characterization of edible coatings and microorganisms on food surfaces using fourier transform...

Volume 55, Number 5, 2001 APPLIED SPECTROSCOPY 5710003-7028 / 01 / 5505-0571$2.00 / 0q 2001 Society for Applied Spectroscopy

Characterization of Edible Coatings and Microorganisms onFood Surfaces Using Fourier Transform InfraredPhotoacoustic Spectroscopy

HONG YANG, JOSEPH IRUDAYARAJ,* and SIVAKESAVA SAKHAMURIDepartment of Agricultural & Biological Engineering, 227 Agricultural Engineering Building, The Pennsylvania State University,University Park, Pennsylvania 16802

Fourier transform infrared photoacoustic spectroscopy (FT-IR/PAS) was used to study edible coatings and microorganisms on fruitsurfaces (apple and honeydew melon). In the experiment, pregela-tinized starch and whey protein concentrate were used to prepareedible coatings, while Saccharomyces cerevisiae, Lactobacillus casei,Escherchia coli, and Staphylococcus aureus were used for microbialstudy. The spectra obtained from the edible coatings on the applesurface indicate that the FT-IR/PAS technique can effectively dis-tinguish the coating surface and the food substrate by examinationof magnitude, phase angle, and generalized two-dimensional (G2D)correlation spectra. Results reported show the � rst application ofFT-IR/PAS to directly differentiate a fruit surface (apple and hon-eydew melon) with/without microorganisms without elaborate sam-ple preparation. The results demonstrate the potential of FT-IR/PAS to characterize the presence of microorganisms on fruit sur-faces.

Index Headings: Fourier transform infrared photoacoustic spectros-copy; Depth pro� ling; Edible coatings; Microorganism; Magnitudespectrum; Phase angle spectrum; G2D correlation analysis; Dis-criminant analysis.

INTRODUCTION

Edible coatings have been used to improve food pres-ervation and appearance to satisfy customers’ demand forhigh quality, longer shelf life, and convenient ready-to-eat foods. Edible coatings are comprised of lipids, poly-saccharides, and proteins and can be directly applied tofood surfaces.1 Edible coatings possess functional prop-erties related to solute, gas, and vapor transfer.2 Manytest methods have been developed for examining theproperties of edible coatings. When edible coatings areused as protective layers or bio� lms, it is important toensure that the integrity and qualitative characteristics ofthe coatings are not compromised. Standard methods,such as measurement of gas permeability by mass spec-trometer and water vapor permeability by gravimeter, areused to assess the functionality of nonedible coatings(e.g., polymer � lm).3

Food and package systems are complex materials. Anedible coating at the surface of a food material can serveas a protective cover for fruits and vegetables and con-stitute a multilayer system with the food surface. It isimperative that the chemical properties and structures ofthe multilayer system be maintained to retain the productvalue and functionality. Examination of the characteris-tics of fruit surfaces nondestructively will provide valu-able information on the fruit quality, the effect of the

Received 29 September 2000; accepted 23 January 2001.* Author to whom correspondence should be sent.

coating on the fruit surface, and the diffusion of coatingchemical components into the fruit. An effective probingtechnique will not only address the above considerationsbut also help to detect and identify microorganisms. Veryfew techniques are available to nondestructively charac-terize the multilayered materials. This research attemptsto characterize fruit surfaces coated with edible layersand microorganisms.

With its characteristic frequencies and correspondingabsorbance, Fourier transform infrared (FT-IR) spectros-copy can be used to characterize conformationally dis-tinct structures and identify functional groups in biolog-ical molecules.4 Information about the chemical compo-nents in the biological samples, such as protein and fat,can be obtained by using FT-IR spectroscopy. With pho-toacoustic spectroscopy (PAS), FT-IR can be used to pro-vide depth-pro� le information of layered materials.5 Theauthors examined a four-layer polymer material to dem-onstrate FT-IR/PAS depth pro� ling. The chemical com-position of starch-based paper coatings was examined byFT-IR/PAS.6 The depth-pro� le information of the coatedlayers was obtained through magnitude, phase angle, andgeneralized two-dimensional (G2D) correlation spectra.The effects of glycerol and polyethylene glycol on theconformation of the protein in sodium caseinate ediblecoatings were studied by FT-IR/PAS.7 Curve-� tting andsecond-derivative spectral analysis were used to study thein� uence of glycerol and polyethylene glycol on ediblecoatings from FT-IR/PAS spectra.

