**Determination of Food Quality by Using Spectroscopic Methods**

Agnieszka Nawrocka and Joanna Lamorska

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/52722

#### **1. Introduction**

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[32] van den Veen M.: Towards intensification of starch processing, PhD Thesis, Wage‐

[33] van den Veen M., van Iersel D., van der Goot A., Boom R.:Shear induced inactivation of α-amylase in a plain shear field, Biotechnology Progress 2004;20(4) 1140-1145.

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[35] vanSoest J., Benes K., de Wit D., Vliegenthart J.: The influence of starch molecular mass on properties of extruded thermoplastic starch, Polymer 1996a;37(16)

[36] vanSoest J., Bezemer R., de Wit D., Vliegenthart J.: Influence of glycerol on the melt‐

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[39] Wolf B.: Polysaccharide functionality through extrusion processing. Current Opinion

[40] Wójtowicz A.: The melting process in thermoplastic starches. In: Janssen L.,Moscicki L. (eds.) Thermoplastic Starch. A green material for various industries, Weinheim,

[41] Wójtowicz A., van der Goot AJ.: The influence of water and glycerol addition on thermal processing rheology and microstructure changes of potato starch, Electronic Journal of Polish Agricultural Univeristies, seria Agricultural Engineering, 2005;8(4)

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#51.

Food is a complex system comprised predominantly of water, fat, proteins and carbohy‐ drates together with numerous minor components. The functional properties of these com‐ ponents, which are governed by their molecular structure and intra- and intermolecular interactions within food system, and the amounts present define the characteristics of food products. Quality of food products refers to the minimum standards for substances to quali‐ fy as fit for human consumption or permitted to come in contact with food. Appearance, col‐ or, flavor and texture are critical aspects for the sensory quality of food. The food quality includes also chemical, biological and microbial factors, e.g. instability of food products, which limits their shelf life and is connected with irreversible chemical and enzymatic reac‐ tions [1]. Recently, public interest in food quality and production has increased, probably re‐ lated to changes in eating habits, consumer behavior, and the development and increased industrialization of the food supplying chains. The demand for high quality and safety in food production obviously calls for high standards for quality and process control, which in turns requires appropriate analytical tools to investigate food.

Spectroscopic methods have been historically very successful at evaluating the quality of ag‐ ricultural products, especially food. These methods are highly desirable for analysis of food components because they often require minimal or no sample preparation, provide rapid and on-line analysis, and have the potential to run multiple tests on a single sample. These advantages particularly apply to nuclear magnetic resonance (NMR), infrared (IR), and near-infrared (NIR) spectroscopy. The latter technique is routinely used as a quality assur‐ ance tool to determine compositional and functional analysis of food ingredients, process in‐ termediates, and finished products [1]. Additionally, UV–VIS spectroscopy, fluorescence and mid-infrared (MIR) and Raman spectroscopy are used in the food quality monitoring.

© 2013 Nawrocka and Lamorska; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 Nawrocka and Lamorska; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The aim of this paper is to demonstrate applicability of four spectroscopic techniques, e.g. UV–VIS spectroscopy, fluorescence, infrared and Raman spectroscopy, as rapid analysis methods to determine the quality of cereals, cereals products and oils. Additionally, physi‐ cal foundations of the aforementioned methods are described.

#### **2. UV-VIS spectroscopy**

Absorption spectroscopy in the UV–VIS region is based on the Lambert-Beer's law, ex‐ pressed by the following equations (1, 2)

$$\mathbf{I} = \mathbf{I}\_0 \mathbf{1} \mathbf{0}^{-\text{ecl}} \tag{1}$$

dehydes which have reacted with p-anisidine. The aforementioned aldehydes are dienals or alka-2-enals and both are one of the final products of lipids oxidation. The highest permissi‐ ble value of AV for edible oils is 8. AV is also an element of Totox (total oxidation value), another factor indicating deterioration level of total fat. The value of Totox is calculated as the sum of two-fold value of AV and peroxide value. According to european standard [2], the measurement of absorbance is performed for three solutions (p-anisidine and sample of fat (A1), acetic acid and sample of fat (A0), and, lastly, blind sample being a mixture of panisidine and isooctane (A2)) at the wavelength 350 nm in a 1 cmcuvette. Theanisidine value

where: Q – content of the sample in the solution based on which the AV is expressed (g

The anisidine value can be also measured by using Flow Injection Analysis (FIA) combined with UV–VIS spectroscopy. Thanks to the implementation of FIA, the period of time re‐ quired for analysis can be significantly shortened. Additionally, the number of reagents is also maintained at very reasonable level. Sample of fat dissolved in propanol-2 is injected into continuous flow of p-anisidine with a mixture of solvents: propanol-2 and glacial acetic acid. Spectrophotometer is used as a detector, and the value of absorbance is measured at

The process of fat deterioration is also described by the peroxide value (PV). The deteriora‐ tion takes place during lipids' exposition to some external factors including temperature, daylight and oxygen. It results in production of peroxides and hydroperoxides, which are regarded as products of fatty acids oxidation. The highest value of PV for oil produced through cold press extraction is 10 meq O2 kg-1, while regarding refined oil it may reach the amount of 5 meq O2 kg-1. The PV value is measured by employing UV–VIS spectrometer as detector [4, 5]. Method of PV measurement of the frying canola oil was developed by Talpur et al. [6]. The authors used stoichiometric reaction of triphenylphosphine (TPP) with the hy‐ droperoxides to produce triphenylphosphine oxide (TPPO) which shown absorbance maxi‐ mum at 240 nm. Therefore, the developed method could serve as an alternative to the titration method for the determination of PV in frying oils due to high correlation of perox‐

Another parameter of oil quality is general colour which is determined by the saturation of chlorophyll or carotenoid pigments. Unlike oil produced through cold press extraction, re‐ fined oil has low saturation intensity colour, as most pigments are removed in the oil refine‐ ment. Carotenoid pigments are included to antioxidants. For this reason, oils with high content of carotenoinds are regarded as healthier and of higher quality. The general colour is assayed spectrophotometrically for oil samples diluted in CCl4, at two wavelengths: 460 nm for carotenoid pigments and 666 nm for chlorophyll pigments for oil samples diluted in

( ) -1 AV=100QV 1.2 A -A -A m 12 0 é ù ë û (3)

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349

); m – weight of the fat sample

can be calculated from the formula (3)

ide values measured by both methods.

(g).

350 nm [3].

cm-3); V – volume in which the fat sample is dissolved (cm3

$$\ln \frac{I\_0}{I} = \ln \frac{1}{T} = \varepsilon cl = A \tag{2}$$

where: I0, I – intensity of light coming in and out of the sample, respectively; ε – extinction molar coefficient; c– molar concentration of substance; l– thickness of the sample (cm). The transmission of the light by the sample is shown in figure 1. Absorption of the studied sam‐ ple depends on the length of the radiation wave, the thickness of the sample and the charac‐ teristic extinction coefficient at a given wavelength.

**Figure 1.** Illustration of Lambert-Beers's law.

The UV-VIS spectroscopy is mainly used to examine the quality of edible oils regarding a number of parameters including the anisidine value. Anisidine value is a measurement of the level of fats oxidation, and is used for the assessment of poorer quality oils. Precisely, it is the measure of aldehyde production during oxidation of fats. The anisidine value (AV) is defined as one hundred-fold value of absorbance of a solution of a fat sample containing al‐ dehydes which have reacted with p-anisidine. The aforementioned aldehydes are dienals or alka-2-enals and both are one of the final products of lipids oxidation. The highest permissi‐ ble value of AV for edible oils is 8. AV is also an element of Totox (total oxidation value), another factor indicating deterioration level of total fat. The value of Totox is calculated as the sum of two-fold value of AV and peroxide value. According to european standard [2], the measurement of absorbance is performed for three solutions (p-anisidine and sample of fat (A1), acetic acid and sample of fat (A0), and, lastly, blind sample being a mixture of panisidine and isooctane (A2)) at the wavelength 350 nm in a 1 cmcuvette. Theanisidine value can be calculated from the formula (3)

The aim of this paper is to demonstrate applicability of four spectroscopic techniques, e.g. UV–VIS spectroscopy, fluorescence, infrared and Raman spectroscopy, as rapid analysis methods to determine the quality of cereals, cereals products and oils. Additionally, physi‐

Absorption spectroscopy in the UV–VIS region is based on the Lambert-Beer's law, ex‐

εcl

where: I0, I – intensity of light coming in and out of the sample, respectively; ε – extinction molar coefficient; c– molar concentration of substance; l– thickness of the sample (cm). The transmission of the light by the sample is shown in figure 1. Absorption of the studied sam‐ ple depends on the length of the radiation wave, the thickness of the sample and the charac‐

The UV-VIS spectroscopy is mainly used to examine the quality of edible oils regarding a number of parameters including the anisidine value. Anisidine value is a measurement of the level of fats oxidation, and is used for the assessment of poorer quality oils. Precisely, it is the measure of aldehyde production during oxidation of fats. The anisidine value (AV) is defined as one hundred-fold value of absorbance of a solution of a fat sample containing al‐

<sup>0</sup> <sup>1</sup> ln ln *<sup>I</sup> cl A I T* = == e

<sup>0</sup> I I 10- <sup>=</sup> (1)

(2)

cal foundations of the aforementioned methods are described.

