Publications

Pollen discrimination and classification by Fourier Transform Infrared (FT-IR) microspectroscopy and machine learning  (2009)

Authors:
Dell'Anna R.; Lazzeri P.; Frisanco M. ; Monti F. ;Malvezzi Campeggi F. ; Gottardini E. ;Bersani M.
Title:
Pollen discrimination and classification by Fourier Transform Infrared (FT-IR) microspectroscopy and machine learning
Year:
2009
Type of item:
Articolo in Rivista
Tipologia ANVUR:
Articolo su rivista
Nations of authors:
ITALIA
Language:
Inglese
Format:
A Stampa
Referee:
Name of journal:
Analytical and Bioanalytical Chemistry
ISSN of journal:
1618-2642
N° Volume:
394
Number or Folder:
5
:
Springer Verlag
Page numbers:
1443-1452
Code PMID:
19396429
Keyword:
FT-IR microspectroscopy - Allergic pollen - Supervised and unsupervised learning methods - Aerobiological monitoring networks
Short description of contents:
The discrimination and classification of allergy-relevant pollen was studied for the first time by mid-infrared Fourier transform infrared (FT-IR) microspectroscopy together with unsupervised and supervised multivariate statistical methods. Pollen samples of 11 different taxa were collected, whose outdoor air concentration during the flowering time is typically measured by aerobiological monitoring networks. Unsupervised hierarchical cluster analysis provided valuable information about the reproducibility of FT-IR spectra of the same taxon acquired either from one pollen grain in a 25 x 25 microm2 area or from a group of grains inside a 100 x 100 microm2 area. As regards the supervised learning method, best results were achieved using a K nearest neighbors classifier and the leave-one-out cross-validation procedure on the dataset composed of single pollen grain spectra (overall accuracy 84%). FT-IR microspectroscopy is therefore a reliable method for discrimination and classification of allergenic pollen. The limits of its practical application to the monitoring performed in the aerobiological stations were also discussed.
Product ID:
53013
Handle IRIS:
11562/338127
Deposited On:
March 21, 2012
Last Modified:
November 2, 2016
Bibliographic citation:
Dell'Anna R.; Lazzeri P.; Frisanco M. ; Monti F. ;Malvezzi Campeggi F. ; Gottardini E. ;Bersani M., Pollen discrimination and classification by Fourier Transform Infrared (FT-IR) microspectroscopy and machine learning «Analytical and Bioanalytical Chemistry» , vol. 394 , n. 52009pp. 1443-1452

Consulta la scheda completa presente nel repository istituzionale della Ricerca di Ateneo IRIS

Related projects
Title Department Managers
Sviluppo di metodologie alternative per l'identificazione e la determinazione quantitativa di pollini allergenici Department Informatica Francesca Monti
<<back

Activities

Research facilities