Using WorldView 2 Vis-NIR MSI Imagery to Support - Exelis VIS
UV-VIS-NIR absorption spectroscopy and …UV-VIS-NIR absorption spectroscopy and multivariate data...
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Proceedings of the Symposium on Photonics Technologies for 7 th Framework Program Wroclaw 12-14 October 2006 488 UV-VIS-NIR absorption spectroscopy and multivariate data processing for fingerprinting extra virgin olive oils A.G. Mignani * a , L. Ciaccheri a , H. Thienpont b , H. Ottevaere b , A. Cimato c , C. Attilio c a CNR-Institute of Applied Physics ‘Nello Carrara’, Sesto Fiorentino (FI), Italy b Vrije Universiteit Brussel, Department of Applied Physics and Photonics, Belgium c CNR-Trees and Timber Institute, Sesto Fiorentino (FI), Italy ABSTRACT Italian extra virgin olive oils bearing labels of certified area of origin were considered. Their multispectral digital signature was measured by means of absorption spectroscopy in the 200-1700 nm spectral range. The spectral data were processed by means of multivariate analysis and plotted on a 2D classification map. The map showed sharp clusters according to the oil’s geographical origin, thus demonstrating the potentials of UV-VIS-NIR spectroscopy for optical fingerprinting. Keywords: UV-VIS-NIR spectroscopy, multivariate data processing, olive oil 1. INTRODUCTION Industrial process control depends increasingly on diagnostic systems capable of distinguishing products and identifying them through reliable methods. In the food sector, inexpensive diagnostic systems are needed to distinguish high-value products in order to protect their brands and to ensure that food peculiarities and safety requisites are met. Italian extra virgin olive oils bearing labels of certified area of origin are characterized by distinctive taste and exceptional nutritional properties. These peculiarities derive from the kind of olives used and the traditional, low- mechanization production means. New methods and technologies are envisaged for qualifying and certifying these oils, to protect both producers and consumers 1-5 . This work presents a method for measuring the multispectral digital identity of extra virgin olive oils bearing labels of certified area of origin. The method complements conventional laboratory procedures that monitor key production chemical parameters. It was applied to 85 samples of extra virgin olive oil produced in the regions of Sicily, Calabria, and Tuscany during the 2005-2006 season. The differences in the oils’ taste and nutritional properties derived from variation in geographical origin, ‘cultivar’, climate, and harvest time. The samples were fingerprinted by UV, VIS, and NIR absorption spectroscopy covering the 200-1700 nm spectral range. A low-cost and compact spectrometric device, precursor to an online diagnostic system, was used. The spectral data were processed by means of multivariate analysis and plotted on a 2D classification map. The map shows that the oil samples are sharply clustered according to geographical origin, thus demonstrating the potentials of UV, VIS, and NIR absorption spectroscopy for optical fingerprinting. 2. INSTRUMENTATION AND DATA PROCESSING Absorption spectroscopy in the 200-1700 nm spectral range was performed by means of the experimental set-up sketched in Figure 1. It consisted of a deuterium/halogen lamp (Micropack Inc., DH-2000-BAL) coupled to a fiber optic bundle, which provided illumination to a quartz cuvette containing the oil sample. Another bifurcated fiber optic bundle was used to detect the oil’s transmitted light intensity and to split it into two spectrometers for UV-VIS (Ocean Optics * [email protected]; phone 0039 055 522-6361
Transcript of UV-VIS-NIR absorption spectroscopy and …UV-VIS-NIR absorption spectroscopy and multivariate data...
Proceedings of the Symposium on Photonics Technologies for 7th Framework Program Wroclaw 12-14 October 2006
488
UV-VIS-NIR absorption spectroscopy and multivariate data processing for fingerprinting extra virgin olive oils
A.G. Mignani ∗ a, L. Ciaccheri a, H. Thienpont b, H. Ottevaere b, A. Cimato c, C. Attilio c
a CNR-Institute of Applied Physics ‘Nello Carrara’, Sesto Fiorentino (FI), Italy b Vrije Universiteit Brussel, Department of Applied Physics and Photonics, Belgium
c CNR-Trees and Timber Institute, Sesto Fiorentino (FI), Italy
ABSTRACT
Italian extra virgin olive oils bearing labels of certified area of origin were considered. Their multispectral digital signature was measured by means of absorption spectroscopy in the 200-1700 nm spectral range. The spectral data were processed by means of multivariate analysis and plotted on a 2D classification map. The map showed sharp clusters according to the oil’s geographical origin, thus demonstrating the potentials of UV-VIS-NIR spectroscopy for optical fingerprinting. Keywords: UV-VIS-NIR spectroscopy, multivariate data processing, olive oil
1. INTRODUCTION Industrial process control depends increasingly on diagnostic systems capable of distinguishing products and identifying them through reliable methods. In the food sector, inexpensive diagnostic systems are needed to distinguish high-value products in order to protect their brands and to ensure that food peculiarities and safety requisites are met. Italian extra virgin olive oils bearing labels of certified area of origin are characterized by distinctive taste and exceptional nutritional properties. These peculiarities derive from the kind of olives used and the traditional, low-mechanization production means. New methods and technologies are envisaged for qualifying and certifying these oils, to protect both producers and consumers 1-5. This work presents a method for measuring the multispectral digital identity of extra virgin olive oils bearing labels of certified area of origin. The method complements conventional laboratory procedures that monitor key production chemical parameters. It was applied to 85 samples of extra virgin olive oil produced in the regions of Sicily, Calabria, and Tuscany during the 2005-2006 season. The differences in the oils’ taste and nutritional properties derived from variation in geographical origin, ‘cultivar’, climate, and harvest time. The samples were fingerprinted by UV, VIS, and NIR absorption spectroscopy covering the 200-1700 nm spectral range. A low-cost and compact spectrometric device, precursor to an online diagnostic system, was used. The spectral data were processed by means of multivariate analysis and plotted on a 2D classification map. The map shows that the oil samples are sharply clustered according to geographical origin, thus demonstrating the potentials of UV, VIS, and NIR absorption spectroscopy for optical fingerprinting.