An important aspect of surface characterization is todetect and identify microorganisms on food, a very cru-cial food safety issue. Traditional methods for differen-tiation and identi� cation of microorganisms depend onbiochemical and serological tests that usually involve in-cubating the culture in selective agar media or broth forup to several days and then performing a speci� c test todetermine the presence of a certain species of bacteria.FT-IR has been used to chemically differentiate intactmicrobial cells without destruction by producing complexbiochemical � ngerprints that are reproducible and distinctfor different bacteria.8 FT-IR spectroscopy has also beenused as a tool to discriminate and classify intact microbialcells at the strain level.9 In all of the past research, onlya sample of the pure microorganism extracted from dif-ferent sample sources was used in analysis.

Normally, the surfaces of food products that are ex-posed to environments are most susceptible to contami-nation by microorganisms. Therefore, sampling and anal-ysis of the surfaces are very important in any analytical

572 Volume 55, Number 5, 2001

procedure. Different sampling procedures can be adoptedto obtain microbial samples from food surfaces, such ascotton swabbing. However, once microorganisms becomeattached to a food surface, it is very dif� cult to recoverthem for analysis.10 Different sampling procedures canprovide different microorganism counts. For example, ex-cision and maceration of tissue produce higher numbersthan swabbing, rinsing, or contact agar.10 Direct methodsto determine the presence of microorganisms on food sur-faces could minimize the time and the effort needed foranalysis.

Fourier transform-infrared photoacoustic spectroscopyhas been used to directly determine fungi contaminationon the surface of corn.11–16 The spectra of corn with orwithout the fungi from FT-IR/PAS were divided into 12distinctive areas for identi� cation.15 Twelve distinct areasin the spectrum were interpreted and assigned by theo-retical comparisons of the relative chemical compositionsof fungi and corn. An arti� cial neural network wastrained to distinguish contaminated from uncontaminatedcorn by pattern recognition. Results demonstrated thatFT-IR/PAS with its multicomponent analysis capabilitywas more reliable than the bright greenish-yellow � uo-rescence (BGYF) method.15 With the use of the spectralproperties of contaminated and uncontaminated corn, itwas possible to automatically determine and isolate con-taminated grains from uncontaminated grains. The pro-tein biomass in Saccharomyces cerevisiae and Escher-chia coli has also been measured by FT-IR/PAS, aftermicroorganisms were deposited and dried on the � lter.17

The increase of protein biomass in the microorganismsduring the growth period was con� rmed by FT-IR/PASspectra. It was concluded that FT-IR/PAS could be a po-tential tool to directly detect the presence of microorgan-isms on the food surface.

Basics of Fourier Transform Infrared Photoacous-tic Spectroscopy. Unlike other infrared spectroscopictechniques, FT-IR/PAS can be used to study opaque andhighly absorbing materials with minimum sample prep-aration. In this procedure, a modulated infrared (IR) beamstrikes a sample, kept in a helium-purged compartment.The incident beam results in the generation of heat withinthe sample by nonradiative deexcitation and causes pe-riodic temperature variation within the sample. The tem-perature oscillation results in a change in pressure at theinterface of the sample and the helium environment,which can be detected by a very sensitive microphoneand converted to an electric signal. The theoretical foun-dation of photoacoustics (RG theory) is described by Ro-sencwaig and Gersho.18 The penetration (mt) of the infra-red beam into the sample is described by the Rosencwaigand Gersho equation as

am 5 (1)t ! p f

where a is the thermal diffusivity and f is the modulationfrequency of the radiation. For different values of mod-ulation frequencies, different depths can be probed.18,19

With the step-scan technique, FT-IR/PAS can be usedfor depth-pro� le analysis by simultaneous acquisition ofspectra at different depths of the sample nondestructive-ly.5,19,20 With the use of a lock-in ampli� er (LIA) or dig-

ital-signal processing (DSP), the photoacoustic (PA) sig-nal can be demodulated and the phase [u(l)] and mag-nitude [M (l)] spectra can be calculated on the basis ofthe in-phase [I (l)] and quadrature [Q(l)] components ofthe signal.

