Discrimination and classification of adulterants in maple syrup with the use of infrared spectroscopic techniques

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1 Journal of the Science of Food and Agriculture J Sci Food Agric 83: (online: 2003) DOI: /jsfa.1332 Discrimination and classification of adulterants in maple syrup with the use of infrared spectroscopic techniques MM Paradkar, S Sivakesava and J Irudayaraj* Department of Agriculture and Biological Engineering, The Pennsylvania State University, 249, Agricultural Engineering Building, University Park, PA 16802, USA Abstract: Food adulteration is a profit-making business for some unscrupulous manufacturers. Maple syrup is a soft target of adulterators owing to its simplicity of chemical composition. In this study the use of Fourier transform infrared (FTIR) spectroscopy and near-infrared (NIR) spectroscopy to detect adulterants such as cane and beet invert syrups as well as cane and beet sugar solutions in maple syrup was investigated. The FTIR spectrum of adulterated samples was characterised and the regions cm 1 (carbohydrates) and and cm 1 (carbohydrates, carboxylic acids and amino acids) were used for detection. The region between 1100 and 1660nm in the NIR spectrum was used for analysis. Linear discriminant analysis (LDA) and canonical variate analysis (CVA) were used for discriminant analysis, while partial least squares (PLS) and principal component regression (PCR) were used for quantitative analysis. FTIR was more accurate in predicting adulteration using two different regions (R 2 >0.93 and >0.98) compared with NIR (R 2 >0.93). Classification and quantification of adulterants in maple syrup show that NIR and FTIR can be used for detecting adulterants such as pure beet and cane sugar solutions, but FTIR was superior to NIR in detecting invert syrups. # 2003 Society of Chemical Industry Keywords: spectroscopy; adulteration; maple syrup; sugars; chemometrics INTRODUCTION Maple syrup is a natural product obtained from the xylem sap of the sugar maple (Acer saccharum). Tapped during the end of the winter season in Canada and many other parts of North America, this sap contains around 2% solids. It may be concentrated through evaporation of water, leaving behind a syrup rich in sugars. Although a wide variability can exist in the sap content of individual trees, around 35 l of sap is required to produce 1 l of pure syrup. 1 The sugars, mostly sucrose, together with various trace elements and organic acids 2 4 and various phenolics, furfurals, 5 flavour components 6 and chromophores, some of which are formed during the concentration process, 7,8 constitute maple syrup. The chemical composition of 80 different types of pure maple syrup samples produced in North America has been investigated by Stuckel and Low. 9 Of the various constituents, sucrose is the most prevalent sugar, accounting for % of the dry matter of the sap, while amino acids, organic acids, phenolic compounds, hormones, minerals, salts and other compounds constitute the remaining 2% or less. 10 In maple syrup, sucrose constitutes %, glucose % and fructose %, while organic acids such as malic and fumaric acids constitute and % respectively. 9 Sucrose, the major component of maple syrup, can also be obtained from other, much less expensive sources such as corn, beet and cane. Hence maple syrup can be adulterated with comparatively cheaper cane, corn 11 and beet 1 sugars/ syrups for economic gain. Adulteration of maple sap and syrup with sugars from other plants violates state and federal laws and defrauds consumers. Detection of adulteration is possible even though maple syrup naturally varies in sugar concentration from batch to batch. Maple syrups adulterated with beet and cane invert syrups can be detected on the basis of altered reducing sugar content. However, it is difficult to detect the presence of pure beet and cane sugar (sucrose) contents in maple syrup, because sucrose is the only predominant sugar in maple syrup. Carro et al 12 used stable carbon isotope ratios to detect adulteration in maple syrup. Morselli and Baggett 13 and Whalen 14 developed an approved procedure for the detection of adulteration of maple syrup with 20% or more corn or cane sugars/syrups using carbon isotope analysis. Stuckel and Low 15 investigated maple syrup authenticity by high-perfor- * Correspondence to: J Irudayaraj, Department of Agricultural and Biological Engineering, The Pennsylvania State University, 249, Agricultural Engineering Building, University Park, PA 16802, USA josephi@psu.edu (Received 19 January 2002; revised version received 9 July 2002; accepted 5 September 2002) # 2003 Society of Chemical Industry. J Sci Food Agric /2003/$