**2. UV-VIS spectroscopy**

348 Advances in Agrophysical Research

pressed by the following equations (1, 2)

teristic extinction coefficient at a given wavelength.

**Figure 1.** Illustration of Lambert-Beers's law.

$$\text{AV} = 100 \text{QV} \left[ \text{1.2} \left( \text{A}\_1 \text{-A}\_2 \right) \text{-A}\_0 \right] \text{m}^{-1} \tag{3}$$

where: Q – content of the sample in the solution based on which the AV is expressed (g cm-3); V – volume in which the fat sample is dissolved (cm3 ); m – weight of the fat sample (g).

The anisidine value can be also measured by using Flow Injection Analysis (FIA) combined with UV–VIS spectroscopy. Thanks to the implementation of FIA, the period of time re‐ quired for analysis can be significantly shortened. Additionally, the number of reagents is also maintained at very reasonable level. Sample of fat dissolved in propanol-2 is injected into continuous flow of p-anisidine with a mixture of solvents: propanol-2 and glacial acetic acid. Spectrophotometer is used as a detector, and the value of absorbance is measured at 350 nm [3].

The process of fat deterioration is also described by the peroxide value (PV). The deteriora‐ tion takes place during lipids' exposition to some external factors including temperature, daylight and oxygen. It results in production of peroxides and hydroperoxides, which are regarded as products of fatty acids oxidation. The highest value of PV for oil produced through cold press extraction is 10 meq O2 kg-1, while regarding refined oil it may reach the amount of 5 meq O2 kg-1. The PV value is measured by employing UV–VIS spectrometer as detector [4, 5]. Method of PV measurement of the frying canola oil was developed by Talpur et al. [6]. The authors used stoichiometric reaction of triphenylphosphine (TPP) with the hy‐ droperoxides to produce triphenylphosphine oxide (TPPO) which shown absorbance maxi‐ mum at 240 nm. Therefore, the developed method could serve as an alternative to the titration method for the determination of PV in frying oils due to high correlation of perox‐ ide values measured by both methods.

Another parameter of oil quality is general colour which is determined by the saturation of chlorophyll or carotenoid pigments. Unlike oil produced through cold press extraction, re‐ fined oil has low saturation intensity colour, as most pigments are removed in the oil refine‐ ment. Carotenoid pigments are included to antioxidants. For this reason, oils with high content of carotenoinds are regarded as healthier and of higher quality. The general colour is assayed spectrophotometrically for oil samples diluted in CCl4, at two wavelengths: 460 nm for carotenoid pigments and 666 nm for chlorophyll pigments for oil samples diluted in CCl4 due to polish standard [7]; or 442 nm for carotenoid pigments and 668 nm for chloro‐ phyll pigments when oil samples are dissolved in hexane [7]. Absorbance values obtained for carotenoid and chlorophyll pigments are summed up, multiplied by 1000, and given in the form of an integer or as general colour value:

$$\mathbf{B} = \left(\mathbf{A}\_{4\60} + \mathbf{A}\_{6\66}\right)\mathbf{1}000\tag{4}$$

( ) ( ) -1 -1 670 630 710 *Pheop mg kg A A A L*

where: A – is the absorbance of the oil at the respective wavelength; L - the cell thickness

Fluorescence is the emission of light subsequent to absorption of ultraviolet or visible light of a fluorescent molecule, called a fluorophore. To typical fluorophores are included qui‐ nine, fluorescein, acridine orange, rhodamine B and pyridine 1 [11]. The general principle of the phenomenon is illustrated by Jablonski diagram, as shown in figure 2. The singlet ground, first and second electronic states are depicted by S0, S1, and S2, respectively. The first step of the fluorescence is the excitation of the molecule from the ground state (S0) to the one of excited states (S1, S2) by the absorption of light. This is followed by a vibrational relaxation or internal conversion, where the molecule undergoes a transition from an upper excited state (S2) to a lower one (S1), without any radiation. Finally, the fluorescence occurs, typically 10-8 s after excitation, when the electron returns to the ground state (S0). Emitting light has

Food analysis has exploited the characteristic advantages of fluorescence spectroscopy, i.e. high sensitivity and specificity. However, the technique alone is not usually used in this field. It is mainly linked with liquid chromatography (e.g. HPLC), and the fluorymeter is used as a detector. The combination of these techniques is still advantageous for detecting extremely low concentrations of contaminants such as toxins (mycotoxins), pathogenic mi‐ crobes (bacterial species: *Salmonella*, *Escherichia coli*), antibiotics (e.g. penicilin, tetracycline, oxytetracycline), and food additives (e.g. aspartam, salicylates). Other important applica‐ tions of fluorescence in food area is the analysis of structure changes in proteins, analysis of

energy equal to the difference between energies of ground and excited states.

´ = 345.3 - 0.5 é ù <sup>+</sup> ë û (8)

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351

a

some carbohydrates and lipids in oils.[12]

**Figure 2.** Jablonski diagram.

(mm).

**3. Fluorescence**

or

$$\mathbf{B} = \left(\mathbf{A}\_{442} + \mathbf{A}\_{668}\right) \mathbf{1}000\tag{5}$$

The concentration of carotenoids can also be detected through the use of the UV–VIS meth‐ od due to the British norm BS 684: Section 2.20:1977 [8]. The absorbance of oil diluted in cy‐ clohexane is measured at the wavelength 445 nm and the proportion of carotenoid expressed by β-carotene content can be calculated using the following equation

$$\beta \text{ - } \text{car} \left( \text{mg} \times \text{kg}^{\cdot \cdot 1} \right) = \text{383E} \left( \text{PC} \right)^{\cdot \cdot 1} \tag{6}$$

where: E – the difference in measured absorbance values for oil sample and cyclohexane; P – optical pathlength (cm); C – concentration of the sample (g 100ml-1).

Chlorophylls also influence general colour of oils, especially pheophytins, which have a prooxidative properties. They give some bitter note as well as green colouring to both cold extract‐ ed oil and olive oil from green olives. The smaller concentration of chlorophylls in oil sample, the oil has the higher quality. The chlorophyll concentration can be determined with the AOCS Official Method Cc 13d-55 [8, 9]. Following the method, the measurement of chlorophyll ab‐ sorption is performed at three wavelengths, namely: 630 nm, 670 nm and 710 nm. They refer to the absorbance of the oil sample diluted in carbon tetrachloride at λ = 625.5, 665.5 and 705.5 nm for oil samples diluted in mixture of ethanol and isooctane, or λ = 630, 665 and 710 nm for oil samples diluted in mixture of ethanol and heptane. The concentration of total chlorophyll (in carbon tetrachloride) is calculated from the following equation:

$$\text{Chl} \left( \text{mg} \times \text{kg}^{-1} \right) = \left[ \text{A}\_{670} \cdot 0.5 \left( \text{A}\_{630} \text{+A}\_{710} \right) \right] \left( 0.901 \text{L} \right)^{\text{-1}} \tag{7}$$

where: A – is the absorbance of the oil at the respective wavelength; L – the cell thickness (cm).

The main chlorophyll pigment, occurring in oils, is pheophytin α. The concentration of this dye can be calculated from the equation (8), as featured in the work of Psomiadou and Tsi‐ midou [10]:

$$\text{Pheop} \alpha \left( \text{mg} \times \text{kg}^{-1} \right) = 345.3 \left[ \text{A}\_{670} \text{ -} 0.5 \left( \text{A}\_{630} + \text{A}\_{710} \right) \right] \text{L}^{-1} \tag{8}$$

where: A – is the absorbance of the oil at the respective wavelength; L - the cell thickness (mm).

### **3. Fluorescence**

CCl4 due to polish standard [7]; or 442 nm for carotenoid pigments and 668 nm for chloro‐ phyll pigments when oil samples are dissolved in hexane [7]. Absorbance values obtained for carotenoid and chlorophyll pigments are summed up, multiplied by 1000, and given in

The concentration of carotenoids can also be detected through the use of the UV–VIS meth‐ od due to the British norm BS 684: Section 2.20:1977 [8]. The absorbance of oil diluted in cy‐ clohexane is measured at the wavelength 445 nm and the proportion of carotenoid

( ) ( )

where: E – the difference in measured absorbance values for oil sample and cyclohexane; P –

Chlorophylls also influence general colour of oils, especially pheophytins, which have a prooxidative properties. They give some bitter note as well as green colouring to both cold extract‐ ed oil and olive oil from green olives. The smaller concentration of chlorophylls in oil sample, the oil has the higher quality. The chlorophyll concentration can be determined with the AOCS Official Method Cc 13d-55 [8, 9]. Following the method, the measurement of chlorophyll ab‐ sorption is performed at three wavelengths, namely: 630 nm, 670 nm and 710 nm. They refer to the absorbance of the oil sample diluted in carbon tetrachloride at λ = 625.5, 665.5 and 705.5 nm for oil samples diluted in mixture of ethanol and isooctane, or λ = 630, 665 and 710 nm for oil samples diluted in mixture of ethanol and heptane. The concentration of total chlorophyll (in

> ( ) ( ) ( ) -1 -1 Chl mg×kg = A -0.5 A +A 0.901L 670 630 710 é ù

where: A – is the absorbance of the oil at the respective wavelength; L – the cell thickness (cm).

