There is a g rowing wealthy niche market for some extra virgin olive oil of special organoleptic characteristics related to the traditional cultivars and cultivation methods[1]. It is of special importance to develop analytical methods to recognize and protect these valuable oils. Several authors studied the possibility to characterize olive oil by means of aspecific measurements with respect to the orchard location or the vegetal variety. NIR and MIR signals were analysed by LDA to assess the botanical variety of Italian monovarietal olive oil [2]. Ligurian oils were classified combining head-space mass spectrometry (electronic nose), UV–visible and NIR spectroscopy [3]. Forina and coworkers [4] investigated the possibility to compute QDA and SIMCA models from UV-Vis spectroscopy to classify the West Liguria PDO “Riviera Ligure-Riviera dei fiori” extra virgin olive oil. In the present work we investigate the possibility to recognize the geographical and/or varietal origin of extra virgin olive oil (EVOO), obtained from three olive variety of Marche in central Italy, through instrumental methods and chemometric data treatments. Sampling were conducted in restricted areas typical for each olive variety, in particular we got oil of Mignola 193in the landscape near Cingoli, Piantone di Mogliano around Mogliano and Coroncina near Caldarola; all samples were provided by the farmers that guarantee the authenticity. Spectroscopic measurements were performed: UV-Vis spectra were acquired with a UV-vis Varian Cary 50 Scan spectrophotometer the IR spectra were obtained with a P erkin Elmer spectrum 100 F T-IR with ATR and the X-ray fluorescence was measured by a E D-XRF Shimadzu 800HS2 with a 10 mm collimator. Some analyzing methods as PLS-DA, LDA, SIMCA and UNEQ were applied to the data to compare their performance. The considered spectroscopies were suitable to classify the samples, as shown in the figure, but they have different prediction ability. UV-Vis spectroscopy coupled to LDA or PLS-DA data treatment permitted both a good classification and prediction ability.

Investigation on the possibility of characterizing three monovarietal extravirgin olive oil from Marche by spectroscopic and chemometric method.

Paolo Conti;Mario Berrettoni;Silvia Zamponi
2013-01-01

Abstract

There is a g rowing wealthy niche market for some extra virgin olive oil of special organoleptic characteristics related to the traditional cultivars and cultivation methods[1]. It is of special importance to develop analytical methods to recognize and protect these valuable oils. Several authors studied the possibility to characterize olive oil by means of aspecific measurements with respect to the orchard location or the vegetal variety. NIR and MIR signals were analysed by LDA to assess the botanical variety of Italian monovarietal olive oil [2]. Ligurian oils were classified combining head-space mass spectrometry (electronic nose), UV–visible and NIR spectroscopy [3]. Forina and coworkers [4] investigated the possibility to compute QDA and SIMCA models from UV-Vis spectroscopy to classify the West Liguria PDO “Riviera Ligure-Riviera dei fiori” extra virgin olive oil. In the present work we investigate the possibility to recognize the geographical and/or varietal origin of extra virgin olive oil (EVOO), obtained from three olive variety of Marche in central Italy, through instrumental methods and chemometric data treatments. Sampling were conducted in restricted areas typical for each olive variety, in particular we got oil of Mignola 193in the landscape near Cingoli, Piantone di Mogliano around Mogliano and Coroncina near Caldarola; all samples were provided by the farmers that guarantee the authenticity. Spectroscopic measurements were performed: UV-Vis spectra were acquired with a UV-vis Varian Cary 50 Scan spectrophotometer the IR spectra were obtained with a P erkin Elmer spectrum 100 F T-IR with ATR and the X-ray fluorescence was measured by a E D-XRF Shimadzu 800HS2 with a 10 mm collimator. Some analyzing methods as PLS-DA, LDA, SIMCA and UNEQ were applied to the data to compare their performance. The considered spectroscopies were suitable to classify the samples, as shown in the figure, but they have different prediction ability. UV-Vis spectroscopy coupled to LDA or PLS-DA data treatment permitted both a good classification and prediction ability.
2013
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11581/424619
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