21u(l) 5 tan [Q (l) /I (l)] (2)2 2M (l) 5 ÏQ (l) 1 I (l) (3)

The magnitude spectrum provides the magnitude of ab-sorbance peaks at the same depth layer. The phase spec-trum shows the phase angle for each peak in the spectrumwith the peaks from the same layer having similar phaseangle values. For example, a PA signal from a deeperlayer of the sample will reach the detector later than thatfrom the surface; hence the phase angle of the moleculargroups of the constituents from the deeper layer is higherthan that from the surface. Such information could beused to differentiate signals from different depths, mak-ing depth pro� ling possible. Step-scan FT-IR/PAS wasused to demonstrate the migration of cheese componentsinto polymer packaging � lm. 21,22 A similar procedurecould be used to study edible coatings on food surfaces.

Generalized two-dimensional spectra correlation anal-ysis is an alternative way to interpret depth-pro� le resultsfrom FT-IR/PAS measurements.5 The advantages of G2Dcorrelation spectroscopy include (1) simpli� cation ofcomplex spectra with many overlapping peaks, (2) en-hancement of spectral resolution by spreading peaks overthe second dimension, and (3) the display of unambigu-ous assignments through correlated bands.23 For example,the G2D correlation spectrum can especially accent spec-tral properties not readily observable in conventionalspectral illustrations. The basic theory of two-dimension-al correlation spectrum was � rst developed by Noda,24

who then extended it to a more general application.25 Across-correlation analysis was used to sinusoidally varydynamic infrared signals and construct a set of G2D IRcorrelation spectra after an external perturbation wave-form was applied to the system.26,27 The G2D correlationmethod was used to successfully demonstrate the migra-tion of protein and fat from cheese into its polymer pack-aging � lm. 22

Although FT-IR/PAS has been widely applied to ana-lyze and study various systems, its application in foodanalysis is very limited. The objective of this study wasto examine edible coatings (protein and starch � lm) andmicroorganisms on the surface of foods (apple and hon-eydew melon) by FT-IR/PAS and G2D correlation anal-ysis.

EXPERIMENTAL

Preparation of Samples for Edible Coating Exper-iments. Apple and honeydew melon were used as thefood substrate layer for edible coatings or microorgan-isms. Whey protein concentrate (New Zealand MilkProducts Inc., Santa Rosa, CA) and pregelatinized starch(Instant TENDER-JEL C, A. E. Staley Manufacturer Co.,Decatur, IL) were used to prepare protein and starch� lms. The aqueous solution concentration of protein orstarch was 10% (w/w). Glycerol (INC Biomedicals Inc.,Aurora, OH) was added as a plasticizer to avoid crackingof the dry � lms, which might interfere with depth-pro� le

APPLIED SPECTROSCOPY 573

analysis. The amount of glycerol was about 40% (w/w)in the protein/starch media. After mixing, the starchturned into a gellike substance due to its pregelatinizationcharacteristics. The protein solution and the starch gelwere stored in a refrigerator (;5 8C) until further use,either to use for analysis or to fabricate a triple-layercomposite.

Apple skin was peeled from an apple and dried at roomtemperature (;25 8C) for 24 h. Protein and starch solu-tions were directly applied and spread on the apple skinsurface. The starch/protein/apple layered sample wasmade by spreading the starch mix on top of the protein/apple layered sample. The protein/starch/apple layeredsample was prepared by pouring the protein solution ontop of the starch/apple layered sample. After 24 h dryingat room temperature, a 4 3 4 mm cross section of thetriple-layered sample (starch/protein/apple and protein/starch/apple) was placed in the PA cell for FT-IR/PASmeasurement. Spectra of pure protein and pure starchwere obtained by directly placing the respective proteinand starch � lms in the aluminum PA cell after drying for24 h at room temperature.