The main chlorophyll pigment, occurring in oils, is pheophytin α. The concentration of this dye can be calculated from the equation (8), as featured in the work of Psomiadou and Tsi‐


expressed by β-carotene content can be calculated using the following equation

b

optical pathlength (cm); C – concentration of the sample (g 100ml-1).

carbon tetrachloride) is calculated from the following equation:

( ) 460 666 B= A +A 1000 (4)

( ) 442 668 B= A +A 1000 (5)


ë û (7)

the form of an integer or as general colour value:

350 Advances in Agrophysical Research

or

midou [10]:

Fluorescence is the emission of light subsequent to absorption of ultraviolet or visible light of a fluorescent molecule, called a fluorophore. To typical fluorophores are included qui‐ nine, fluorescein, acridine orange, rhodamine B and pyridine 1 [11]. The general principle of the phenomenon is illustrated by Jablonski diagram, as shown in figure 2. The singlet ground, first and second electronic states are depicted by S0, S1, and S2, respectively. The first step of the fluorescence is the excitation of the molecule from the ground state (S0) to the one of excited states (S1, S2) by the absorption of light. This is followed by a vibrational relaxation or internal conversion, where the molecule undergoes a transition from an upper excited state (S2) to a lower one (S1), without any radiation. Finally, the fluorescence occurs, typically 10-8 s after excitation, when the electron returns to the ground state (S0). Emitting light has energy equal to the difference between energies of ground and excited states.

Food analysis has exploited the characteristic advantages of fluorescence spectroscopy, i.e. high sensitivity and specificity. However, the technique alone is not usually used in this field. It is mainly linked with liquid chromatography (e.g. HPLC), and the fluorymeter is used as a detector. The combination of these techniques is still advantageous for detecting extremely low concentrations of contaminants such as toxins (mycotoxins), pathogenic mi‐ crobes (bacterial species: *Salmonella*, *Escherichia coli*), antibiotics (e.g. penicilin, tetracycline, oxytetracycline), and food additives (e.g. aspartam, salicylates). Other important applica‐ tions of fluorescence in food area is the analysis of structure changes in proteins, analysis of some carbohydrates and lipids in oils.[12]

**Figure 2.** Jablonski diagram.

The high specificity of fluorescence is due to use of two spectra, i.e. excitation and emission spectra, while the high sensitivity of the technique is a result of measuring radiation against absolute darkness. However, the use of only excitation and emission wavelengths could lim‐ it the ability of fluorescence spectroscopy to determine the quality of food systems. To com‐ ply with this requirement, the variation in the excitation and emission wavelengths allows simultaneous determination of compounds in several food products. This could be realized by using synchronous fluorescence spectroscopy (SFS) [13].

intensity at both 440 and 455 nm, a medium band around 681 nm and a strong one at 525 nm. The latter two bands have been ascribed to chlorophyll and vitamin E compounds, re‐ spectively. All refined oils showed only one intense peak at 445 nm, which is due to fatty acid oxidation products formed as a result of the large percentage of polyunsaturated fatty acids present in these oils. Fluorescence is regarded as the technique that provided the best models for anisidine and iodine values, oligomers and vitamin E content in deteriorated oil

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Infrared (IR) radiation was discovered by F.W Herschel in 1800. This is an electromagnetic radiation extending from 780 nm to 1 mm. The IR range is divided into the following three bands: near-infrared (NIR; 780 nm – 5 μm), mid-infrared (MIR; 5 – 30 μm) and far-infrared

Infrared (IR) spectroscopy is a technique based on the vibrations of the atoms of a molecule. An infrared spectrum is commonly obtained by passing infrared radiation through a sample and determining what fraction of the incident radiation is absorbed at a particular energy. The energy at which any peak in an absorption spectrum appears corresponds to the fre‐ quency of a vibration of a part of a sample molecule. There are different kinds of vibrations observed in the infrared as well as Raman spectra. Vibrations observed in diatomic mole‐ cules are shown in fig.3. IR spectroscopy gives information on molecular structure through the frequencies of the normal modes of vibration of the molecule. A normal mode is one in which each atom executes a simple harmonic oscillation about its equilibrium position. All atoms move in phase with the same frequency, while the center of gravity of the molecule does not move. There are 3N-6 normal modes of vibrations (known as fundamentals) of a molecule (3N-5 for linear molecules), where N is the number of atoms. For a molecule with no symmetry, all 3N-6 fundamental modes are active in the IR and may give rise to absorp‐ tions. There are also observed overtones in the IR spectra. Overtones has frequencies corre‐ sponding approximately to twice, three times etc. that of the fundamental. The frequencies

Vibrations of certain functional groups such as –OH, –NH2, –CH3, C=O, C6H5–, and so on always give rise to bands in the IR spectrum within well-defined frequency ranges regard‐ less of the molecule containing the functional group. The IR spectrum of any compound that contains a C=O group has a strong band between 1800 and 1650 cm-1. Compounds contain‐ ing –NH2 groups have two IR bands between 3400 and 3300 cm-1. The spectrum of a com‐ pound containing the C6H5– group has sharp peaks near 1600 and 1500 cm-1 due to stretching modes of the benzene ring. The explanation of these characteristic diatomic group frequencies lies in the approximately constant values of the stretching force constant of a bond in different molecules. Thus, the IR spectrum can be regarded as a 'fingerprint' of the

after repeated frying cycles [24].

of many overtone bands are in the NIR region [25].

**4. Infrared spectroscopy**

(FIR; 30 – 1000 μm).

molecule [26].

Fluorescence spectroscopy is one of the most valuable instrumental analytical techniques for determining causes of food poisoning by analyzing concentration of toxins, especially myco‐ toxins. Almost all mycotoxins, apart from aflatoxins (aflatoxins B1 and B2 exhibit blue fluo‐ rescence, while aflatoxins G1 and G2 show yellow-green fluorescence [14]), do not exhibit fluorescence. For this reason, the technique is connected with other analytical techniques and spectrofluorymeter serves as a detector. Corneli and Maragos (1998) used capillary elec‐ trophoresis (CE) with a laser induced fluorescence detector to determine ochratoxin A in roasted coffee, corn and sorghum [15]. CE has also been used in corn samples to analyze fu‐ monisin B1, which was fluorescein-labeled due to lack of a UV chromophore [16]. Maragos and Plattner (2002) developed a rapid test for deoxynivalenol (DON) in wheat using the principle of fluorescence polarization (FP) immunoassay. The assay was based on the com‐ petition between DON and a novel DON-fluorescein tracer for a DON-specific monoclonal antibody in solution. FP immunoassay utilizes the interaction of a toxin-specific antibody with a toxin-fluorophore conjugate (tracer) to effectively decrease the rate of rotation of the tracer. Binding of the antibody to the tracer increases polarization. In the presence of free toxin less of the antibody is bound to the tracer, reducing polarization [17]. The FP immuno‐ assays have been also developed for the fumonisin mycotoxin detection [18].

Fluorescence has been also used in analysis of cereals and cereals products. Zandomeneghi [19] used fluorescence spectroscopy to differentiate between different cereal flours (e.g. rise, maize). Emission spectra of red and white wheat kernels were recorded by Ram and coworkers (2004) and a clear difference was observed between the two group of samples. This difference has been attributed to the morphological variation in the pericarp and nuclear or‐ ganization of the two varieties of wheat [20]. The fluorescence spectroscopy has been also used to monitor wheat flour refinement and milling efficiency by recording emission spectra of ferulic acid and riboflavin [21].

One of the most important edible oils is olive oil, which market price depends on its quality. The most expensive is the extra-virgin olive oil (EVOO) owing to its high quality. For eco‐ nomic reasons, it may be adulterated by the addition of cheaper oils such as refined olive oil, residue oil, synthetic olive oil-glycerol products, seed oils and nut oils. For this reason, a rapid method to detect such a practice is important for quality control and labeling purposes [13]. Sayago et al. [22] applied fluorescence spectroscopy for detecting hazelnut oil adultera‐ tion in virgin olive oils. Kyriakidis and Skarkalis [23] used excitation wavelength of 360 nm to differentiate between common vegetable oils, including olive oil, olive residual oil, re‐ fined olive oil, corn oil, soybean oil, sunflower oil and cotton oil. All the oils studied showed a strong fluorescence band at 430 – 450 nm, except for virgin olive oil, which exhibited a low intensity at both 440 and 455 nm, a medium band around 681 nm and a strong one at 525 nm. The latter two bands have been ascribed to chlorophyll and vitamin E compounds, re‐ spectively. All refined oils showed only one intense peak at 445 nm, which is due to fatty acid oxidation products formed as a result of the large percentage of polyunsaturated fatty acids present in these oils. Fluorescence is regarded as the technique that provided the best models for anisidine and iodine values, oligomers and vitamin E content in deteriorated oil after repeated frying cycles [24].