2 Maple syrup adulteration mance anion exchange liquid chromatography with pulsed amperometric detection (HPAE-PAD) based on oligosaccharide fingerprinting. Martin et al 1 studied maple syrup adulteration in detail using 2 H SNIF-NMR (site-specific nuclear isotope fragmentation as measured by nuclear magnetic resonance) and 13 C SIRA-MS (stable isotope ratio analysis) techniques based on ethanol fermented from sugars. Maple syrup, apple, citrus fruits and beet lie in the same group of C3 plants, whereas plants such as corn and cane fall in the category of C4 plants. Plants in these two photosynthetic groups differ in 13 C/ 12 C ratios. 13 C SIRA-MS can differentiate between C3 and C4 plants and hence can detect the presence of cane and corn sugars in maple syrup, whereas SNIF- NMR permits discrimination of botanical origin within a pathway, ie it can detect the presence of beet sugars in maple syrup. However, both these techniques need sample preparation and require the conversion of sugars to ethanol, making these methods time-consuming and expensive. Infrared spectroscopy such as near-infrared (NIR) and mid-infrared (MIR) has been used for exploring the authenticity of many foods. 16,17 Past applications include establishing the authenticity of foods such as vegetable oils, 18 olive oil, coffee, 23 honey, 24,25 raspberry purées, 26 orange juice 27 and meat Attempts were also made to determine the presence and quantity of sugars in aqueous mixtures 31 and in plant cell culture media 32 using Fourier transform infrared attenuated total reflectance (FTIR-ATR). Infrared spectroscopic methods are simple, costeffective, rapid and non-destructive and could serve as a potential tool for detecting economic adulteration or for routine analysis if proper calibration and validation procedures with data acquisition protocols are established. Multivariate analysis is often used in spectroscopy to extract information from complex spectra containing overlapping absorption peaks, interference effects and instrumental artefacts from the data collected. The most commonly used multivariate calibration methods are partial least squares (PLS) and principal component regression (PCR). Both these methods are based on data compression and inverse calibration, 33 where possible to calibrate for the desired component while implicitly modelling the other source of variation. Discriminant analysis is another multivariate procedure commonly used for the classification of objects into groups or clusters based on a statistical measure. The success of these methods depend upon the choice of proper spectral range and the number of variables employed in the calibration model. The objective of this study was to apply infrared spectroscopic methods for detection of maple syrup adulteration. The specific goals were to (1) investigate FTIR and NIR spectroscopic methods to quantitatively estimate the levels of adulterants in maple syrup and (2) demonstrate the potential of spectroscopy in detecting the presence and type of adulteration (due to beet and cane sugars and their inverts) in maple syrup. MATERIALS AND METHODS Samples Pure Canadian maple syrup (Foodhold USA Inc, Atlanta, GA, USA) was adulterated with various quantities of medium-invert beet and cane syrups and with 60% solutions of beet and cane sugars (60% solution was chosen in order to avoid supersaturation of sugar in water and also to match with the sucrose content of maple syrup which is approximately 60%). Liquid beet and cane invert sugar samples were obtained from the Imperial sugar company (Sugar Land, TX, USA). All additions are expressed in percentage by weight of maple syrup. Each adulterated sample set included 54 samples in the range between 0 and 270g kg 1 in steps of 5g kg 1. The ranges were chosen to evaluate the adequacy of the method for maple syrup adulteration studies. Forty-one of these were used for calibration; the remainder were used for validation. Samples were mixed well and kept at room temperature to equilibrate before FTIR and NIR measurements. FTIR analysis A Bio-Rad FTS 6000 (Cambridge, MA, USA) spectrometer equipped with a deuterated triglycine sulphate detector was used for FTIR analysis. The sampling station was equipped with an overhead ATR accessory (Horizontal Attenuated Total Reflectance Accessory with multiple reflections, ie 10), comprising transfer optics within the chamber through which infrared radiation is directed to a detachable ATR zinc selenide crystal mounted in a shallow trough for sample containment. Distilled water was used for the background spectrum, and 256 co-added scans were taken at a resolution of 32cm 1. Single-beam spectra ( cm 1 ) of the samples were obtained, and corrected against the background spectrum of water, to