Sample Preparation for Microorganism Detection.The microorganisms used in this study were Saccharo-myces cerevisiae (ATCC 24859), Lactobacillus casei(ATCC 11443), Escherchia coli (K-12), and Staphylo-coccus aureus (NRRL B-1657). Frozen cultures werethawed and the organisms were grown in standard re-spective optimum broth at 32 8C for 24 h. S. cerevisiaewas grown in a medium that contained 20 g of glucose,6 g of yeast extract, 0.23 g of CaCl2·2H2O, 4 g of(NH4)2SO 4, 1 g of MgSO 4·7H2O, and 1.5 g of KH 2PO 4

per liter of distilled water. L. casei culture was inoculatedby using a lactic acid fermentation (LAF) medium (20 gof glucose, 8 g of yeast extract, 0.5 g of K2HPO 4, 1 g ofCH3COONa, 0.6 g of MgSO 4, and 0.03 of MnSO 4·7H2Oper liter of distilled water). E. coli was grown in a 2 3YT medium (10 g of yeast extract, 16 g of tryptone, and5 g of NaCl per liter of distilled water). A medium thatcontained 10 g of yeast extract and 5 g of NaCl per literof distilled water was used to grow S. aureus. The growncultures were centrifuged at 5000 rpm for 15 min andwashed two times with distilled water. Aliquots of resus-pended microbial suspensions were evenly placed at thesurface of apple and honeydew melon skin and dried atroom temperature for 12 h before spectroscopic analysis.A total of four microorganisms and two fruit surfacesconstituted a total of eight different samples.

FT-IR/PAS Measurement. A Bio-Rad FTS 6000 FT-IR spectrometer (Cambridge, MA) with a Bio-Rad de-modulator and a helium-purged MTEC Model 100 PAcell (Ames, IA) was used. The FT-IR spectrometer con-tained a cooled ceramic mid-IR source and a KBr beam-splitter. A Model 75-52 FT-IR purge-gas generator(Whatman, Inc., Haverhill, MA) was used to provideCO2- and H2O-free dry air to the interferometer system,while helium was used to purge the PAS detector.

The interferometer in the spectrometer can operate inthe rapid-scan or step-scan modes. The step-scan optionwas used for all depth-pro� ling studies. A carbon blackreference was used to collect the corresponding referencespectra for spectra-intensity normalization. Win-IR ProTM

software (Version 2.5, Bio-Rad Laboratories, Cambridge,

MA) with DSP was used to control the FT-IR spectrom-eter and process all data.

The PA cell with a small piece of sample was purgedfor 5 min by helium to provide a CO2- and moisture-freeenvironment. The pure starch, protein, and polyethylene� lms, deposited in the aluminum PA cell, were directlymeasured by rapid scan at a speed of 5 kHz scan, a res-olution of 16 cm21, and at 256 scans/sample. A modu-lation frequency of 100 Hz was used for depth-pro� leanalysis of the multiple-layer � lm sample at the step-scanmode. The modulation amplitude was set at 2, the reso-lution at 16 cm21, and the numbers of scans at 2. Thestep-scan FT-IR/PAS spectra of package � lm were col-lected for G2D correlation analysis. Spectra obtainedwere consistent; hence all experiments were replicatedtwice and averaged for analysis.

