EAT-by-LIGHT: Fiber-Optic and Micro-Optic Devices for Food Quality and Safety Assessment

1342 IEEE SENSORS JOURNAL, VOL. 8, NO. 7, JULY 2008

EAT-by-LIGHT: Fiber-Optic and Micro-OpticDevices for Food Quality and Safety Assessment

Anna Grazia Mignani, Leonardo Ciaccheri, Costanza Cucci, Andrea Azelio Mencaglia, Antonio Cimato,Cristina Attilio, Heidi Ottevaere, Hugo Thienpont, Member, IEEE, Roberto Paolesse, Marco Mastroianni,Donato Monti, Marco Gerevini, Giovanna Buonocore, Matteo Alessandro Del Nobile, Annalisa Mentana,

Maria Francesca Grimaldi, Chiara Dall’Asta, Andrea Faccini, Gianni Galaverna, and Arnaldo Dossena

Invited Paper

Abstract—A selection is presented of fiber-optic and micro-opticdevices that have been designed and tested for guaranteeing thequality and safety of typical foods, such as extra virgin olive oil,beer, and milk. Scattered colorimetry is used to authenticate var-ious types of extra virgin olive oil and beer, while a fiber-optic-based device for UV-VIS-NIR absorption spectroscopy is exploitedin order to obtain the hyperspectral optical signature of olive oil.This is done not only for authentication purposes, but also so as tocorrelate the spectral data with the content of fatty acids, whichare important nutritional factors. A micro-optic sensor for the de-tection of olive oil aroma that is capable of distinguishing differentageing levels of extra virgin olive oil is also presented. It shows ef-fective potential for acting as a smart cap of bottled olive oil inorder to achieve a nondestructive olfactory perception of oil ageing.Lastly, a compact portable fluorometer for the rapid monitoring ofthe carcinogenic M1 aflatoxin in milk, is experimented.

Index Terms—Absorption spectroscopy, aflatoxins, beer, fluores-cence spectroscopy, food authentication, milk, olive oil, scatteredcolorimetry.

I. BETTER FOOD FOR BETTER HEALTH

T HE quality and safety of the food we eat attracts a greatdeal of publicity, and is high on the list of public con-

cerns. This highly emotional issue leads to a more “aware” con-

Manuscript received July 20, 2007; accepted February 14, 2008. PublishedJuly 16, 2008 (projected). This work was supported by the EU SM&T Pro-gramme, under Contract SMT4-CT972157 “OPTIMO”; Regione Toscana, ITT“CARABIOTEC”; MIUR-FIRB, under Contract RBNE01KZZM “BIOSENS”;EU FP6 Network of Excellence Contract 003887 “NEMO”; CNR Short TermMobility Program; DWTC-IAP, FWO Vlaanderen and the OZR of the VrijeUniversiteit Brussel; and Regione Sicilia, Assessorato Agricoltura e Foreste,Servizio IX , Palermo. The work of H. Ottevaere was supported by the FlemishFund for Scientific Research (FWO) under the “Postdoctoraal Onderzoeker”Fellowship. The associate editor coordinating the review of this paper and ap-proving it for publication was Prof. Brian Culshaw.

A. G. Mignani, L. Ciaccheri, C. Cucci, and A. A. Mencaglia are with theCNR-IFAC, Sesto Fiorentino (FI), Italy (e-mail: [email protected]).

A. Cimato and C. Attilio are with the CNR-IVALSA, Sesto Fiorentino (FI),Italy.

H. Ottevaere and H. Thienpont are with the Department of Applied Physicsand Photonics, Vrije Universiteit Brussel, Brussels, Belgium.

R. Paolesse, M. Mastroianni, and D. Monti are with the Dipartimento diScienze e Tecnologie Chimiche, Università di Roma Tor Vergata, Roma, Italy.

M. Gerevini is with the Tecnoalimenti S.C.p.A., Milano, Italy.G. Buonocore is with the CNR-IMCB, Napoli, Italy.M. A. Del Nobile, A. Mentana, and M. F. Grimaldi are with the Dipartimento

di Scienze degli Alimenti, Università di Foggia, Foggia, Italy.C. Dall’Asta, A. Faccini, G. Galaverna, and A. Dossena are with the Diparti-

mento di Chimica Organica e Industriale, Università di Parma, Parma, Italy.Color versions of one or more of the figures in this paper are available online

at http://ieeexplore.ieee.org.Digital Object Identifier 10.1109/JSEN.2008.926971

sumption of food, and a demand for fresher, better-tasting, safer,healthier, and higher quality food is escalating in every country.As part of a healthier lifestyle, people of all ages are being en-couraged to increase their consumption of fresh or minimallyprocessed foods [1]–[4].

We live in a global marketplace, and we eat a great variety offoods from many different countries. Many fruits, vegetables,and dairy products now on the market were not available tenyears ago. These are grown using a variety of production prac-tices, from small organic operations to large-scale mechanizedfarms. On the one hand, produce buyers want to be reassuredthat farmers are taking reasonable steps to ensure that the pro-duce delivered is safe and free from human pathogenic bacteriaand mycotoxins. On the other hand, consumers and food han-dlers (restaurateurs, retailers, etc.) need to know that the foodwhich they eat and serve is safe and healthy.

In addition to conventional analytical techniques, new instru-ments and tools are being envisaged that are capable of reducingthe costs of quality control and of alerting people of the onsetof risks. Also, new instruments for traceability and certifica-tion are needed, especially those based on low-cost techniques.The associations of producers and small farmers are increas-ingly demanding cheap and effective control devices, whichare mainly considered as marketing tools for the protection of“locally-grown” traditional foods. These foods are renowned,and need to be protected from adulteration and imitation, inview of their high qualitative standards, safety, and nutritionalexcellence.