present the spectra in absorbance units. The ATR crystal was carefully cleaned with water between measurements and dried using nitrogen gas after each experiment to ensure the best possible sample spectra. Spectra were collected in duplicate and used for multivariate analysis. NIR analysis Each sample (3.5ml) was poured and spread over a small polystyrene petri dish (60mm15mm) without bubbles. Five NIR scans (Perten model DA 7000, Perten Instruments, North America Inc, Reno, NV, USA) of the samples were taken using a fibre optic probe with a white background. A blank reading was measured using an empty petri dish to avoid interference in the sample reading. Spectra were collected and used for multivariate analysis. J Sci Food Agric 83: (online: 2003) 715

3 MM Paradkar, S Sivakesava, J Irudayaraj Chemometrics: multivariate analysis Multivariate analysis was used for quantitative and qualitative analysis. Partial least squares (PLS) and principal component regression (PCR) algorithms, proven to be effective in many quantitative applications, were used in the present study. Discriminant analysis was used to classify samples based on adulterant concentration level and to differentiate between the different types of adulterants in maple syrup. Quantitative analysis The Grams 32 (Galactic Industries Corporation, Salem, NH, USA) software package was used for quantitative analysis using PLS 34 and PCR 35 methods. Calibration models with original and firstderivative transformed spectra were developed and the optimum number of calibration factors was selected based on predicted residual sum of squares (PRESS), which should be minimised, along with the R 2 from regression. The predictability of the models was tested by computing the standard error of calibration (SEC) for the calibration data set and the standard error of prediction (SEP) for the validation data set: vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P n u ðactual predictedþ 2 ti¼1 SEC ¼ n f 1 vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P u n ðactual predictedþ 2 ti¼1 SEP ¼ n variates (wavenumbers) into a reduced new set of variates. Discriminant analysis is used here for two purposes: for classifying each adulteration into predetermined concentration groups as above and to test the ability of this method for differentiating between the types of adulterant. RESULTS AND DISCUSSION FTIR spectra In the analysis of aqueous solutions, overlap of the vibrational bands of water and solutes occurs, resulting in broad bands which usually cannot be deconvoluted into their constituents. This was overcome by using the spectrum of water as the background. Fig 1 presents the FTIR-ATR spectra of pure maple syrup, beet invert, cane invert and 60% beet and cane sugar solutions with the corresponding band assignments. The spectrum of maple syrup shows absorbance bands at 927, 991, 1042, 1110, 1259, 1327, 1419 and 2929cm 1. These bands are representative of the chemical or functional groups of components present in the sample. Assignment of functional groups corresponding to the vibrational modes was based on identification of the spectral peaks and matching the frequency with the corresponding chemical group that absorbs in the MIR region owing to fundamental vibration of the molecules. The region cm 1 Actual concentration refers to the cane mediuminvert sugar concentration added to the specific sample, predicted concentration refers to the value computed using spectral data, n is the number of samples in the calibration set and f is the number of factors used in the calibration model. Cross-validation was used in all cases to minimise the risk of overfitting the calibrations when evaluating model accuracy. Discriminant analysis The Win-DAS (Wiley, Chichester, UK) software package was used for discriminant analysis. Area normalisation of spectroscopic data was done to compensate for gross differences in spectral response caused by physical effects such as instrumental artefacts. Adulterated samples were classified into three groups (5 80, and g kg 1 respectively) based on the quantity of adulterant added to maple syrup. Two methods of discriminant analysis were used for the purpose of multiple group classification: linear discriminant analysis (LDA) and canonical variate analysis (CVA). Since multidimensional data (arising when the number of variates is larger than the number of observations) cannot be used directly in the above methods, PCA and PLS were employed for data compression to transform the data set comprising a large number of intercorrelated Figure 1. FTIR spectra of pure maple syrup and its adulterants. 716 J Sci Food Agric 83: (online: 2003)