G2D Correlation Spectral Interpretation. The G2Dcorrelation spectra contain synchronous and asynchro-nous correlation spectra, calculated from in-phase andquadrate spectra from the step-scan FT-IR/PAS measure-ments at a speci� c frequency.25 The synchronous G2Dcorrelation spectrum represents similarity among the dif-ferent peaks in the spectra with respect to depth, whilethe asynchronous spectrum represents the dissimilarity orthe difference among the peaks.25 In this study, differ-ences among peaks from different layers were expected;hence only the asynchronous spectrum was used to in-terpret the depth pro� le spectra. An asynchronous spec-trum consists of two types of cross peaks: positive andnegative. A positive asynchronous G2D PA correlationpeak at l1 /l2 (l1 5 wavenumber on the X axis and l2 5wavenumber on the Y axis) indicates that the absorbanceat l1 occurs before the absorbance at l2; i.e., the spatialorigin of the signal peak at l1 is from a shallower depththan at l2. A negative asynchronous G2D PA correlationpeak represents the opposite; i.e., the spatial location ofthe signal at l1 is from a deeper location than that at awavenumber l2. The positive and negative signs associ-ated with the peaks in the asynchronous spectrum indi-cate the respective functional group information at dif-ferent depths.

Discriminant Analysis. Principal component (PC) andcanonical variate (CV) analyses were applied to the spec-tra obtained from microbial characterization experimentsto discriminate microorganisms. In general, weighted lin-ear combinations of the spectra are structured so as tomaximize the differences among the group means, rela-tive to their variances. The linear combinations of thevariances, known as canonical variates, can be plotted tocluster the data into different groups based on spectralsimilarities. Discriminant analysis was done to classifyfruit surfaces with different microorganisms by usingWin-DAS (Wiley, Chichester, UK) software.

RESULTS AND DISCUSSION

Characterization of Edible Coating on Apple Sur-face. Figure 1 contains the rapid-scan PA spectra of pureprotein � lm, starch � lm, and apple skin with the peakscorresponding to the major functional groups related tothe respective chemical components of the materials. Ta-ble I lists the peaks for the major chemical groups in thesample. The absorbances due to amide I (1655 cm21) and


FIG. 1. Rapid-scan FT-IR/PAS spectra of protein, starch, and apple skin.

TABLE I. The major peaks in pure protein � lm, starch � lm, andapple skin.

Samples Wavenumber (sm21) Assignment

Protein 32982929287916551555145914021243926853

N–H stretchingC–H stretchingC–H stretchingAmide IAmide IIC–H bengingC–H bendingC–H bengingC–H bendingC–H bending

Starch 33762933165214581054930857

O–H stretchingC–H stretchingC5C stretchingC–H bendingC–O–C stretchingC–H bendingC–H bending

Apple skin 292328541733165414571174726

C–H stretchingC–H stretchingC5O stretchingC5C stretchingC–H bendingC–O–C stretchingC–H bending

II (1555 cm21) from the protein groups in the samplewere identi� ed in the PA magnitude spectrum (Fig. 2a).Two other major peaks around 1733 cm21 due to C5Ostretch could be attributed to the skin layer, con� rmed bythe corresponding absorbance of the starch sample spec-trum (Fig. 1). The magnitude spectrum of the two-layerprotein/apple skin sample at a phase modulation frequen-cy of 900 Hz is shown in Fig. 2a. From Eq. 1, the phasemodulation frequency of 900 Hz corresponds to a prob-ing depth of 6 mm, where the key protein peaks (amideI and II) could be identi� ed due to the protein layer whilethe peak at 1733 cm21 due to the skin also appeared in

the magnitude spectrum. It was impossible to distinguishthe position of protein and starch layers in the three-layersample from the magnitude spectra at 100 and 900 Hzwithout further analysis.

The phase-angle spectrum of the same sample at thephase-modulation frequency of 100 Hz enhances the dif-ference and helps to identify the source of the absorbingfunctional groups of the originating signal (Fig. 2a). Thephase angle of amide I was 08, indicating that its PAsignal originated from the surface, while the phase angleat wavenumber 1733 cm21 was 138, denoting that its PAsignal originated from the position deeper than amide I.Such analysis is very useful in distinguishing spectrafrom multilayer materials.28