Sensors based on fiber-optic and micro-optic techniques arefound to offer effective and low-cost solutions for many indus-trial and process control applications. Especially in the case ofspectroscopy-based devices, the intrinsic optical and mechan-ical characteristics of optical fibers, together with the wide avail-ability of bright LEDs and portable spectrometers, have made itpossible to implement compact instrumentation with a high po-tential for many applications in the food sector.

This paper presents a selection of spectroscopy-based fiber-optic and micro-optic devices that have been designed and testedfor monitoring the quality and safety of typical foods, such asextra virgin olive oil, beer, and milk.

• Multi-angle and multi-wavelength absorption spec-troscopy in the visible spectral range, i.e., scatteredcolorimetry, has been experimented to gather informationon the entire color and turbidity content of liquids. This

1530-437X/$25.00 © 2008 IEEE

MIGNANI et al.: EAT-BY-LIGHT 1343

Fig. 1. Scattered colorimetry technique—left: the working principle; right: diagram of the instrumentation.

technique has been used to classify extra virgin olive oilsaccording to their geographic area of origin, and for adigital mapping of Belgian beers, in order to group theseaccording to assigned classes.

• A low-cost fiber-optic-based device for wide-range absorp-tion spectroscopy has been experimented to measure the hy-perspectral optical signature of extra virgin olive oils. Thiswas done not only in order to predict their geographic origin,but also to correlate the spectral data to the content of themost important fatty acids, essential nutritional factors.

• A micro-optic sensor for oil aroma detection, that is ca-pable of distinguishing different ageing levels of extravirgin olive oils, has been implemented. The sensor uses anarray of metalloporphyrin-based materials, the absorptionspectra of which act as oil-quality indicators. The experi-mental results have shown the possibility of implementinga “smart cap,” fitted by the metalloporphyrins as sensors,for achieving a nondestructive olfactory perception of oilageing during the bottle shelf life.

• A compact, easy-to-handle and portable fluorometer hasbeen tested for the rapid detection of the carcinogenic M1aflatoxin in milk. This sensor is able to identify the legallimits of toxin, both 25 and 50 ppt, for baby and adult food,respectively, without any pre-concentration of the samplebeing necessary.

II. SCATTERED COLORIMETRY FOR THE DIGITAL MAPPING AND

AUTHENTICATION OF EXTRA VIRGIN OLIVE OIL AND BEER

A. Working Principle

Scattered colorimetry is a novel technique that makes use ofmulti-wavelength and multi-angle absorption spectroscopy. Itis performed in the visible spectral range in order to simultane-ously measure the entire content of color and turbidity of liquids,that is, in practice, the appearance [5].

Although appearance is usually referred to a visual perception,scattered colorimetry determines appearance objectively bymeans of a measuring instrument. It does this in such a way that itdoes away with subjectivity. In addition, in many cases, scatteredcolorimetry not only provides information regarding visual per-ception, but also indicates special characteristics such as qualityand, in the case of mixtures, a breakdown of components.

Once appearance has been measured, similar liquids can bemapped, i.e., they can be classified according to similarities,and then compared. The mapping of similar liquids provides

information that is complementary to the strictly chemical dataobtained by conventional analytical tools and endows it with adigital fingerprint. Once liquids have been mapped, i.e., groupsof liquids have been created on the basis of similarities, samplesmay be associated to the appropriate classes.

B. Instrumentation

The instrumentation used for scattered colorimetry is a low-cost optoelectronic device for measuring the absorption spectraof samples at different angles, as shown in Fig. 1. It consists offour white-light LEDs that span the 450–650 nm spectral range,and a miniaturized optical fiber spectrometer that serves as adetector. The sources, which can either be fitted to the probeor guided by optical fibers, are located at an angle of 0 , 30 ,60 , and 90 with relation to the detector. The probes, with andwithoutoptical fibers, are shown in Fig. 2. The LEDs are switchedon sequentially in order to measure the transmitted and scatteredspectra.

Because scattering is a wavelength-dependent phenomenon,the transmission spectrum of turbid media, which mainly pro-vides information regarding color, is also affected by turbidity.On the other hand, the scattered spectra, which mainly provideinformation on turbidity, are also affected by color. Given thespectrometer’s spectral resolution, the sample of liquid beingtested can be characterized by means of a maximum of 184spectral values coming from the four absorption spectra, each ofwhich consists of 46 wavelengths. In practice, each sample ofliquid analyzed can be represented by a point in a space with 184dimensions.

C. Data Processing

Because scattered colorimetry is a spectroscopic method thatis inherently multivariate, a multivariate data processing wasused to achieve a reduction in data dimensionality, in order tobetter extract the significant information for sample identifica-tion and classification [6]–[9].

The spectral data were processed by means of PrincipalComponent Analysis (PCA) or Linear Discriminant Analysis(LDA), which provided the coordinates for identifying the sam-ples on two- or three-dimensional maps. PCA, which provedto be a powerful tool for explorative data analysis and for re-ducing data dimensionality, linearly combined the 184 spectraldata characterizing each sample to produce new variables orprincipal components (PCs). High order PCs had little weightin characterizing the samples, and could be disregarded with


Fig. 2. Probes for scattered colorimetry measurements—left: with LEDs directly fitted to the jig; right: with optical fibers.