4 Maple syrup adulteration corresponds to the absorption zones of the three major sugar constituents of maple syrup: fructose, glucose and sucrose. The cm 1 region is the anomeric region and is characteristic of the saccharide configuration. 36 The bands in the cm 1 region are assigned to C O and C C stretching modes, 37 and those around cm 1 are due to the bending modes of O C H, C C H and C O H angles. Negative bands were observed around 1618 and 3635cm 1. These bands are due to lower water concentration in the maple syrup compared with the reference employed, and the fact that water presents an O H stretch at these wavelengths. 38 The broad, strong NH þ 3 stretching band in the cm 1 region can be related to primary amino acids. 39 Table 1 shows the FTIR spectrum of pure maple syrup with the bonds and functional groups along with the corresponding modes of vibration. 39 The peak at 927cm 1 may be due to C H stretching of carbohydrates, whereas the peaks observed at 991, 1042, 1110 and 1259cm 1 may be due to C O bond stretching in the C OH group as well as C C stretching in the carbohydrate structure. In addition, the peak at 1110cm 1 may be due to stretching of the C O bond of the C O C linkage. The C O C bond is present here in sucrose as a glycosidic bond, a bond attaching monosaccharides such as glucose and fructose. The peak at 1327cm 1 may be due to O H bending of the C OH group, while that at 1419cm 1 may be due to a combination of O H bending of the C OH group and C H bending of alkenes (ie the structure of an organic acid such as fumaric acid has an HC=CH bond which may contribute to this peak). The peak at 2929cm 1 may be mainly due to C H stretching of carbohydrates, with minor contributions from O H stretching of carboxylic acids (in maple syrup, organic acids such as malic and fumaric acids and traces of various free amino acids may contribute to carboxylic acid) and NH þ 3 of free amino acids. Hence the region cm 1 can be characterised as the carbohy- Table 1. Functional groups and vibrational modes obtained from FTIR-ATR spectrum of pure maple syrup drate region, whereas the and cm 1 regions denote the organic and amino acids. Fig 1 shows the mid-ir (FTIR) spectra of maple syrup and the adulterants in the range cm 1. The absorption peak at 991cm 1 is more dominant than that at 1042cm 1 in the case of maple syrup, and is nearly equal in intensity to the peak at 1049cm 1 in the case of beet and cane sugar solutions. The peak at 991cm 1 is practically absent in invert syrups. Owing to the high degree of variation in the sucrose content of maple syrup, 9 the carbohydrate-absorbing region may not be sufficient for characterisation; hence the regions representing a combination of carbohydrates with organic and amino acids ( and cm 1 ) should be considered. The combination of both carbohydrate and carbohydrate/organic acid/amino acid regions can prove to be an excellent tool for characterisation. Stuckel and Low 9 have emphasised a matrix approach (where the number of chemical parameters is measured) to prove the authenticity of maple syrup. NIR spectra The NIR spectra ( nm) of pure maple syrup and its adulterants are shown in Fig 2. The cane and beet invert spectra overlap with each other, and so do the cane and beet sugar solution spectra. Maple syrup remains different from its adulterants in its absorption spectrum. Invert syrups contain glucose, fructose and sucrose and show strong absorption within a narrow spectral range ( nm), sugar (sucrose) solutions show a moderate range of intensity over a broad spectral range ( nm), whereas maple syrup shows a lower intensity of absorption over a moderate spectral range ( nm). All these spectra show absorption in the ranges and nm. The nm region denotes absorptions that may occur owing to the second overtone of C H stretching, while the nm region may be due to a combination of the first overtone of O H stretching in sugars (1450 nm), the first overtone of O H stretching in water ( nm) and the Wavenumber (cm 1 ) Vibrational bond and its functional group Mode of vibration 927 C H (carbohydrates) Bending 991 C O (C OH groups) Stretching 1042 C O (C OH groups) Stretching 1110 C O (C OH groups) Stretching C=O of ketones Stretching/bending C O (C O C bond) Stretching 1259 C O (C OH groups) Stretching 1327 O H (C OH groups) Bending 1419 O H (C OH groups) Bending C H (alkenes) Bending 2929 C H (carbohydrates) Stretching O H (carboxylic acids) Stretching NH þ 3 (free amino acids) Stretching Figure 2. NIR spectra ( nm) of pure maple syrup and its adulterants. J Sci Food Agric 83: (online: 2003) 717