#### **4. Infrared spectroscopy**

The high specificity of fluorescence is due to use of two spectra, i.e. excitation and emission spectra, while the high sensitivity of the technique is a result of measuring radiation against absolute darkness. However, the use of only excitation and emission wavelengths could lim‐ it the ability of fluorescence spectroscopy to determine the quality of food systems. To com‐ ply with this requirement, the variation in the excitation and emission wavelengths allows simultaneous determination of compounds in several food products. This could be realized

Fluorescence spectroscopy is one of the most valuable instrumental analytical techniques for determining causes of food poisoning by analyzing concentration of toxins, especially myco‐ toxins. Almost all mycotoxins, apart from aflatoxins (aflatoxins B1 and B2 exhibit blue fluo‐ rescence, while aflatoxins G1 and G2 show yellow-green fluorescence [14]), do not exhibit fluorescence. For this reason, the technique is connected with other analytical techniques and spectrofluorymeter serves as a detector. Corneli and Maragos (1998) used capillary elec‐ trophoresis (CE) with a laser induced fluorescence detector to determine ochratoxin A in roasted coffee, corn and sorghum [15]. CE has also been used in corn samples to analyze fu‐ monisin B1, which was fluorescein-labeled due to lack of a UV chromophore [16]. Maragos and Plattner (2002) developed a rapid test for deoxynivalenol (DON) in wheat using the principle of fluorescence polarization (FP) immunoassay. The assay was based on the com‐ petition between DON and a novel DON-fluorescein tracer for a DON-specific monoclonal antibody in solution. FP immunoassay utilizes the interaction of a toxin-specific antibody with a toxin-fluorophore conjugate (tracer) to effectively decrease the rate of rotation of the tracer. Binding of the antibody to the tracer increases polarization. In the presence of free toxin less of the antibody is bound to the tracer, reducing polarization [17]. The FP immuno‐

assays have been also developed for the fumonisin mycotoxin detection [18].

of ferulic acid and riboflavin [21].

Fluorescence has been also used in analysis of cereals and cereals products. Zandomeneghi [19] used fluorescence spectroscopy to differentiate between different cereal flours (e.g. rise, maize). Emission spectra of red and white wheat kernels were recorded by Ram and coworkers (2004) and a clear difference was observed between the two group of samples. This difference has been attributed to the morphological variation in the pericarp and nuclear or‐ ganization of the two varieties of wheat [20]. The fluorescence spectroscopy has been also used to monitor wheat flour refinement and milling efficiency by recording emission spectra

One of the most important edible oils is olive oil, which market price depends on its quality. The most expensive is the extra-virgin olive oil (EVOO) owing to its high quality. For eco‐ nomic reasons, it may be adulterated by the addition of cheaper oils such as refined olive oil, residue oil, synthetic olive oil-glycerol products, seed oils and nut oils. For this reason, a rapid method to detect such a practice is important for quality control and labeling purposes [13]. Sayago et al. [22] applied fluorescence spectroscopy for detecting hazelnut oil adultera‐ tion in virgin olive oils. Kyriakidis and Skarkalis [23] used excitation wavelength of 360 nm to differentiate between common vegetable oils, including olive oil, olive residual oil, re‐ fined olive oil, corn oil, soybean oil, sunflower oil and cotton oil. All the oils studied showed a strong fluorescence band at 430 – 450 nm, except for virgin olive oil, which exhibited a low

by using synchronous fluorescence spectroscopy (SFS) [13].

352 Advances in Agrophysical Research

Infrared (IR) radiation was discovered by F.W Herschel in 1800. This is an electromagnetic radiation extending from 780 nm to 1 mm. The IR range is divided into the following three bands: near-infrared (NIR; 780 nm – 5 μm), mid-infrared (MIR; 5 – 30 μm) and far-infrared (FIR; 30 – 1000 μm).

Infrared (IR) spectroscopy is a technique based on the vibrations of the atoms of a molecule. An infrared spectrum is commonly obtained by passing infrared radiation through a sample and determining what fraction of the incident radiation is absorbed at a particular energy. The energy at which any peak in an absorption spectrum appears corresponds to the fre‐ quency of a vibration of a part of a sample molecule. There are different kinds of vibrations observed in the infrared as well as Raman spectra. Vibrations observed in diatomic mole‐ cules are shown in fig.3. IR spectroscopy gives information on molecular structure through the frequencies of the normal modes of vibration of the molecule. A normal mode is one in which each atom executes a simple harmonic oscillation about its equilibrium position. All atoms move in phase with the same frequency, while the center of gravity of the molecule does not move. There are 3N-6 normal modes of vibrations (known as fundamentals) of a molecule (3N-5 for linear molecules), where N is the number of atoms. For a molecule with no symmetry, all 3N-6 fundamental modes are active in the IR and may give rise to absorp‐ tions. There are also observed overtones in the IR spectra. Overtones has frequencies corre‐ sponding approximately to twice, three times etc. that of the fundamental. The frequencies of many overtone bands are in the NIR region [25].

Vibrations of certain functional groups such as –OH, –NH2, –CH3, C=O, C6H5–, and so on always give rise to bands in the IR spectrum within well-defined frequency ranges regard‐ less of the molecule containing the functional group. The IR spectrum of any compound that contains a C=O group has a strong band between 1800 and 1650 cm-1. Compounds contain‐ ing –NH2 groups have two IR bands between 3400 and 3300 cm-1. The spectrum of a com‐ pound containing the C6H5– group has sharp peaks near 1600 and 1500 cm-1 due to stretching modes of the benzene ring. The explanation of these characteristic diatomic group frequencies lies in the approximately constant values of the stretching force constant of a bond in different molecules. Thus, the IR spectrum can be regarded as a 'fingerprint' of the molecule [26].

**Wavelength [nm] Assignment**

1932 2058 2180

2302 2342

1718 1760

2308 2346

1932 2100

2290 2324

**Water** 1454 1st overtone O–H stretching

**Proteins** 1208 2nd overtone C–H stretching

1734 1st overtone C–H stretching

**Oil** 1210 2nd overtone C–H stretching

1406 1st overtone H–N and O–H stretching

2114 combinations N–H and O–H stretching

1464 1st overtone H–N and O–H stretching

**Starch** 1204 2nd overtone C–H stretching

1465 1st overtone H–N and O–H stretching

combinations N–H and O–H stretching

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combination C–H stretching

1st overtone C–H stretching

combination C–H stretching

combination C–H stretching

**Table 1.** Principal absorption bands of water, oil, protein and starch observed in the NIR region.

combinations N–H and O–H stretching

The application of NIR analysis in wheat and wheat products has included flour yield, dam‐ aged starch, water absorption, dough development time, extensibility and loaf volume measurements. The use of NIR technology to determine the protein and moisture contents of both wheat and flour is now routine practice in flour mills worldwide. It is used for test‐ ing each delivery of wheat in order to make decisions about acceptance, price and binning; for determination of conditioning time from measurement of hardness; and for analyzing flour to check that it complies with specifications before shipment to the customer [28].

1932 O–H combinations

**Figure 3.** Oscillations observed in diatomic molecules.

#### **4.1. Near-infrared spectroscopy**

Near-infrared (NIR) spectroscopy has been primarily employed in the quantitative analysis of foods. The spectroscopy has been applied to measure moisture, fat, protein and carbohy‐ drate content in wide variety of foods. The most significant advantage is its ability to deter‐ mine simultaneously several components in a food sample within a short time. The precision of NIR analysis for a wide range of applications is comparable to or better than that of the chemical techniques it replaces. On the other hand, the main disadvantage of NIR quantitative analysis is that it requires calibration using samples of known composition. This has seriously limited the use of NIR spectroscopy because of the large amount of time and expense required for the development of calibrations. This disadvantage is compound‐ ed by the problem of calibration instability resulting from changes in sample or instrument characteristics over time, which can make frequent recalibration necessary, and the lack of transferability of calibrations owing to optical differences between instruments. Other disad‐ vantages of NIR analysis include the need for high-precision spectroscopic instruments, the complexity of data treatment, and the lack of sensitivity for minor constituents [27].

NIR region of the IR spectrum are due to overtones and combinations of the fundamental vibrations observed in the MIR region. Overtones has frequencies corresponding approxi‐ mately to twice, three times etc. that of the fundamental, while combination bands arise by interaction of two or more vibrations taking place simultaneously and the frequency of a combination band is the sum of multiples of the relevant fundamental frequencies. Vibra‐ tions involving C–H, O–H, N–H and possibly S–H and C=O bonds are responsible for the majority of the observed absorption bands in the NIR region. Table 1 presents principal ab‐ sorption bands of water, oil, protein and starch, which are observed in the NIR region.