Fig. 3. Absorption spectra at 0 of some samples of extra virgin olive oils.

little loss of information. In actual practice, only PC1, PC2,and PC3 were found to be significant for sample identification.When several samples were analyzed, the three-dimensionalmaps in the PC1–2–3 subspace were populated by clusters ofpoints, grouping the samples in terms of similarities in theircolor and turbidity.

In cases where PCA was unable to discriminate satisfacto-rily, LDA was used, which provided a significant reduction indata dimensionality and automatic object classification. Givenan N-class problem, the LDA extracted N-1 discriminating func-tions (DFs) from the data, which corresponded to the PCs in thePCA, but offered a better resolution in cases of poorly separatedclusters. In practice, the cluster pattern recognition method waschosen case by case, depending on the complexity and similar-ities of the spectral data.

D. Mapping of Extra Virgin Olive Oils for GeographicOrigin Traceability

Italian extra virgin olive oils (EVOO) are renowned for theirtangy taste and for their nutritional benefits as monounsaturatedfats and antioxidants [10]. Suitable methods and technologiesfor qualifying and certifying oils thus need to be provided, toprotect both producers and consumers [11]. The taste and ap-pearance of oils are determined not only by weather conditions,

Fig. 4. Mapping of extra virgin olive oils according to quality and to the geo-graphic area of origin.

but also by olive-harvesting methods, which are primarily basedon local traditions. Appearance depends on both color and tur-bidity. Color is mainly determined by the pigment content ofthe olives, the type of tree they grow on, and how ripe they are


Fig. 5. Belgian beers—left: absorption spectra at 0 of different beer types; right: mapping according to type.

when they are harvested. On the other hand, turbidity is mainlyrelated to the production method.

To validate scattered colorimetry and multivariate data pro-cessing as mapping tools, we examined extra virgin olive oilsproduced according to traditional methods and compared themwith other extra virgin and non extra virgin commercial oils.The samples included 115 Tuscan and 53 Calabrian extra virginolive oils produced by traditional methods and 68 oils (58 extravirgin and 10 non extra virgin) purchased from retailers. Theoils were obtained from olives harvested during the 2002–2003season.

Fig. 3 shows the absorption spectra at 0 of some sorted sam-ples. Fig. 4 shows the three-dimensional map in the DF1-2-3subspace of the entire collection of 236 oils. The Tuscan oilsare clearly distinguishable from the other extra virgin oils, asare the Calabrian oils despite their greater spread. As expected,the cluster of non extra virgin olive oils (non EVOO) is distinctlyseparate [12].

E. Mapping of Belgian Beers

The brewing industry, both artisan breweries and large-scalecomplexes, makes use of specially-equipped laboratories for theassessment of beer quality, so that the production process canbe optimized. In addition to monitoring chemical parameters,allergens and microbiological organisms, other authenticationmethods are envisaged, in order to guarantee quality and safetyduring the production process and packaging phase.

Scattered colorimetry was validated also to map beer, whichis one of the Belgium’s greatest specialties. There are more than100 different breweries producing beers with unusual and pecu-liar tastes [13], [14]. In addition to having a different taste, eachbeer has a different and distinctive appearance. This is causednot only by the color, but also by the turbidity content. Con-sequently, the appearance of the beer can be considered as aproduct fingerprint.

A collection of 25 diverse and commercially-available Bel-gian light beers was considered and measured by means of scat-tered colorimetry. Brown beers were not considered because oftheir high absorbance, which results in a poor signal-to-noiseratio. Fig. 5-left shows the absorption spectra at 0 of all beer

Fig. 6. Experimental setup for UV-VIS-NIR absorption spectroscopy.

types. The spectral data from the absorption spectra at 0 and90 were processed by means of PCA. Fig. 5-right shows thebeer mapping in the PC1–2 subspace: the points representingthe beer samples cluster according to the four beer types: blonde,amber, red, and weiss, demonstrating that a digital mapping hasbeen successfully obtained [15].

III. HYPERSPECTRAL SIGNATURE OF LIQUIDS BY MEANS OF

WIDE-RANGE ABSORPTION SPECTROSCOPY

Absorption spectroscopy is one of the most popular andsuccessful methods in conventional analytical chemistry. Whenperformed over a wide spectral range it can lead to a productfingerprint, especially as far as the nutritional factors of thefood are concerned [16]–[18]. An attempt was made to useUV-VIS-NIR absorption spectroscopy for the authenticationof extra virgin olive oils, as well as for predicting the mostimportant fatty acids [19].

A. Instrumentation

Absorption spectroscopy in the 200–1700 nm spectral rangewas performed by means of a compact and low-cost spectro-metric device that made use of fiber optic bundles, as shownin Fig. 6. It consisted of a deuterium/halogen lamp (Micropack,


Fig. 7. UV-VIS-NIR spectral signatures of the full collection of Italian extra virgin olive oils.

Inc., DH-2000-BAL) coupled to a fiber optic bundle, which pro-vided illumination to a quartz cuvette containing the oil sample.Another bifurcated fiber optic bundle was used to detect thetransmitted light intensity, and to split it into two spectrome-ters for UV-VIS (Ocean Optics, Inc., HR4000) and NIR (OceanOptics, Inc., NIR512) spectroscopy, respectively.

The working ranges of the spectrometers were slightly over-lapped, with a different spectral resolution. The 200–1100 nmUV-VIS range offered the best resolution of 0.23 nm, while the900–1700 nm NIR range provided a lower resolution of 1.7 nm.

B. Data Processing

The spectral data were processed by means of multivariatedata analysis techniques: PCA was used for dimensionality re-duction, while LDA was used for oil classification. The data pro-cessing protocol considered the following steps.

1) Two matrices were created by means of the UV-VIS andNIR transmission spectra, respectively, with each row rep-resenting the spectrum of a different oil sample.