5 MM Paradkar, S Sivakesava, J Irudayaraj Table 2. Quantitative analysis of maple syrup adulteration with different adulterants using FTIR and NIR spectroscopy with PLS/first derivative Calibration Validation Calibration method Factors R 2 SEC R 2 SEP FTIR region cm 1 Beet invert syrup Cane invert syrup Beet sugar solution Cane sugar solution FTIR regions and cm 1 Beet invert syrup Cane invert syrup Beet sugar solution Cane sugar solution NIR region nm Beet invert syrup Cane invert syrup Beet sugar solution Cane sugar solution third overtone of carbonyl groups (>C=O) ( nm). 40 Williams and Norris 41 reported that the third overtone of C=O stretching in unsaturated aldehydes and ketones gives peaks in the ranges and nm respectively; hence the region nm was chosen for model development. Classification using carbohydrate region ( cm 1 ) of FTIR spectra Quantitative analysis was conducted with maple syrup adulterated with beet invert, cane invert, beet sugar and cane sugar (Table 2). The calibration methods developed using PLS/first derivative gave the highest R 2 values of 0.983, 0.980, and (with four to seven factors) for quantitative estimation of beet invert syrup, cane invert syrup, beet sugar solution and cane sugar solution respectively. The respective SEC values were 1.582, 1.677, and 2.801, ie SEC values for beet and cane sugar solutions were higher than those for beet and cane invert syrups. R 2 and SEP values for validation samples are also given in Table 2. In discriminant analysis the PCA data compression method with CVA, denoted PCA/CVA, performed better than the other methods. Table 3 shows the calibration data obtained for different adulterants within the two regions of the FTIR spectra and the single region of the NIR spectra using the PCA/CVA method. For the carbohydrate region the per cent correct discrimination of calibration samples was found to be more than 95% for all adulterants of maple syrup with five to eight factors. The per cent correct classification (Table 3) for validated samples was in the range %. Classification using carbohydrate, organic acid and amino acid regions ( and cm 1 ) of FTIR spectra These regions represent carbohydrates as well as organic acids and amino acids in maple syrup. Maple syrup has been reported to contain organic acids such as malic, fumaric, succinic and citric acids, and free amino acids such as aspartic acid, asparagine and glutamine. 10 These organic and amino acids may be minor contributors to the carbohydrate peaks in the spectra. Quantitative analysis of the spectra in the combined region shows that the PLS/first derivative method (five to six factors) was better in this region. R 2 values greater than 0.98 were obtained for all adulterant prediction models. A validation analysis yielded R 2 values greater than 0.99 for all adulterant prediction models, with SEP values of 1.124, 1.071, and for maple syrup model blends with beet invert syrup, cane invert syrup, beet sugar solution and cane sugar solution respectively. Discriminant analysis of calibration data using PCA/CVA yielded a better result in this region (Table 3), Table 3. Discriminant analysis of maple syrup adulteration with different adulterants using PCA/CVA method Adulterant Factors % correct discrimination of calibration samples % correct discrimination of validation samples FTIR ( cm 1 ) Beet invert syrup Cane invert syrup Beet sugar solution Cane sugar solution FTIR ( and cm 1 ) Beet invert syrup Cane invert syrup Beet sugar solution Cane sugar solution NIR ( nm) Beet invert syrup Cane invert syrup Beet sugar solution Cane sugar solution J Sci Food Agric 83: (online: 2003)

6 Maple syrup adulteration demonstrating the potential of this region as a suitable marker to detect the experimental adulterants. NIR spectra in region nm The NIR spectra generally result in broad peaks, in contrast to the sharp peaks from the FTIR spectra. In quantitative analysis (Table 2) the PLS/first derivative calibration method yielded R 2 values of and with high SEC values of and for beet and cane inverts respectively, whereas R 2 values of and with SEC values of and were obtained for beet and cane sugar predictions respectively. Calibration results in this region indicate that the number of factors for invert syrups is quite high (10 12), while the number of factors for the pure sugar solution model was only three to six. This shows that the NIR method has the potential to detect the adulteration of maple syrup with pure sugar solutions to a greater extent than its adulteration with inverts. NIR was found to be better suited for quantitative analysis but not for classification or characterisation studies. Discriminant analysis of the calibration data set using PCA/CVA gave the best prediction among the methods with three to eight factors (Table 3). Classification of adulterants Data from individual calibration sets of the four different adulterants were merged and new calibrations were obtained