Generalized 2D correlation analysis can also be usedfor depth pro� ling studies.20 Figure 2b illustrates theasynchronous G2D PA correlation spectrum of the dou-ble-layered protein/apple sample at a phase modulationfrequency of 100 Hz. The cross peaks demonstrate dif-ferent modes of molecular vibrations in the sample. InFig. 2b, cross peaks are denoted by positive or negativesigns. The positive sign in the cross peak (l1 /l2) indicatesthat the absorbance at wavenumber l1 (marked on the x-axis) is from a shallower layer than that at l2 (marked onthe y-axis) in the sample, and vice versa. The positivesigns that correspond to cross peaks amide I/1733 cm21

and amide II/1733 cm21 indicate that the absorbance ofamide I and II is from a layer higher than that of 1733cm21, respectively. Conversely, the negative signs thatcorrespond to cross peaks 1733/amide I and 1733/amideII in the asynchronous spectrum are clearly marked inFig. 2b. The G2D correlation analysis further demonstrat-ed that the apple skin layer was below the protein � lmlayer.

Figure 3a shows the step-scan PA magnitude spectraof the double-layer starch/apple sample at phase modu-lation frequencies of 100 and 900 Hz, respectively. The


FIG. 2. (a) Step-scan FT-IR/PAS magnitude and phase-angle spectra of two-layer protein/apple at a phase-modulation frequency of 100 and 900Hz. (b) Asynchronous G2D correlation spectra of two-layer protein/apple at a phase-modulation frequency of 100 Hz 1800–700 cm21.

peak at 1733 cm21 from the skin layer does not appearin the 900 Hz spectrum but could be seen in the 100 Hzspectrum, a layer deeper than the spectrum obtained at amodulation frequency of 900 Hz. The phase angle cor-responding to the peak at 1053 cm21 from polyethylenelayer (Fig. 1) is 08 (Fig. 3a), while the phase angle at1733 cm21 from the apple layer is 228, thus indicatingthat the starch layer was above the apple-skin layer. Fig-ure 3b illustrates the asynchronous G2D PA correlationspectrum of the double-layer starch/apple sample at a

phase-modulation frequency of 100 Hz. The negativesign corresponds to the cross peak 1733/1053 cm21, in-dicating that the apple skin layer was below the starchlayer.

Figure 4a shows the step-scan PA magnitude spectraof the three-layer starch/protein/apple sample at phase-modulation frequencies of 100 and 900 Hz, respectively.Amide I and II bands (protein bands), 1053 cm21 (starchband), and 1733 cm21 (skin band) can be observed inboth magnitude spectra. The position of protein and


FIG. 3. (a) Step-scan FT-IR/PAS magnitude and phase-angle spectra of two-layer starch/apple at a phase-modulation frequency of 100 and 900Hz. (b) Asynchronous G2D correlation spectra of two-layer starch/apple at a phase-modulation frequency of 100 Hz 1800–700 cm21.

starch � lm in the three-layer sample could not be deter-mined from the magnitude spectra. The phase angles atamide I and II from the protein layer are 48 and 78, re-spectively. The phase angle at 1053 cm21 from the starchlayer is 08, and that at 1733 cm21 from the skin layer is248. Thus, from the phase angle spectrum, it could bedemonstrated that the starch layer was on the top, theprotein layer was in the middle, and the apple skin layerwas at the bottom.

Figure 4b illustrates the asynchronous G2D PA cor-

relation spectrum of the three-layer starch/protein/applesample at a phase-modulation frequency of 100 Hz. Thenegative signs are shown on the cross peaks, 1733 cm21 /amide I, 1733 cm21 /amide II, and 1733/1053 cm21. Thisresult indicates that the absorbance of 1733 cm21 wasfrom a layer deeper than the protein and starch layers.Conversely, the positive signs that correspond to crosspeaks amide I/1733 cm21, amide II/1733 cm21, and 1053/1733 cm21 in the asynchronous spectrum are clearlymarked in Fig. 4b. The negative signs are also shown for


FIG. 4. (a) Step-scan FT-IR/PAS magnitude and phase-angle spectra of three-layer starch/protein/apple at a phase-modulation frequency of 100and 900 Hz. (b) Asynchronous G2D correlation spectra of three-layer starch/protein/apple at a phase-modulation frequency of 100 Hz 1800–700cm21.

the cross peaks, amide I/1053 cm21 and amide II/1053cm21, indicating that the starch layer was on top of theprotein layer.