Fig. 8. Mapping of extra virgin olive oils in accordance with the geographicregion of origin.

2) The two matrices were separately processed by meansof PCA, in order to compress the relevant information


TABLE IBEST FITTING OF SPECTRAL DATA AND THE MOST IMPORTANT FATTY ACIDS OF THE OILS

into a limited numbers of features (scores), thus creatingtwo score-matrices, for UV-VIS and NIR PCA-data,respectively.

3) The two score-matrices were concatenated along thedimension, thus obtaining the UV-VIS and NIR datafusion.

4) LDA was applied to the joint matrix, by extracting twoLinear Discriminating functions, DF1 and DF2, for theclassification of oil.

Lastly, DF1 and DF2 were used to build a 2-D map, each pointof which represented one oil with its own peculiar spectralcharacteristics.

C. Fingerprinting Extra Virgin Olive Oils According to theGeographic Area of Origin

A collection of 85 extra virgin olive oil samples from the2005–2006 harvest was considered. The oils were produced inthree different Italian regions: Sicily (the deep south of Italy),Calabria (the south of Italy), and Tuscany (the central-northernpart of Italy), respectively. These oils have distinctive tastes, notonly because they are produced from different kind of olives,but also because of the different environmental conditions andagronomic practices in which the olives grow.

The transmission spectra of the full collection, as shown inFig. 7, reveal at a glance different spectral signatures for thevarious oils. The main differences in the UV-VIS region aredue to the different content of phenol-derivatives, carotenoidsand chlorophylls, while the small differences in the NIR regionare mainly caused by the difference in fatty acid content.

Three PCAs were sufficient to model the NIR spectra, and ex-plained 99% of the data variance. The UV-VIS spectra showeda more complex structure, and required four PCAs to describethe data, with an explained variance of 93%. The data matrix forLDA consisted, therefore, of 7 columns.

Fig. 8 shows the result of PCA/LDAprocessing, that is, the 2-Dmap in the DF1-2 space. A very good clustering was achieveddepending on the geographic region of origin of the oils.

D. Correlation of the Spectral Data With the Most ImportantNutritional Parameters of the Oils

Among the 85 samples of Italian extra virgin olive oils con-stituting the analyzed collection, those from Sicily were in themajority, with 42 samples. This subset was selected to run mul-tivariate data analyses in order to test what kind of correlationmight exist between the optical data and the chemical charac-teristics of the oils, especially the fatty acids.

To find the degree of correlation between the spectral andchemical data, the spectral data were processed by means of PLSanalysis. Both UV-VIS and NIR bands were tested as predictormatrices, and the most convenient one was then chosen.

Olive oil is a complex compound made up principally of fattyacids. These represent 98% of its composition. The related per-centage of fatty acid reveals the nutritional value of the oil itself.For these reasons, the most important fatty acids were consid-ered for correlation with the spectral data.

The set of fatty acids was obtained by using of conventionalanalytical techniques. Table I lists the fatty acids that gave thebest fitting by processing the spectral data of the NIR spectralband. The average value of fatty acids, the SECV and the cor-relation coefficient, R, between the analytically measured andpredicted values, are also listed in Table I.

As shown in Fig. 9, the best correlation was found in the totalcontent of Palmitic Stearic acids, together with a good corre-lation with Oleic acid, the main monounsaturated fatty acid ofolive oil, and with Palmitic acid. However, adequate correlationwas detected also with Eptadecanoic and Eptadecenoic acids,which usually exhibit a concentration lower than 0.5%. Thisdemonstrates that the concentration level influences the predic-tion method only slightly.

IV. SMART CAP FOR ACHIEVING A NONDESTRUCTIVE

OLFACTORY PERCEPTION OF OIL AGEING

Extra virgin olive oil is usually bottled in such a way that ahead space is left between the oil surface and the cap. During theoil’s shelf life, this head space becomes saturated by oil vapors.These vapors are true indicators of the quality of the oil, sincethe aroma changes drastically to rancid because of ageing orimproper conservation [20]. A nondestructive system would bedesirable in order to detect the state of the oil aroma during itsshelf life without having to open the bottle.

A possible design of a smart cap for olive oil aroma detectionis shown in Fig. 10. As aldehydes, such as n-hexaldehyede,octyl-aldehyde, and nonanal, are mainly responsible for therancid aroma [21], aldehyde-sensitive chromophores thatchange their colors as a function of aldehyde concentrationcan be fitted to the cap and used as optochemical sensors ofoil ageing. In practice, the olfactory pattern of the bottle headspace is converted into a color pattern of the chromophore-array,which can be detected by means of a spectrometric-based op-tical head. With this idea in mind, we implemented and testeda precursor of a smart cap [22].


Fig. 9. Correlation between the conventionally-measured fatty acids and their values as predicted by the spectral data.

Fig. 10. Smart cap for the olfactory perception of olive oil ageing.

A. Precursor of the Smart Cap—An Optical Scanner for theInterrogation of Vapor-Exposed Metalloporphyrin-BasedSensors

Metalloporphyrin-based materials are highly sensitive to awide range of volatile compounds [23]–[25]. They change theabsorption spectrum and, consequently, the color when exposedto many types of vapors, including aldehydes, although they arelacking in high selectivity. As the sensitivity and selectivity ofporphyrins are greatly influenced by the coordinated metal, anarray of metalloporphyrins made of different metals was createdand their overall response to aldehydes was processed by meansof chemometric methodologies in order to achieve an olfactoryperception. The sensors were prepared from water-ethanol met-alloporphyrin solutions that were sprayed on polyethylene disks.