**Figure 3.** Oscillations observed in diatomic molecules.

Near-infrared (NIR) spectroscopy has been primarily employed in the quantitative analysis of foods. The spectroscopy has been applied to measure moisture, fat, protein and carbohy‐ drate content in wide variety of foods. The most significant advantage is its ability to deter‐ mine simultaneously several components in a food sample within a short time. The precision of NIR analysis for a wide range of applications is comparable to or better than that of the chemical techniques it replaces. On the other hand, the main disadvantage of NIR quantitative analysis is that it requires calibration using samples of known composition. This has seriously limited the use of NIR spectroscopy because of the large amount of time and expense required for the development of calibrations. This disadvantage is compound‐ ed by the problem of calibration instability resulting from changes in sample or instrument characteristics over time, which can make frequent recalibration necessary, and the lack of transferability of calibrations owing to optical differences between instruments. Other disad‐ vantages of NIR analysis include the need for high-precision spectroscopic instruments, the

complexity of data treatment, and the lack of sensitivity for minor constituents [27].

NIR region of the IR spectrum are due to overtones and combinations of the fundamental vibrations observed in the MIR region. Overtones has frequencies corresponding approxi‐ mately to twice, three times etc. that of the fundamental, while combination bands arise by interaction of two or more vibrations taking place simultaneously and the frequency of a combination band is the sum of multiples of the relevant fundamental frequencies. Vibra‐ tions involving C–H, O–H, N–H and possibly S–H and C=O bonds are responsible for the majority of the observed absorption bands in the NIR region. Table 1 presents principal ab‐ sorption bands of water, oil, protein and starch, which are observed in the NIR region.

**4.1. Near-infrared spectroscopy**

354 Advances in Agrophysical Research

**Table 1.** Principal absorption bands of water, oil, protein and starch observed in the NIR region.

The application of NIR analysis in wheat and wheat products has included flour yield, dam‐ aged starch, water absorption, dough development time, extensibility and loaf volume measurements. The use of NIR technology to determine the protein and moisture contents of both wheat and flour is now routine practice in flour mills worldwide. It is used for test‐ ing each delivery of wheat in order to make decisions about acceptance, price and binning; for determination of conditioning time from measurement of hardness; and for analyzing flour to check that it complies with specifications before shipment to the customer [28].

NIR was used in Australia to predict optimum fertilizer requirements of cereal crops by analysis of total nitrogen and carbohydrate (fructan) in plant tissue samples [29]. Wheat hardness had been measured in both meal and whole grain by using NIR [30]. NIR spectro‐ scopy has also been shown to be useful in the study of changes in starches during process‐ ing and storage [31]. This utility is primarily due to the sensitivity of the O–H stretching mode overtone absorptions of starch and of the water bound to starch to changes in hydro‐ gen bonding that accompany changes in starch structure. The spectroscopy combined with chemometrics has been applied to discriminate wheat varieties [32]. It was developed a dis‐ criminant equation, which gave 94% correctly identified varieties.

The MIR spectroscopy, similar to NIR spectroscopy, is applying to analysis of moisture, pro‐ tein, carbohydrate and fat content in food products. Owing to the intense absorption of MIR radiation by water, FTIR was used to determination of moisture of food emulsions e.g. but‐ ter [37] and mayonnaise [38]. FTIR technique is also well established as a powerful tool for the study of protein secondary structure, based primarily on examination of the amide I re‐ gion (1600 – 1700 cm-1) [39]. Proteins are widely used as ingredients in the food processing industry because of their useful properties such as emulsification, gelation and thickening. These properties are highly related to the secondary structure of protein, which can change during processing and storage of food products [27]. Examination of amide I region are made by mathematical process called deconvolution. Deconvoluted amide I band of wheat

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gluten are presented in figure 4 [40].

**Wavenumber [cm-1] Assignment**

**Water**

**Proteins**

1480 – 1575 Amide II (C–N stretching and N–H bending) 1230 – 1300 Amide III (C–N stretching and N–H bending)

**Carbohydrates**

MIR spectroscopy play a crucial role in research on the chemistry of fats and oils. An impor‐ tant result of early investigations of the IR spectra of fats and oils was the identification of an absorption band at 996 cm-1 which is characteristic for isolated trans double bonds. Al‐ though the double bonds in naturally occurring fats and oils predominantly have the cis configuration, extensive cis-trans isomerization occurs during industrial catalytic hydroge‐ nation processes, which are widely employed to convert oils to fats and to increase the oxi‐ dative stability of polyunsaturated oils. Van de Voort et al. [41] developed a method for the simultaneous determination of trans unsaturation, cis unsaturation and total unsaturation,

800 – 1400 Skeletal stretching and bending

1600 – 1690 Amide I (C=O stretching)

**Fats**

3200 – 3600 O–H stretching 1650 H–OH stretching

2800 – 3000 C–H stretching 1725 – 1745 C=O stretchnig 970 C=C–H bending

2800 – 3000 C–H stretching

**Table 2.** The major bands of food components localized in MIR region.

Recently, NIR spectroscopy is often connected with hyperspectral imaging system. Canadi‐ an wheat classes has been determined by using near-infrared hyperspectral imaging (NIR-HSI) system [33]. Seventy-five relative reflectance intensities were extracted from the scanned images and used for the differentiation of wheat classes using a statistical classifier and an artificial neural network (ANN) classifier. Classification accuracies were 100%. This imaging system has also been used to detect spectral differences between healthy and dam‐ aged products, which are connected with different chemical composition of these products. Singh et al. [34, 35] studied insect-damaged kernels. It was observed that insect-damaged kernels had less starch compared to healthy ones, due to consumption of starch by insects during their development.

The study of food authenticity involves establishing whether a sample is genuine in terms of its description, including geographical origin. The application of NIR for authenticity testing of coffee, fruit pulps, milk powders, orange juice, pig carcasses, rice, sausages, sugars, vege‐ table oils, wheat grain and wheat flour have been reviewed by Downey [36]. This spectro‐ scopy is required to classify within a series of possible classes, to identify a particular kind of adulteration or to quantify adulteration.

#### **4.2. Mid-infrared spectroscopy**

Mid-infrared (MIR) spectroscopy can both provide information on structure-functionality relationships and serve as a quantitative analysis tool. For this reason, it is regarded as a highly valuable technique for both food-related research and quality control purposes in the food industry. The Fourier-transform infrared spectroscopy (FTIR) is used the most often.

The mid-infrared spectrum (4000 – 400 cm-1) includes four regions: the X–H stretching re‐ gion (4000 – 2500 cm-1), the triple-bond region (2500 – 2000 cm-1), the double-bond region (2000 – 1500 cm-1) and the fingerprint region (1500 – 600 cm-1). The fundamental vibrations of the X–H stretching region are generally due to O–H, C–H and N–H stretching. Vibrations of C≡C and C≡N bonds are mainly observed in the triple-bond stretching region. Whereas absorption bands corresponding to C=C, C=O and C=N occurs in the double-bond region. The "fingerprint" bands are connected mostly with bending and skeletal vibrations The im‐ portant mid-infrared bands associated with major food components (water, proteins, fats and carbohydrates) are summarized in table 2 [25].

The MIR spectroscopy, similar to NIR spectroscopy, is applying to analysis of moisture, pro‐ tein, carbohydrate and fat content in food products. Owing to the intense absorption of MIR radiation by water, FTIR was used to determination of moisture of food emulsions e.g. but‐ ter [37] and mayonnaise [38]. FTIR technique is also well established as a powerful tool for the study of protein secondary structure, based primarily on examination of the amide I re‐ gion (1600 – 1700 cm-1) [39]. Proteins are widely used as ingredients in the food processing industry because of their useful properties such as emulsification, gelation and thickening. These properties are highly related to the secondary structure of protein, which can change during processing and storage of food products [27]. Examination of amide I region are made by mathematical process called deconvolution. Deconvoluted amide I band of wheat gluten are presented in figure 4 [40].


**Table 2.** The major bands of food components localized in MIR region.

NIR was used in Australia to predict optimum fertilizer requirements of cereal crops by analysis of total nitrogen and carbohydrate (fructan) in plant tissue samples [29]. Wheat hardness had been measured in both meal and whole grain by using NIR [30]. NIR spectro‐ scopy has also been shown to be useful in the study of changes in starches during process‐ ing and storage [31]. This utility is primarily due to the sensitivity of the O–H stretching mode overtone absorptions of starch and of the water bound to starch to changes in hydro‐ gen bonding that accompany changes in starch structure. The spectroscopy combined with chemometrics has been applied to discriminate wheat varieties [32]. It was developed a dis‐

Recently, NIR spectroscopy is often connected with hyperspectral imaging system. Canadi‐ an wheat classes has been determined by using near-infrared hyperspectral imaging (NIR-HSI) system [33]. Seventy-five relative reflectance intensities were extracted from the scanned images and used for the differentiation of wheat classes using a statistical classifier and an artificial neural network (ANN) classifier. Classification accuracies were 100%. This imaging system has also been used to detect spectral differences between healthy and dam‐ aged products, which are connected with different chemical composition of these products. Singh et al. [34, 35] studied insect-damaged kernels. It was observed that insect-damaged kernels had less starch compared to healthy ones, due to consumption of starch by insects

The study of food authenticity involves establishing whether a sample is genuine in terms of its description, including geographical origin. The application of NIR for authenticity testing of coffee, fruit pulps, milk powders, orange juice, pig carcasses, rice, sausages, sugars, vege‐ table oils, wheat grain and wheat flour have been reviewed by Downey [36]. This spectro‐ scopy is required to classify within a series of possible classes, to identify a particular kind

Mid-infrared (MIR) spectroscopy can both provide information on structure-functionality relationships and serve as a quantitative analysis tool. For this reason, it is regarded as a highly valuable technique for both food-related research and quality control purposes in the food industry. The Fourier-transform infrared spectroscopy (FTIR) is used the most often.