Figure 5a is the step-scan PA magnitude spectra of thethree-layer protein/starch/apple sample at the respectivephase-modulation frequencies of 100 and 900 Hz. Similarto the starch/protein/skin magnitude spectra, protein (am-ide I and II), starch (1053 cm21), and skin (1733 cm21)

bands are displayed in the magnitude spectra. Thereforethe phase-angle spectrum could be used to differentiatedifferent layers. The phase angle at 1733 cm21 from theskin layer is 138; those for amide I and II from the proteinlayer are 08 and 28, respectively; and that at 1053 cm21

from the starch layer is 68. The phase-angle informationobtained thus indicates that the protein layer was abovethe starch layer and the apple skin layer, while the starch


FIG. 5. (a) Step-scan FT-IR/PAS magnitude and phase-angle spectra of three-layer protein/starch/apple at a phase-modulation frequency of 100and 900 Hz. (b) Asynchronous G2D correlation spectra of three-layer protein/starch/apple at a phase-modulation frequency of 100 Hz 1800–700cm21.

layer was on top of the apple skin layer. It is very obviousthat the intensity at 1053 cm21 is lower than the inten-sities corresponding to amide I and II in the protein/starch/apple magnitude spectra (Fig. 5a). However, theintensity at 1053 cm21 is higher than the intensities atamide I and II in the starch/protein/apple magnitude spec-tra (Fig. 4a), which implies the reverse.

The asynchronous G2D PA correlation spectrum of athree-layer protein/starch/apple sample at a phase-mod-

ulation frequency of 100 Hz is shown in Fig. 5b. Similarto the starch/protein/apple G2D correlation spectrum(Fig. 4b), the negative signs correspond to cross peaksdue to 1733 cm21 /amide I, 1733 cm21 /amide II, and1733/1053 cm21 indicating that protein and starch layerswere on top of the apple skin. However, the signs thatindicate the positions between starch and protein layerswere transposed. The positive signs are displayed on thecross peaks, amide I/1053 cm21, and amide II/1053 cm21,


FIG. 6. (a) Rapid-scan FT-IR/PAS spectra of honeydew melon with/without microorganisms. (b) Discriminant canonical variate analysis based on� rst two canonical variates of honeydew melon with/without microorganisms.

indicating that the protein layer was above the starch lay-er.

Microbial Characterization of Apple and Honey-dew Melon Surfaces. Apple and honeydew melon sur-faces were smeared with S. cerevisiae, L. casei, E. coli,or S. aureus, and the spectra of the surfaces were mea-sured by both FT-IR/PAS rapid-scan and step-scanmodes. Spectra of each microorganism and the fruit sur-faces were obtained individually. The surface spectra ofhoneydew melon with and without microorganisms areshown in Fig. 6a. The FT-IR/PAS spectra were comprisedof the features of both the microorganisms and the hon-eydew melon. Expected major components in the fruit

are carbohydrates; hence the peaks related to carbon, ox-ygen, and hydrogen should be evident in the spectra (e.g.,C5O stretching at 1733 cm21). Since microorganismscontain proteins in their cells, their infrared spectrashould contain protein bands or their correspondingpeaks, which may not be present in the spectra of hon-eydew melon or apple. Consequently, the amide II band(;1550 cm21) cannot be seen in the spectrum of purehoneydew melon sample but only in the spectra of thesurface with microorganisms. Five regions in the spec-trum were used for discriminant and classi� cation anal-ysis of the microorganisms.9 They are 3050 to 2800 cm21,corresponding to the vibrations of the CH2 and CH3


FIG. 7. (a) Rapid-scan FT-IR/PAS spectra of apple with/without microorganisms. (b) Discriminant canonical variate analysis based on � rst twocanonical variates of apple with/without microorganisms.