The precursor of a smart cap for sniffing olive oil ageing andthe experimental setup for its testing are shown in Fig. 11. Thecontainer of extra virgin olive oil was placed on a heater to pro-vide artificial ageing. The oil vapor were guided inside a flowcell containing the sensors. A micro-optic scanner fitted insidethe flow cell was used for spectral interrogation of the sensorswhile exposing them to vapors of progressively aged oil [26].The scanner consisted of a revolving platform with 16 slots pow-ered by a step motor: in one slot, a polyethylene disk was posi-tioned as a reference for signal normalization, while the metal-loporphyrin-based sensors were positioned in the remaining fif-teen slots. Two optical fibers, connected to an optical fiber spec-trophotometer, were fitted to the flow cell in a fixed position sothat they could perform transmission measurements of all thesensors while the revolving platform rotated. The spectropho-tometer used for the spectral interrogation of the sensor arraywas a custom-made device operating in the 400–700 nm spec-tral range, with a resolution of 10 nm [27]. LabView softwarewas used to manage all measurements, to set the spectropho-tometer parameters, to operate the step motor, and to acquirethe spectral data.

B. Experimental Results During Oil’s Artificial Ageing

A sample of extra virgin olive oil was artificially aged by ex-posure to 70 C for 45 h, with six heating steps, while measuringthe absorption spectra of the sensor array at every step. The pro-cessing of the spectral data was performed by means of Un-scramble software [28]. The results of PLS analysis, which cor-


Fig. 11. Experimental setup of the smart cap for sniffing olive oil ageing—left: diagram; right: practical implementation.

Fig. 12. Correlation between the ageing time of extra virgin olive oil and the sensor array response.

related the ageing time to the sensor array response, are shownin Fig. 12. The correlation factor was 0.97, demonstrating thatthe micro-optic system implemented, which simulated the per-formance of a smart cap, was capable of distinguishing the dif-ferent ageing levels of extra virgin olive oil.

V. PORTABLE FLUOROMETER FOR THE RAPID DETECTION IN

MILK OF THE CARCINOGENIC M1 AFLATOXIN

Aflatoxins (AFs) are fungal metabolites produced by wide-spread moulds, and can colonize foodstuffs and feed that sup-port fungal growth. A very important aflatoxin is the M1 type

(AFM1), also known as “milk toxin.” AFM1, which is the mainmetabolite of B1 aflatoxin (AFB1), is found in the milk of lac-tating animals as a result of having eaten AFB1-contaminatedfeed. Due to the fundamental role of milk in the human diet, es-pecially as infant nourishment, the fact of finding AFM1 in dairyproducts is regarded as a significant hazard for food safety andpublic health.

To date, the European Union has the most rigorous regula-tions concerning AFM1 in milk: the maximum legal limit is setat 0.05 g/Kg (50 ppt) for all European Union Member States,and guidelines suggest adopting lower limits for baby food, i.e.,


Fig. 13. AFM1 concentration detection—left: the experimental setup for fluorescence measurements; right: excitation and detection spectral bands.

Fig. 14. Left: titration curve for AFM1 aqueous solutions in the 0–125 ppt range; right: improved sensitivity by using succinyl-� -CD as fluorescence enhancer.

25 ppt [29], [30]. New low-cost screening methodologies suit-able for rapid and large-scale tests on milk are therefore greatlyneeded.

As AFM1 has a native fluorescence, a portable fluorometerwas implemented for AFM1 content detection in liquids.Although the instrument was equipped by means of a quartzcuvette, it could be easily implemented by means of an opticalfiber strand, as shown in Fig. 13-left. The instrument makes useof a LED source emitting at 365 nm and of a highly sensitivePMT detector that makes it possible to measure extremelylow fluorescence signals. The source and the detector wereequipped by means of band pass filters that provided an optimaloptical isolation between the illumination and detection spectralbands. The optical system was PC-driven, and the measurementprocedure could be suitably automated by using custom-madesoftware. The spectral configuration for AFM1 fluorescencedetection is shown in Fig. 13-right. It is characterized by anexcellent isolation between excitation and detection spectralbands [31].

The titration curve for AFM1 aqueous solutions in the0–125 ppt concentration range is shown in Fig. 14-left. With aview to practical applications, the main interest was to develop

a reliable screening device able to rapidly single out situationsof potential risk. Hence, starting from the titration curve, athreshold scale based on three levels could be identified:

• level 1—‘safe’, AFM1 ppt: [2000–2900]photo-counts;

• level 2—‘alert for baby-food’, 25 ppt ppt:[2900–3770] photo-counts;

• level 3—‘alarm’, AFM1 ppt: over 3770photo-counts.

Based on this reference scale, the aforesaid fluorometer couldbe used as the starting point for “tree decisions” when measuringfluorescence of unknown samples: if the result is within level1, the sample is considered “safe” and the control chain endsat this point; if the fluorescence value falls within level 2, thesample is potentially contaminated, and more thorough analysesare needed; if the result is level 3, the sample belongs to a stockthat is contaminated over the admitted level, and the entire stockshould be discarded.

Since the use of cyclodextrins (CDs) as fluorescenceenhancers for aflatoxin detection is widely reported in the liter-ature, and succinyl- -CD is considered to be the most efficientfluorescence enhancer for AFM1 [32], [33], a new titration


curve was measured by using succinyl- -CD at 5 mM ratio.Fig. 14-right shows the differences between the photo-countsmeasured with and without the fluorescence enhancer, at thevarious AFM1 concentrations. The increased sensitivity isevident: in particular, the value for the lowest detectable limit(25 ppt) increased by a factor of 3 in the presence of succinyl--CD. Moreover, the improvement in sensitivity is highlightedby the higher slope in the linear best fit, which increased about1.5 times in the presence of the fluorescence enhancer [34].