The mid-infrared spectrum (4000 – 400 cm-1) includes four regions: the X–H stretching re‐ gion (4000 – 2500 cm-1), the triple-bond region (2500 – 2000 cm-1), the double-bond region (2000 – 1500 cm-1) and the fingerprint region (1500 – 600 cm-1). The fundamental vibrations of the X–H stretching region are generally due to O–H, C–H and N–H stretching. Vibrations of C≡C and C≡N bonds are mainly observed in the triple-bond stretching region. Whereas absorption bands corresponding to C=C, C=O and C=N occurs in the double-bond region. The "fingerprint" bands are connected mostly with bending and skeletal vibrations The im‐ portant mid-infrared bands associated with major food components (water, proteins, fats

criminant equation, which gave 94% correctly identified varieties.

during their development.

356 Advances in Agrophysical Research

of adulteration or to quantify adulteration.

and carbohydrates) are summarized in table 2 [25].

**4.2. Mid-infrared spectroscopy**

MIR spectroscopy play a crucial role in research on the chemistry of fats and oils. An impor‐ tant result of early investigations of the IR spectra of fats and oils was the identification of an absorption band at 996 cm-1 which is characteristic for isolated trans double bonds. Al‐ though the double bonds in naturally occurring fats and oils predominantly have the cis configuration, extensive cis-trans isomerization occurs during industrial catalytic hydroge‐ nation processes, which are widely employed to convert oils to fats and to increase the oxi‐ dative stability of polyunsaturated oils. Van de Voort et al. [41] developed a method for the simultaneous determination of trans unsaturation, cis unsaturation and total unsaturation, which is traditionally expressed as the iodine value (IV), as well as saponification number (SN) (a measure of weight-average molecular weight).

Likewise fluorescence, MIR spectroscopy is used to study adulteration of olive oil by other edible oils. The edible oils widely employed in virgin olive oil adulteration can be lower quality olive oil (refined or pomace olive oil) or other vegetable or seed oils such as corn, peanut, cottonseed, sunflower, soybean and poppy seed oils [50]. Gurdeniz and Ozen [51] wanted to demonstrate that MIR spectroscopy connected with chemometrics is a rapid method to detect and quantify adulteration of extra-virgin olive oil (EVOO) with vegetable oils (rapeseed, cottonseed, and corn-sunflower binary mixture). The adulteration of EVOO by different concentrations of palm oil was studied by using FTIR technique [52]. Not only EVOO is adulterated by a low-quality edible oils but also virgin coconut oil (VCO), which possesses several biological activities such as antiviral and antimicrobial. Rohman and Che Man used FTIR spectroscopy combined with chemometrics to determine the level of adul‐

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The region below 400 cm-1 down to 10 cm-1 is defined as the far-infrared. The region below 200 cm-1 is not readily accessible and there are not many useful spectra-structure correla‐ tions in this region. However, compounds containing halogen atoms, organometallic com‐ pounds and inorganic compounds absorb in the far-infrared and torsional vibrations and

Raman effect arises from the interaction of incident photons with electrons of the matter un‐ der investigation (inelastic scattering of the incident light). During this interaction the pho‐ ton can lose (Stokes' process; h(ν-νR)) or gain (anti-Stokes' process; h(ν+νR)) energy equal to the vibrational energy of the atoms (see fig.5). Consequently the vibrational energy of the atoms increases or decreases. Such communication is possible for the motions of atoms, which modulate the polarizability of the molecule. Intense Raman bands will be observed from non-polar groups, particularly aromatic rings, the vibrations of which produce consid‐ erable modulation of polarizability. The resulting Raman spectrum, presented in wave num‐ bers (cm-1) as the difference between the excited and emitted photon energy, is the vibrational spectrum of the molecule. The effect is very weak, because the energy exchange

Raman spectroscopy (RS) is a vibrational spectroscopy technique, based on the Raman effect. It is an irreplaceable tool for the study of biological events at the molecular level and for identifi‐ cation of molecules. There are several reasons for this. First of all, RS measures the vibrations of atoms. This implies that the positions of the bands, widths and intensities are sensitive to the molecular structure. Vibrations of some molecular groups are very characteristic and there‐ fore can be used for the identification of certain groups or even whole molecules. Second, wa‐ ter causes weak Raman scattering, and consequently molecules can be studied in their natural environment without solvent interference. The third reason for the growing interest in RS is re‐

teration of VCO with corn and sunflower oils [53].

hydrogen bond stretching modes are found in this region [26].

**4.3. Far-infrared spectroscopy**

**5. Raman spectroscopy**

probability is low [54].

**Figure 4.** Deconvoluted amide I band of wheat gluten (αH - α-helix, βS - β-sheet, βT - β turns).

Another area of application of FTIR spectroscopy that has been investigated is its use in the assessment of oil quality and stability. The reaction between unsaturated lipids and atmos‐ pheric oxygen under ambient conditions, termed lipid autooxidation, is a leading cause of deterioration of fats and oils, as well as of any lipid-containing food, as it gives rise to the off-flavors and unpalatable odors associated with oxidative rancidity. FT-IR spectroscopy proved to be the most direct and accurate method of monitoring gross changes in the frying oil over time [24, 42]. A quantitative FTIR method was used for monitoring the oxidative state of frying oils, based on the determination of anisidine value (AV), a measure of alde‐ hydes that are major secondary oxidation products in polyunsaturated oils, has also been re‐ ported [43]. FTIR methods have also been developed to serve as alternatives to the peroxide value (PV) test, which is widely employed by the fats and oils industry to assess the oxida‐ tive status and stability of refined oils. This method entails measurement of the hydroperox‐ ide OO–H stretching absorption, which is observed at 3444 cm-1 in the spectra of neat oils [44]. FTIR spectroscopy was also used to understand in more detail the mechanisms of ther‐ mally induced oxidative processes (thermal oil degradation) in extra-virgin olive oils [45].

FTIR methods for the determination of other minor components present in oils, including free fatty acids in refined [46] and crude oils [47], β-carotene in palm oil [48], and phospholi‐ pids in vegetable oils [49], have also been reported.

Likewise fluorescence, MIR spectroscopy is used to study adulteration of olive oil by other edible oils. The edible oils widely employed in virgin olive oil adulteration can be lower quality olive oil (refined or pomace olive oil) or other vegetable or seed oils such as corn, peanut, cottonseed, sunflower, soybean and poppy seed oils [50]. Gurdeniz and Ozen [51] wanted to demonstrate that MIR spectroscopy connected with chemometrics is a rapid method to detect and quantify adulteration of extra-virgin olive oil (EVOO) with vegetable oils (rapeseed, cottonseed, and corn-sunflower binary mixture). The adulteration of EVOO by different concentrations of palm oil was studied by using FTIR technique [52]. Not only EVOO is adulterated by a low-quality edible oils but also virgin coconut oil (VCO), which possesses several biological activities such as antiviral and antimicrobial. Rohman and Che Man used FTIR spectroscopy combined with chemometrics to determine the level of adul‐ teration of VCO with corn and sunflower oils [53].

#### **4.3. Far-infrared spectroscopy**

which is traditionally expressed as the iodine value (IV), as well as saponification number

(SN) (a measure of weight-average molecular weight).

358 Advances in Agrophysical Research

**Figure 4.** Deconvoluted amide I band of wheat gluten (αH - α-helix, βS - β-sheet, βT - β turns).

Another area of application of FTIR spectroscopy that has been investigated is its use in the assessment of oil quality and stability. The reaction between unsaturated lipids and atmos‐ pheric oxygen under ambient conditions, termed lipid autooxidation, is a leading cause of deterioration of fats and oils, as well as of any lipid-containing food, as it gives rise to the off-flavors and unpalatable odors associated with oxidative rancidity. FT-IR spectroscopy proved to be the most direct and accurate method of monitoring gross changes in the frying oil over time [24, 42]. A quantitative FTIR method was used for monitoring the oxidative state of frying oils, based on the determination of anisidine value (AV), a measure of alde‐ hydes that are major secondary oxidation products in polyunsaturated oils, has also been re‐ ported [43]. FTIR methods have also been developed to serve as alternatives to the peroxide value (PV) test, which is widely employed by the fats and oils industry to assess the oxida‐ tive status and stability of refined oils. This method entails measurement of the hydroperox‐ ide OO–H stretching absorption, which is observed at 3444 cm-1 in the spectra of neat oils [44]. FTIR spectroscopy was also used to understand in more detail the mechanisms of ther‐ mally induced oxidative processes (thermal oil degradation) in extra-virgin olive oils [45].