2. INSTRUMENTATION AND DATA PROCESSING Absorption spectroscopy in the 200-1700 nm spectral range was performed by means of the experimental set-up sketched in Figure 1. It consisted of a deuterium/halogen lamp (Micropack Inc., DH-2000-BAL) coupled to a fiber optic bundle, which provided illumination to a quartz cuvette containing the oil sample. Another bifurcated fiber optic bundle was used to detect the oil’s transmitted light intensity and to split it into two spectrometers for UV-VIS (Ocean Optics
∗ [email protected]; phone 0039 055 522-6361
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Inc., HR4000) and NIR (Ocean Optics Inc., NIR512) spectroscopy, respectively 6. The working ranges of the spectrometers were slightly overlapping, with different spectral resolution. The 200-1100 nm UV-VIS range offered a high resolution of 0.27 nm, while the 900-1700 nm NIR range provided a lower resolution of 1.7 nm. Therefore, each oil sample was characterized by 4160 spectral data. The spectral data were processed by means of multivariate data analysis techniques 7-9. Principal Component Analysis (PCA) was used for dimensionality reduction, while Linear Discriminant Analysis (LDA) was used for oil classification. The data processing protocol considered the following steps:
1. Two matrices were created by means of the UV-VIS and NIR transmission spectra, respectively, each row representing the spectrum of a different oil sample.
2. The two matrices were separately processed by means of PCA, to compress the relevant information into a limited numbers of features (scores), thus creating two score-matrices, for UV-VIS and NIR PCA-data, respectively.
3. The two score-matrices were concatenated along the 2nd dimension, thus operating the UV-VIS and NIR data fusion.
4. LDA was applied to the joint matrix, extracting two Linear Discriminating Functions, DF1 and DF2, for oil classification.
5. Finally, DF1 and DF2 were used to build a 2D map, each point of which representing an oil with its own peculiar spectral characteristics.
Figure 1: Experimental set-up for oil’s spectroscopy.
3. EXPERIMENTAL RESULTS A library of 85 oil samples from the 2005-2006 harvesting was considered. They were produced in three different Italian regions, Sicilia (deep South of Italy), Calabria (South of Italy), and Toscana (Central-North part of Italy), respectively. These oils have distinctive tastes not only because of the different ‘cultivar’, but also because of the different weather conditions and harvesting methods, the latter deriving primarily from local traditions. The transmission spectra of the full library (Figure 2) show at a glance different spectral signatures for the various oils. The main differences in the UV-VIS region are due to the diverse content of phenol-derivatives, carotenoids and chlorophylls, while the little differences in the NIR region are mainly caused by the diverse fatty-acid content. Three PCAs were sufficient to model the NIR spectra, explaining the 99% of the data variance. The UV-VIS spectra showed a more complex structure requiring four PCAs to describe the data, with an explained variance of 93%. The data matrix for LDA was, therefore, made of 7 columns. Figure 3 shows the result of multivariate data analysis, that is the 2D map in the DF1-2 space. A very good clustering is achieved according to the oil’s geographic region of origin and production. Although the oil’s library was not sufficiently
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populated to create crowded calibration and validation sets, an attempt of predicting the geographic origin was made by considering 65 and 20 oil samples for calibration and validation, respectively. The resulting standard-error-prediction was less than 5%, which can be considered a successful result.
4. PERSPECTIVES A low-cost spectrometric device and a suitable multivariate data processing allowed to clustering a bunch of Italian extra virgin olive oils according to the geographic region of origin and production. These preliminary fingerprinting results demonstrate the possibility of implementing an authentication device based on cheap microoptic technologies, and the use of optical fibers is precursor to an online diagnostic system. Further development of this research will consider the correlation of spectral data with the oil’s chemical analysis looking for the achievement of a complete traceability by means of optical techniques.
Figure 2: UV-VIS-NIR spectral signatures of the oil’s library.
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Figure 3: 2D map in the DF1-2 space, clustering the extra virgin olive oils
according to the geographic region of origin and production.
ACKNOWLEDGEMENTS The European Network of Excellence ‘NEMO’, the CNR Short Term Mobility Programme, and the Regional Board of Sicily (Assessorato Agricoltura e Foreste, Servizio IX°, Palermo) are acknowledged for partial financial support.
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6. http://www.oceanoptics.com/ . 7. H. Martens, T. Maes, Multivariate Calibration , John Wiley and Sons, Chichester UK, 1989. 8. M.A. Adams, Chemometrics in Analytical Spectroscopy, The Royal Society of Chemistry, Letchworth UK,
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Chemometrics and Qualimetrics, Elsevier Science BV, Amsterdam, 1998.
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