VI. PERSPECTIVES

The instruments presented in this paper have been imple-mented with the intention of providing information that iscomplementary to the strictly chemical data obtained by usingconventional analytical techniques. Based on low-cost spectro-scopic devices and friendly, programmable software interfaces,these instruments can easily be adapted for other applications.Typically, the color and turbidity assessment of liquids as anobjective tool for liquid mapping can be of interest for manytypes of liquids, such as spirits, juices, and beverages of alltypes, both for product control during production and for certi-fication purposes. Moreover, the hyperspectral signature of allkinds of liquids can provide information regarding the presenceof dyes, peculiar constituents, nutritional factors, preservatives,and additive compounds. We should also point out that, inaddition to the smart cap presented here, there are many otherproducts looking for sensorized packaging. The most relevantof these is a smart packaging capable of controlling the coldchain. Fiber-optic and micro-optic technologies are particularlywell received in the food sector with a view to implementing abar-code reader able to nondestructively interrogate the qualityand safety of many food types by means of a light-mediatedsensorized packaging.

ACKNOWLEDGMENT

The authors are grateful to F. Cosi for the technical assistanceand to D. Tirelli for the mechanical designs.

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Anna Grazia Mignani was born in Bologna, Italy,in 1957. She graduated in physics and received thePh.D. degree in nondestructive testing from the Uni-versity of Florence, Florence, Italy.

Since 1983, she has been with CNR-IFAC, Italy,currently as Senior Scientist. Her research workincludes fiber-optic and micro-optic sensors, passiveguided-wave components for sensing applications,and fiber-optic sensor networks. This activity isdocumented by many journal and conference publi-cations, invited talks, and some international patents.

She managed national and international research contracts on applicationoriented optical sensing.

Dr. Mignani chaired the 14th International Conference on Optical Fiber Sen-sors, some SPIE Conferences on Optical Sensing, and served as Guest Ed-itor of the IEEE SENSORS JOURNAL and IOP Measurement Science and Tech-nology. She is a member of the Board of the Italian Society of Sensors andMicrosystems.

Leonardo Ciaccheri received the Degree in physicsand the Ph.D. degree in nondestructive controls fromthe University of Florence, Florence, Italy, in 1997and 2001, respectively.

Since 2003, he has been collaborating contin-uously with the Fiber Optic Group, Institute ofApplied Physics “Nello Carrara”—CNR, Florence.His current research interests are in fiber opticsensors for spectroscopy and multivariate dataprocessing. He also collaborates with the Faculty ofElectrical Engineering of the University of Florence,

where he teaches geometric optic, as part of the optoelectronic program.

Costanza Cucci graduated in physics and receivedthe Ph.D. degree in conservation science from theUniversity of Florence, Florence, Italy.

Since 2000, she has carried on her research activityat the Institute of Applied Physics “Nello Carrara”of the National Research Council (IFAC-CNR) ofFlorence. She has been member of the team of theEC LiDo Project EVK4-CT-2000-00016 whichresulted in the development of a new light-dosimeterfor museum environment, now commercialized asLightCheck@System. Presently, she is employed as

temporary researcher in the Department of Signal Imaging and Processing,IFAC-CNR, Florence. Her research interests concern the application of opticaland spectroscopic techniques to analysis and characterization of materials, witha special focus on nondestructive methodologies, and development and testingof optical sensors and monitoring systems for different application fields,such as: diagnostic and control of cultural heritage, environmental monitoring,safety/quality controls of substances in complex matrices (food products,organic materials, etc.).

Andrea Azelio Mencaglia received the Degree inphysics from the University of Florence, Florence,Italy, in 1987.

He was with CNR, Institute of Research onElectromagnetic Waves (IROE) from 1987 to April1996, first awarded with fellowships and then as aResearcher. In 1996, he was Research Fellow at theUniversity of Strathclyde, Glasgow, U.K., for sixmonths within the Human Capital Mobility program.From January 1997 to 2001, he was responsiblefor research activity at Prodotec. Since January

2002, he has been a Scientist with the Institute of Applied Physics of CNR.His activity is mainly concentrated in the area of optical fibres sensors andsystems and optoelectronic instrumentation, with applications in the fields of

diagnostics for food, for the cultural heritage, environmental, industrial andmedical diagnostics. He is responsible for a contract with a company for thedevelopment of a system for multiple analysis for clinical diagnostics andcollaborates in several European and national projects. He is author of about100 publications in journals and conference proceedings and of several patents(USA, Europe, and Italy).

Antonio Cimato graduated in agriculture sciencesfrom Florence University, Florence, Italy, in 1976.

He is presently Senior Researcher at CNR-IVALSA, where he has participated and coordinatedseveral national and international projects. Thescientific activity, finalized to basic and appliedresearch and to technological transfer, has beendeveloped in the agro-technical sector, especially forolive growing. The research lines are referable to:interventions to optimize agricultural productions,interactions between agronomic techniques and

food quality, technological innovations, food certification, agro-alimentary linetraceability (virgin olive oil), characterization strategies, biodiversity safeguard,sustainability, and exploitation.

Cristina Attilio graduated with a Degree in agricul-ture and technological sciences from Florence Uni-versity, Florence, Italy, in 2000.