FTIR methods for the determination of other minor components present in oils, including free fatty acids in refined [46] and crude oils [47], β-carotene in palm oil [48], and phospholi‐

pids in vegetable oils [49], have also been reported.

The region below 400 cm-1 down to 10 cm-1 is defined as the far-infrared. The region below 200 cm-1 is not readily accessible and there are not many useful spectra-structure correla‐ tions in this region. However, compounds containing halogen atoms, organometallic com‐ pounds and inorganic compounds absorb in the far-infrared and torsional vibrations and hydrogen bond stretching modes are found in this region [26].

## **5. Raman spectroscopy**

Raman effect arises from the interaction of incident photons with electrons of the matter un‐ der investigation (inelastic scattering of the incident light). During this interaction the pho‐ ton can lose (Stokes' process; h(ν-νR)) or gain (anti-Stokes' process; h(ν+νR)) energy equal to the vibrational energy of the atoms (see fig.5). Consequently the vibrational energy of the atoms increases or decreases. Such communication is possible for the motions of atoms, which modulate the polarizability of the molecule. Intense Raman bands will be observed from non-polar groups, particularly aromatic rings, the vibrations of which produce consid‐ erable modulation of polarizability. The resulting Raman spectrum, presented in wave num‐ bers (cm-1) as the difference between the excited and emitted photon energy, is the vibrational spectrum of the molecule. The effect is very weak, because the energy exchange probability is low [54].

Raman spectroscopy (RS) is a vibrational spectroscopy technique, based on the Raman effect. It is an irreplaceable tool for the study of biological events at the molecular level and for identifi‐ cation of molecules. There are several reasons for this. First of all, RS measures the vibrations of atoms. This implies that the positions of the bands, widths and intensities are sensitive to the molecular structure. Vibrations of some molecular groups are very characteristic and there‐ fore can be used for the identification of certain groups or even whole molecules. Second, wa‐ ter causes weak Raman scattering, and consequently molecules can be studied in their natural environment without solvent interference. The third reason for the growing interest in RS is re‐ lated to the considerable intensity enhancement (up to 106 ) observable in resonance Raman spectroscopy (RRS) and surface-enhanced Raman spectroscopy (SERS). Fourthly, because the Raman effect is instantaneous (timescale in order of 10-14 s), and due to the recent advances in laser technology, the time-resolved action of molecules down to picosecond resolution can be followed, retaining the value of structural information [54].

**Wavenumber [cm-1] Assignment**

510 525 545

630−670

2912

**Table 3.** Raman bands of major food component.

**Water**

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**Proteins**

1235 – 1245 Amide III (C–N stretching and N–H bending)

1600 – 1700 Amide I (C=O stretching and N–H bending)

**Fats**

**Carbohydrates**

S–S stretching

3200 – 3600 O–H stretching

<sup>700</sup>−<sup>745</sup> C–S stretching

2550 – 2580 S–H stretching 2800 – 3000 C–H stretchnig

 CH2 bending CH3 – CH2 bending C=C stretching 2855 – 2960 C – H stretching

836 C – C stretching 1064 C – O stretching

<sup>2944</sup> C – H stretching

3451 O – H stretching

Raman spectroscopy, likewise IR spectroscopy, has been used to quantify and characterized the lipid components of food systems, including quantitative analysis of the degree of unsa‐ turation and the content of cis and trans isomers, identification or detection of adulteration of various oils, characterization of polymorphism and chain packing, and monitoring of in‐ teractions with other food components or changes induced by processing or storage, such as autooxidation or isomerization. Rapid quantitative analysis of unsaturation and cis and trans isomers content has been reported by using dispersive laser Raman spectroscopy and FT-Raman spectroscopy [57, 58, 59]. Low-resolution Raman spectroscopy was used to moni‐ tor oxidation status of olive oil. Primary and secondary oxidation parameters (e.g. peroxide

**Figure 5.** Scheme of scattering of the light.

The limitations of the technique must also be considered. First of all, the probability of Ram‐ an scattering is very low, so the effect is weak and high concentrations of samples are re‐ quired. Secondly, in Raman experiments excitation within the electronic absorption band often causes photodegradation of the molecule. To avoid such problems, low laser powers, moving samples and independent inspection of the sample integrity are often employed. Fi‐ nally, many molecules, or impurities in the sample, exhibit intense fluorescence, obscuring the Raman spectra [54].

Raman spectroscopy, which is regarded as a complementary technique to IR spectroscopy, is similarly applied to study water, carbohydrate, protein and fat structure in food samples. Raman bands of major food components are shown in table 3. As it was mentioned above, weak Raman scattering of water is the advantage, but it also makes difficult to observe changes in water structure due to weak Raman signals. However, changes in water struc‐ ture have been observed as decrease of intensity of the O–H stretching band at 3250 cm-1 relative to the C–H band at 2938 – 2942 cm-1. It was a result of interaction between water molecules and food proteins [55]. Structure of food proteins may also be analyzed by using RS. The –CO–NH– amide or peptide bond has several distinct and conformationally sensi‐ tive vibrational modes, with the amide I and III bands being the most commonly used for secondary structure characterization. [56]. Changes in food carbohydrate structure inducing by processing or storage can be monitored by this technique. Using RS technique interac‐ tions of carbohydrates with other food components, particularly with water have also been studied [27].


**Table 3.** Raman bands of major food component.

lated to the considerable intensity enhancement (up to 106

followed, retaining the value of structural information [54].

**Figure 5.** Scheme of scattering of the light.

the Raman spectra [54].

360 Advances in Agrophysical Research

studied [27].

spectroscopy (RRS) and surface-enhanced Raman spectroscopy (SERS). Fourthly, because the Raman effect is instantaneous (timescale in order of 10-14 s), and due to the recent advances in laser technology, the time-resolved action of molecules down to picosecond resolution can be

The limitations of the technique must also be considered. First of all, the probability of Ram‐ an scattering is very low, so the effect is weak and high concentrations of samples are re‐ quired. Secondly, in Raman experiments excitation within the electronic absorption band often causes photodegradation of the molecule. To avoid such problems, low laser powers, moving samples and independent inspection of the sample integrity are often employed. Fi‐ nally, many molecules, or impurities in the sample, exhibit intense fluorescence, obscuring

Raman spectroscopy, which is regarded as a complementary technique to IR spectroscopy, is similarly applied to study water, carbohydrate, protein and fat structure in food samples. Raman bands of major food components are shown in table 3. As it was mentioned above, weak Raman scattering of water is the advantage, but it also makes difficult to observe changes in water structure due to weak Raman signals. However, changes in water struc‐ ture have been observed as decrease of intensity of the O–H stretching band at 3250 cm-1 relative to the C–H band at 2938 – 2942 cm-1. It was a result of interaction between water molecules and food proteins [55]. Structure of food proteins may also be analyzed by using RS. The –CO–NH– amide or peptide bond has several distinct and conformationally sensi‐ tive vibrational modes, with the amide I and III bands being the most commonly used for secondary structure characterization. [56]. Changes in food carbohydrate structure inducing by processing or storage can be monitored by this technique. Using RS technique interac‐ tions of carbohydrates with other food components, particularly with water have also been

) observable in resonance Raman

Raman spectroscopy, likewise IR spectroscopy, has been used to quantify and characterized the lipid components of food systems, including quantitative analysis of the degree of unsa‐ turation and the content of cis and trans isomers, identification or detection of adulteration of various oils, characterization of polymorphism and chain packing, and monitoring of in‐ teractions with other food components or changes induced by processing or storage, such as autooxidation or isomerization. Rapid quantitative analysis of unsaturation and cis and trans isomers content has been reported by using dispersive laser Raman spectroscopy and FT-Raman spectroscopy [57, 58, 59]. Low-resolution Raman spectroscopy was used to moni‐ tor oxidation status of olive oil. Primary and secondary oxidation parameters (e.g. peroxide value) were obtained in a rapid, non-destructive and direct way [60]. FT-Raman spectrosco‐ py combined with multivariate analysis procedures was applied to determine the level of adulteration of virgin olive oil by some vegetable oils (soybean, corn and raw olive residue oils) [61].

**Author details**

Chełm, Poland

**References**

Chemistry 2006.

1985; 62, 1495-1500.

1823-1826.

termination of anisidine value.

Chemists' Society1978;55, 539-546.

+ Business Media, LLC; 2006.

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NOŚĆ. Nauka. Technologia. Jakość 2010; 73, 146-157 (in Polish).

els. Journal of the Science of Food and Agriculture 2001; 81, 640-647.

