Tracing the origin of extra virgin olive oils by infrared spectroscopy and chemometrics: a case study
Research output: Contribution to journal › Journal article › peer-review
Standard
Tracing the origin of extra virgin olive oils by infrared spectroscopy and chemometrics : a case study. / Bevilacqua, Marta; Bucci, Remo; Magrì, Andrea D.; Magrì, Antonio L.; Marini, Federico.
In: Analytica Chimica Acta, Vol. 717, 2012, p. 39-51.Research output: Contribution to journal › Journal article › peer-review
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - JOUR
T1 - Tracing the origin of extra virgin olive oils by infrared spectroscopy and chemometrics
T2 - a case study
AU - Bevilacqua, Marta
AU - Bucci, Remo
AU - Magrì, Andrea D.
AU - Magrì, Antonio L.
AU - Marini, Federico
PY - 2012
Y1 - 2012
N2 - In this paper, the potential of coupling mid- and near-infrared spectroscopic fingerprinting techniques and chemometric classification methods for the traceability of extra virgin olive oil samples from the PDO Sabina was investigated. To this purpose, two different pattern recognition algorithm representative of the discriminant (PLS-DA) and modeling (SIMCA) approach to classification were employed. Results obtained after processing the spectroscopic data by PLS-DA evidenced a rather high classification accuracy, NIR providing better predictions than MIR (as evaluated both in cross-validation and on an external test set). SIMCA confirmed these results and showed how the category models for the class Sabina can be rather sensitive and highly specific. Lastly, as samples from two harvesting years (2009 and 2010) were investigated, it was possible to evidence that the different production year can have a relevant effect on the spectroscopic fingerprint. Notwithstanding this, it was still possible to build models that are transferable from one year to another with good accuracy.
AB - In this paper, the potential of coupling mid- and near-infrared spectroscopic fingerprinting techniques and chemometric classification methods for the traceability of extra virgin olive oil samples from the PDO Sabina was investigated. To this purpose, two different pattern recognition algorithm representative of the discriminant (PLS-DA) and modeling (SIMCA) approach to classification were employed. Results obtained after processing the spectroscopic data by PLS-DA evidenced a rather high classification accuracy, NIR providing better predictions than MIR (as evaluated both in cross-validation and on an external test set). SIMCA confirmed these results and showed how the category models for the class Sabina can be rather sensitive and highly specific. Lastly, as samples from two harvesting years (2009 and 2010) were investigated, it was possible to evidence that the different production year can have a relevant effect on the spectroscopic fingerprint. Notwithstanding this, it was still possible to build models that are transferable from one year to another with good accuracy.
KW - Chemometrics
KW - Extra virgin olive oil
KW - Food traceability
KW - Infrared spectroscopy
KW - Partial least squares discriminant analysis (PLS-DA)
KW - SIMCA
U2 - 10.1016/j.aca.2011.12.035
DO - 10.1016/j.aca.2011.12.035
M3 - Journal article
AN - SCOPUS:84856430038
VL - 717
SP - 39
EP - 51
JO - Analytica Chimica Acta
JF - Analytica Chimica Acta
SN - 0003-2670
ER -
ID: 228375809