She is currently Contract Researcher atCNR-IVALSA. The activity has primarily beendeveloped in subjects related to characterization,production, safeguard and valorization of theagro-alimentary resources. In the olive growingsector, the research field of application are referableto: biodiversity safeguard, control of the qualitativeand quantitative aspects of the productions and

identification of innovative methodologies for the traceability in the agro-ali-mentary production line. She participates in the coordination and the technicalmanagement of research projects financed by international institutions.

Heidi Ottevaere was born in Halle, Belgium, onJanuary 21, 1974. She received the Master degreein electrotechnical engineering with majors inphotonics and the Ph.D. degree in applied sciencesfrom the Vrije Universiteit Brussel (VUB), Brussels,Belgium, in 1997 and 2003, respectively.

In 1997, she joined the Department of AppliedPhysics and Photonics (FirW-TONA), VUB, as aTeaching Assistant, where she is currently engagedin research on optical fiber sensing, where shedemonstrated a novel method to characterize dental

resin cements. She was an invited speaker at the SPIE Photonics EuropeConference in Strasbourg, France, in 2004. She is currently supervisingseveral microoptical industry-oriented research projects. Recently, she alsoinitiated together with her colleagues a research group on biophotonics withassistance from different European top-research groups. She is also a promoteror copromoter of some basic research projects, which are financially supportedby regional and national bodies such as the Fund for Scientific ResearchVlaanderen (FWO) and the Belgian Federal Science Policy Office. She is also aDeputy Workpackage Leader of the Centre for Measurement and Instrumenta-tion of the European Sixth FP Network of Excellence on Micro-optics NEMO.She is the author or coauthor of more than 50 papers in international conferenceproceedings and is the author of two book chapters. She is the holder of onepatent. Her current research interests include the optical characterization ofmicrolenses, the fabrication of microlenses with deep proton lithography, inparticular, and micro-optical instrumentation.


Hugo Thienpont (A’97–M’97) was born in Ninove,Belgium, in 1961. He received the Master degree inelectrotechnical engineering and the Ph.D. degree inapplied sciences from the Vrije Universiteit Brussel(VUB), Brussels, Belgium, in 1984 and 1990,respectively.

In 1994, he became a Professor in the Facultyof Applied Sciences, with teaching responsibilitiesin photonics. In 2000, he became a Research Di-rector in the Department of Applied Physics andPhotonics (FirW-TONA), VUB, and in 2004, he

was elected Chair of the Department. Currently, he is coordinating severalbasic research and networking projects such as the European Network ofExcellence on Micro-Optics (NEMO). In addition to academic-oriented re-search projects, he manages microphotonics-related industrial projects withcompanies like Barco, Agfa-Gevaert, Tyco, and Umicore. He is the authoror coauthor of more than 120 SCI-stated journal papers and more than 400publications in international conference proceedings. He is the editor of 20conference proceedings and is the author of five chapters in books. He wasan invited speaker at 40 international conferences. He is the holder of tenpatents. His current research interests include micro-optics technologies, op-tical interconnects, and photonic sensing.

Dr. Thienpont is a Fellow of the International Society for Optical Engi-neering (SPIE), a fellow of the EOS, and a member of the IEEE Laser andElectro-Optics Society (LEOS), and the Optical Society of America (OSA).He served as a Guest Editor of several special issues on optical intercon-nects for Applied Optics and the IEEE JOURNAL OF SELECTED TOPICS ON

QUANTUM ELECTRONICS, and is a General Chair of the SPIE PhotonicsEurope conferences in Strasbourg, France. He was the recipient of the In-ternational Commission for Optics Prize ICO’99 and the Ernst Abbe medalfrom Carl Zeiss, the title of IEEE LEOS Distinguished Lecturer in 2003, theSPIE President’s Award for dedicated service to the European Communityin 2005, and the MOC Award in 2007.

Roberto Paolesse graduated with a Degree (cumlaude) in chemistry from the University of Rome LaSapienza, Rome, Italy, in 1983, where he began hisresearch activity with a AIRI Fellowship.

From 1986 to 2001, he was Assistant Professor atthe Faculty of Engineering, University of Rome TorVergata, where he has been Associate Professor sinceNovember 2001. In 1992, 1993, 1995, and 1996 hewas Visiting Professor at the Department of Chem-istry, University of California at Davis, collaboratingwith the Professor Kevin M. Smith. His research ac-

tivity is documented by more than 190 papers on international journals, fourpatents and can be described by four different topics: synthesis and reactivity oftransition metal complexes of tetrapyrrolic macrocycles; development of chem-ical sensors to be exploited in sensor arrays; thin films deposition of organicmaterials; study of the optoelectronic properties of porphyrin and related macro-cycle thin films.

Mr. Paolesse is a member of the Steering Committee of the InternationalMeeting on Chemical Sensors (IMCS) conference.

Marco Mastroianni was born in Rome, Italy, onMarch 30, 1974. He received the Master degree inchemistry in 2001 and the Ph.D. degree in chemicalsciences in 2004 from the University of Rome TorVergata, Rome, Italy.

His research interests include the preparation ofporphyrin derivatives as sensitive material for sen-sors, in both liquid and gas phase, and reactivity ofcorroles.

Donato Monti received the Ph.D. degree in chem-istry from the University of Rome La Sapienza,Rome, Italy, in 1994.

He then began his research activity as CNRFellow. He has been an Assistant Professor with theScience Faculty, University of Rome Tor Vergatasince November 1996. From 1992 to 1994, hecollaborated with Professor Peter M. Maitlis atSheffield University, Sheffield, U.K. His researchactivity is documented by more than 60 papers oninternational journals, and is focused on the study of

porphyrin aggregates and their application in clinical and sensing fields.