Agnieszka Nawrocka1

and Joanna Lamorska2

1 Bohdan Dobrzansky Institute of Agrophysics, Polish Academy of Sciences, Lublin, Poland

Determination of Food Quality by Using Spectroscopic Methods

http://dx.doi.org/10.5772/52722

363

2 The Institute of Agricultural Sciences, The State School of Higher Education in Chełm,

[1] McGorrin, R.J. Food analysis techniques: Introduction. Encyclopedia of Analytical

[2] European standard PE-EN ISO 6885:2008 – Oils and animal and vegetable fats – De‐

[3] Labrinea E.P., Thomaidis N.S., Georgiou C.A. Direct olive oil anisidine value deter‐

[4] Gray J.I. Measurement of Lipid Oxidation: A Review. Journal of the American Oil

[5] Lezerovich A. Determination of Peroxide Value by Conventional Difference and Dif‐ ference-Derivative Spectrophotometry. Journal of the American Oil Chemists' Society

[6] Talpur M.Y., Sherazi S.T.H., Mahesar S.A., Bhutto A.A. A simplified UV method for determination of peroxide value in thermally oxidized canola oil. Talanta 2010; 80,

[7] Polish standard PN-A-86934:1995 – Oils and animal and vegetable fats – Spectropho‐

[8] Mińkowski K., Grześkiewicz S., Jerzewska M., Ropelewska M. Characteristic of chemical composition of vegetable oil about high contents of linoleic acids ŻYW‐

[9] Dirman H., Dibeklioğlu H. Characterization of Turkish Virgin Olive Oils Produced from Early Harvest Olives. American Oil Chemists' Society (AOCS) 2009; 86, 663-674.

[10] Psomiadou E., Tsimidou M. Pigments in Greek virgin olive oils: occurrence and lev‐

[11] Lakowicz, J.R. Principles of Fluorescence Spectroscopy. New York; Springer Science

mination by flow injection. AnalyticaChimicaActa 2001; 448, 201-206.

Nowadays, Raman spectroscopy is often combined with microscopy (Raman microspectro‐ scopy). The combination results in an analytical method that allows spatially resolved inves‐ tigation of the chemical composition of heterogeneous food and food ingredients. Both qualitative and quantitative information can be obtained using microspectroscopy. A num‐ ber of organic compounds and functional groups can be identified by their unique pattern of absorption, and the intensity of the absorption may be used for the calculation of the relative concentration in the sampled entity. Furthermore, samples of microscopic size can be ana‐ lyzed directly, in air, at ambient temperature and pressure, wet or dry, and in many cases without destroying the sample [62]. Confocal Raman microspectroscopy has been applied to obtain information about microstructure and chemical composition of wheat grain [63]. The work was focused on the protein content and composition of the starchy endosperm and on the aleurone cell walls in arabinoxylan and ferulic acid derivatives. Confocal Raman micro‐ scopy was also used to follow the evolution of protein content and structure during grain development of various wheat varieties selected on the basis of hardness level and aptitude to separation of peripheral layers during milling. Raman microspectroscopy is not only a powerful technique to identify cereal components, but it also gives information about secon‐ dary structure and configuration of these proteins. For instance, the technique permits to de‐ termine the conformation of a non-specific wheat phospholipid transfer protein, and to study the role of disulphide bridges in the stabilization of the α-helical structure. In addi‐ tion, Raman microspectroscopy was used to determine the secondary structure and confor‐ mation of puroindolines, lipid-binding protein of wheat [64].

#### **6. Conclusions**

Spectroscopic methods seem to be very successful at evaluating the food quality. They are used to qualitative as well as quantitative analysis of food products. Furthermore, they pro‐ vide information on structure-functionality relationships (e.g. secondary structure of pro‐ teins). These techniques can be used independently or combined with other analytical techniques such as chromatography and served as detector. Some of them (IR and Raman spectroscopy) are regarded as rapid, no sample preparation techniques which additionally can be used on-line.

The above described methods are mainly used to determine technological parameters (anisi‐ dine value, peroxide value and general color) and authenticity (kind and level of adultera‐ tion) of edible oils. They can also be used to differentiate cereal classes (wheat classes), determine quality of flours, and level of the insects and fungal damage in food products. But first of all, the spectroscopic methods are applied to determine content of the major food components (water, proteins, lipids and carbohydrates). Although some researches claimed that spectroscopy is unsuitable tool for studying food products, nowadays it is used com‐ monly and with a great success.

## **Author details**

value) were obtained in a rapid, non-destructive and direct way [60]. FT-Raman spectrosco‐ py combined with multivariate analysis procedures was applied to determine the level of adulteration of virgin olive oil by some vegetable oils (soybean, corn and raw olive residue

Nowadays, Raman spectroscopy is often combined with microscopy (Raman microspectro‐ scopy). The combination results in an analytical method that allows spatially resolved inves‐ tigation of the chemical composition of heterogeneous food and food ingredients. Both qualitative and quantitative information can be obtained using microspectroscopy. A num‐ ber of organic compounds and functional groups can be identified by their unique pattern of absorption, and the intensity of the absorption may be used for the calculation of the relative concentration in the sampled entity. Furthermore, samples of microscopic size can be ana‐ lyzed directly, in air, at ambient temperature and pressure, wet or dry, and in many cases without destroying the sample [62]. Confocal Raman microspectroscopy has been applied to obtain information about microstructure and chemical composition of wheat grain [63]. The work was focused on the protein content and composition of the starchy endosperm and on the aleurone cell walls in arabinoxylan and ferulic acid derivatives. Confocal Raman micro‐ scopy was also used to follow the evolution of protein content and structure during grain development of various wheat varieties selected on the basis of hardness level and aptitude to separation of peripheral layers during milling. Raman microspectroscopy is not only a powerful technique to identify cereal components, but it also gives information about secon‐ dary structure and configuration of these proteins. For instance, the technique permits to de‐ termine the conformation of a non-specific wheat phospholipid transfer protein, and to study the role of disulphide bridges in the stabilization of the α-helical structure. In addi‐ tion, Raman microspectroscopy was used to determine the secondary structure and confor‐

Spectroscopic methods seem to be very successful at evaluating the food quality. They are used to qualitative as well as quantitative analysis of food products. Furthermore, they pro‐ vide information on structure-functionality relationships (e.g. secondary structure of pro‐ teins). These techniques can be used independently or combined with other analytical techniques such as chromatography and served as detector. Some of them (IR and Raman spectroscopy) are regarded as rapid, no sample preparation techniques which additionally

The above described methods are mainly used to determine technological parameters (anisi‐ dine value, peroxide value and general color) and authenticity (kind and level of adultera‐ tion) of edible oils. They can also be used to differentiate cereal classes (wheat classes), determine quality of flours, and level of the insects and fungal damage in food products. But first of all, the spectroscopic methods are applied to determine content of the major food components (water, proteins, lipids and carbohydrates). Although some researches claimed that spectroscopy is unsuitable tool for studying food products, nowadays it is used com‐

mation of puroindolines, lipid-binding protein of wheat [64].

oils) [61].

362 Advances in Agrophysical Research

**6. Conclusions**

can be used on-line.

monly and with a great success.

Agnieszka Nawrocka1 and Joanna Lamorska2

1 Bohdan Dobrzansky Institute of Agrophysics, Polish Academy of Sciences, Lublin, Poland

2 The Institute of Agricultural Sciences, The State School of Higher Education in Chełm, Chełm, Poland

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**Chapter 15**

**Plant Fibres for Textile and Technical Applications**

Recently natural and made-man polymer fibres are used for preparation of functionalised textiles to achieve smart and intelligent properties. There are numerous application possibil‐ ities of these modified materials. Main pathways for functionalizaton of fibres are: inclusion of functional additives (inorganic particles, polymers, organic compounds); chemical graft‐ ing of additives on the surface of fibres and coating of fibres with layers of functional coat‐ ings. A new approach to produce new materials is by nanotechnology, which offers a wide variety of possibilities for development of materials with improved properties. Composites of cellulose fibres with nano-particles combine numerous advantageous properties of cellu‐ lose with functionality of inorganic particles, hence yielding new, intelligent materials. For preparing cellulose composite materials profound knowledge about fibres properties is needed. Besides, new fibre qualities are demanded to guaranty the modification efficiency. Therefore non-standard methods are involved to determine physical properties of fibres.

In addition to, manufacture, use and removal of traditional textile materials are now consid‐ ered more critically because of increasing environmental consciousness and the demands of legislative authorities. Natural cellulose fibres have successfully proven their qualities when also taking into account an ecological view of fibre materials. Different cellulose fibres can be used for textile and technical applications, e.g. bast or stem fibres, which form fibrous bundles in the inner bark (phloem or bast) of stems of dicotyledenous plants, leaf fibres which run lengthwise through the leaves of monocotyledenous plants and fibres of seeds and fruits. Flax, hemp, jute, ramie, sisal and coir are mainly used for technical purposes. Re‐ cently, the interest for renewable resources for fibres particularly of plant origin is increas‐ ing. Therefore several non-traditional plants are being studied with the aim to isolate fibres

> © 2013 Smole et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

© 2013 Smole et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

distribution, and reproduction in any medium, provided the original work is properly cited.

M. Sfiligoj Smole, S. Hribernik, K. Stana Kleinschek and T. Kreže

http://dx.doi.org/10.5772/52372

**1. Introduction**

from plant leaves or stems.

Additional information is available at the end of the chapter