groups; 1750 to 1500 cm21, due to the protein and peptidebands; 1500 to 1200 cm21, a mixed region containingvibrations of fatty acids, proteins, and polysaccharides;1200 to 900 cm21, dominated by polysaccharide peaks;and 900 to 700 cm21, called the � ngerprint region.9

The regions of 3000 to 2800 cm21 and 1800 to 1500cm21 were selected for discriminant analysis because oftheir high spectral correlation. From canonical variateanalysis, the � rst CV score accounted for 90% of thevariation among groups, while the second vector account-ed for about 5%. Figure 6b demonstrates the results ofdiscriminant analysis based on the � rst two CV scores,

clearly differentiating the samples with and without mi-croorganisms.

Figure 7a shows the apple skin contaminated by mi-croorganisms. A slight shoulder around amide I (;1650cm21) in the spectra of apple skin with microorganismsis evident due to the protein constituents from the micro-organisms. In the spectra of apple with S. cerevisiae, L.casei, and E. coli on the surfaces, the intensity of amideII is higher than that of pure apple skin. From CV anal-ysis, the � rst CV score accounted for about 86% of thevariations among groups, while the second vector ac-counted for about 7% of the variation. Figure 7b shows


FIG. 8. (a) Magnitude spectra of step-scan FT-IR/PAS obtained from honeydew melon with E. coli from 100 to 700 Hz. (b) Magnitude spectraof 100 and 700 Hz obtained from honeydew melon with L. casei, S. aureus, and S. cerevisiae.

the results of the discriminant analysis based on the � rsttwo CV scores.

The magnitude spectra collected from a honeydewmelon surface contaminated by E. coli by using FT-IR/PAS with modulation frequencies between 100 and 700Hz are given (Fig. 8a). Spectra were obtained with si-multaneous demodulation within a single measurement.The magnitude spectrum of 100 Hz is from a place inthe sample deeper than that of 700 Hz (Eq. 1). Intensitiesof amide I and II bands slightly increase as the modula-tion frequency increases from 100 to 700 Hz. A similarphenomenon was also observed from the spectra of skinsurfaces that contained other microorganisms (Fig. 8b).In Fig. 8b, only 100 and 700 Hz spectra are displayed,and the change of spectral contour due to amide I (;1650cm21) and II (;1550 cm21) can be seen.

Figure 9a displays the magnitude spectra collectedfrom apple with S. aureus at the surface with the use of

modulation frequencies between 100 and 700 Hz. Theintensity of amide I gradually appeared as the modulationfrequency increased, indicating the presence of microor-ganisms at the surface layers. As expected, amide II alsobecame somewhat more intense as the modulation fre-quency increased. Figure 9b contains the magnitude spec-tra at 100 and 700 Hz for other microorganisms. Thechanges in amide I and II are pointed out in Fig. 9b.

CONCLUSION

In this research, the potential of FT-IR/PAS for simul-taneous depth pro� ling of the edible coatings and micro-organisms on the surface of apple and honeydew melonwas demonstrated. The magnitude, phase angle, and G2Dcorrelation analysis can be effectively used for charac-terizing multilayered samples and edible coatings. Thevery � rst application of FT-IR/PAS with discriminant


FIG. 9. (a) Magnitude spectra of step-scan FT-IR/PAS obtained from honeydew melon with S. aureus from 100 to 700 Hz. (b) Magnitude spectraof 100 and 700 Hz obtained from honeydew melon with L. casei, E. coli, and S. cerevisiae.

analysis to differentiate fruit (apple and honeydew mel-on) surfaces with and without microorganisms was pre-sented. Experiments conducted on selected products withfour different microorganisms demonstrated that FT-IR/PAS with multivariate analysis could be a new tool forthe determination of microorganisms on food productsurfaces.

ACKNOWLEDGMENT

The assistance of Dr. Ali Demirci in supplying microorganisms andpreparing microbial cultures for analysis is greatly appreciated.

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characterization of edible coatings and microorganisms on food surfaces using fourier transform...

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