Marco Gerevini graduated with a Degree in food sci-ence and technology from the Univerisità degli Studidi Milano, Milan, Italy.

His main interests concern all the aspects ofresearch an innovation in the food chain. Since2001, he has been with Tecnoalimenti S.C.p.A.,Milano, as a Senior Project Manager for Euro-pean Commission funded projects in research anddevelopment of the Agrifood Industry. He set upresearch consortia, writing successful proposalsand coordinating national and international funded

research projects on innovative nonthermal processing technologies to improvethe quality and safety of ready-to-eat meals, E-platform technologies for theEuropean agro-food supply chain, Transregional Cooperative Platform forCompetitiveness in meat research and SMEs, novel food chain e-platformapproaches for responding to consumers concerns, integrated system of supplyfor increasing agro-food quality, safety and consumer confidence, study ofmultifunctional micro-systems for chemical and biochemical determinationsin biological complex matrixes.

Giovanna Buonocore graduated in chemical engi-neering from the Università di Napoli Federico II,Italy, and received the Ph.D. degree in materials sci-ence and engineering from the same university.

She is a Researcher with the Institute for Com-posites and Biomedical Materials (IMCB)—NationalResearch Council. Her research activities are relatedto the development and characterization of innova-tive polymeric materials for food packaging appli-cations (i.e., oxygen scavenger films, antimicrobialfilms, nanocomposite biodegradable films). The char-

acterization of this material is mainly related to the determination of their phys-ical- chemical, mechanical and mass transport properties, their processabilityand their suitability as food-contact material. She has been visiting researcherat the University of Santiago di Compostela, Spain, and the University of Texasat Austin. She is author or coauthor of more than 20 publications on interna-tional journals and of several works presented to international conferences.

Matteo Alessandro Del Nobile received the Ph.D.degree in material science from the University ofNaples Federico II, Italy.

He is now with the University of Foggia, Foggia,Italy, as a Full Professor. The main areas of interestinclude mass diffusion through polymeric materialsand packaging structure design. Most of his effortswere put forward to determine the relationshipsexisting between physical and chemical structure ofpolymers and their mass transport properties. Thistopic has been approached both from a theoretical

and from an experimental point of view. The knowledge gained studying masstransport phenomena through polymer has been applied for developing toolsintended for packaging structure design. He is now actively working on activepackaging. In particular, he is developing active packaging with antimicrobialactivity. He has published over 100 papers on topics related to polymer scienceand food science.


Annalisa Mentana graduated with a Degree (cumlaude) in food science and technology from the Uni-versità di Foggia, Foggia, Italy, where she receivedthe Ph.D. degree in food product biotechnologies.

She is an expert in analytical instrumentation forfood analysis, biosensors for food toxicity assess-ment, and food packaging, especially the monitoringof food-packaging interaction. She belongs to panelsfor wine tasting as well as for the sensory evaluationof a wide variety of foods.

Maria Francesca Grimaldi graduated with a Degreein chemistry from the University of Foggia, Foggia,Italy.

She specializes in analytical chemistry at theUniversity of Foggia. Her expertise includes foodpackaging and chromatographic analyses, especiallythose related to fish quality and freshness and tobroccoli quality during the shelf life.

Chiara Dall’Asta graduated with a Degree in chem-istry in 2000 and received the Ph.D. degree in foodscience and technology in 2004 from the Universityof Parma, Parma, Italy.

Since 2005, she has been an Associate Researcherin Food Chemistry at the University of Parma. Her re-search activities are focused on the identification andcharacterization of free and masked-mycotoxins byLC-MS/MS. Moreover, she is involved in the design,synthesis and application of chemosensors for fooddiagnostic.

Andrea Faccini graduated with a Degree in chem-istry from the University of Parma, Parma, Italy, in2001, where he received the Ph.D. degree in chem-istry in 2005 with a thesis on synthesis and charac-terization of PNA with biological activity for medicalapplication.

Since 2005, his research activities have beenfocused on the synthesis and characterization ofcyclodextrins as chemosensor for mycotoxins byfluorescence and LC-MS/MS.

Gianni Galaverna graduated with a Degree (cumlaude) in chemistry from the University of Parma,Parma, Italy, in 1989, where he received the Ph.D.degree in chemical sciences in 1994.

He became Researcher of organic chemistry in1997 and then Associate Professor of food chemistryin 2004 at the Faculty of Agriculture. His researchactivity is focused on different interrelated topicsparticularly relevant in the food sector: on one side,the development of new methods for the separationand identification of principal and secondary com-

ponents of foods (amino acids, peptides, antioxidants, DNA, mycotoxins) and,on the other side, the application of the methods to different types of foods(cheeses, salami, fruit juices, milk, yogurt, wine, cereals, etc.) in correlationwith production and transformation processes, seasoning and preservation,chemical or microbiological contamination.

Arnaldo Dossena graduated and received a Degreein chemistry from the University of Parma, Parma,Italy, in 1971.

Since 2000, he has been a Full Professor of Or-ganic Chemistry and Lecturer of Chemistry of Or-ganic Natural Substances. His research in the fieldsof organic chemistry, food chemistry, and biotech-nology led to more than 100 scientific research pub-lications published in international journals. He has aspecific experience in the field of isolation and char-acterization of natural substances and modification of

amino acids and peptides. He has been involved in the design and synthesisof chiral selectors, based on amino acids and on functionalized cyclodextrins,for the enantiomeric discrimination of biologically and pharmacologically ac-tive molecules developing different original chromatographic methods to studycomplex systems such as foods.

EAT-by-LIGHT: Fiber-Optic and Micro-Optic Devices for Food Quality and Safety Assessment

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