagas disease ; {M}achine learning ; {C}lassification ; {VIS}-{NIRS} ; {BOLIVIE}},
  booktitle = {},
  journal = {{C}hemometrics and {I}ntelligent {L}aboratory {S}ystems},
  volume = {197},
  numero = {},
  pages = {art. 103914 [9 p.]},
  ISSN = {0169-7439},
  year = {2020},
  DOI = {10.1016/j.chemolab.2019.103914},
  URL = {https://www.documentation.ird.fr/hor/fdi:010077999},
}