- 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
- Language:
-
Inglese
- Format:
-
A Stampa
- Referee:
-
Sì
- 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
- 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:
-
May 18, 2021
- 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.
5
,
2009
,
pp. 1443-1452
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