to develop a single calibration model to determine the type of adulterant in maple syrup. The combined calibration data set comprises 200 samples and the validation data set consists of 72 samples. Figures 3 and 4 show the CVA plots for the classification of adulterants using the FTIR and NIR spectra respectively. Table 4 shows that data compression by PLS and discrimination by LDA using the spectra in the cm 1 region resulted in 100% correct classification of the calibration as well as the validation data set. However, when information in the Figure 3. Classification of adulterants by FTIR spectroscopy using PLS/CVA with 10 factors. Figure 4. Classification of adulterants by NIR spectroscopy using PLS/CVA with eight factors and cm 1 regions was used, the classification accuracy was about 96 and 100% respectively. In the case of NIR, PLS/LDA shows about 98% correct discrimination for both calibration and validation samples. The results indicate that the adulterants separate primarily into two groups, ie inverts and pure sugar solutions, as expected owing to the difference in composition (due to the presence of reducing sugars in inverts). Inverts contain a mixture of glucose, fructose and sucrose, whereas pure solutions contain mostly sucrose. Additionally, Stuckel and Low 15 reported that inversion leads to the production of oligosaccharides, which are not found in natural products. Hence the presence of these oligosaccharides may be another factor contributing to the differences between inverts and pure sugar solutions. In the case of FTIR, beet invert and cane invert sugars separate between themselves in a similar manner to beet sugar and cane sugar solutions (Fig 3). This may be due to minor compositional differences between the two sugars of different plant sources. Beet falls in the class of C3 plants whereas cane falls in the C4 plant category, with different 13 C/ 12 C ratios due to different photosynthetic pathways. Differences in deuterium/hydrogen (D/H) ratio, which is characteristic of the biological origin of each plant, may be a factor contributing to the differences observed in this classification. 1 IR spectroscopic measurements are all based on the vibrational energy of the molecules that constitute the sample. Naturally, absorption of energy will be different for different isotopes and could contribute to the classification of adulterants. NIR is efficient in differentiating invert syrups from pure sugar solutions as well as cane sugar solutions from beet sugar solutions, but it was not suitable for cane invert and beet invert classification, perhaps owing to large overlapping regions. This failure of NIR to classify inverts may be due to its inability to classify mixtures of glucose, fructose and sucrose simultaneously in maple syrup. The present study considered only one variety of maple syrup. For a comprehensive study, several varieties of maple syrup need to be investigated. J Sci Food Agric 83: (online: 2003) 719

7 MM Paradkar, S Sivakesava, J Irudayaraj Table 4. Classification of maple syrup adulterants Factors % correct discrimination of calibration samples % correct discrimination of validation samples FTIR ( cm 1 ) PCA data compression LDA CVA PLS data compression LDA CVA FTIR ( and cm 1 ) PCA data compression LDA CVA PLS data compression LDA CVA NIR ( nm) PCA data compression LDA CVA PLS data compression LDA CVA CONCLUSIONS FTIR spectroscopy and NIR spectroscopy were successfully used to detect the type and level of adulterants in maple syrup. Chemometric models developed using the FTIR and NIR methods yielded R 2 values greater than 0.9. NIR measurements are simple and more suitable for detecting adulterants such as pure beet and cane sugar solutions, while FTIR spectroscopy can be used to classify pure as well as invert sugar adulterants. Distinct regions such as the carbohydrate region and the organic and amino acid regions could be identified in the FTIR spectra and used as markers for detecting adulterants in maple syrup with a high degree of accuracy. REFERENCES 1 Martin GG, Martin YL, Naulet N and McManus HJD, Application of 2 H SNIF-NMR and 13 C SIRA-MS analyses to maple syrup: detection of added sugars. J Agric Food Chem 44: (1996). 2 Mollica JN and Morselli MF, Sugar and sugar products: gas chromatographic determination of non-volatile organic acids in sap of sugar. J Assoc Off Anal Chem 67: (1984). 3 Morselli MF and Whalen ML, Amino acid increase in xylem sap of Acer saccharum prior to bud break. Am J Bot 73: (1986). 4 Wassem M, Phipps J, Carbonneau R and Simmonds J, Plant growth substances in sugar maple (Acer saccharum Marsh) spring sap. Identification of cytokinins, abscisic acid and indolic compounds. J Plant Physiol 138: (1991). 5 Kermasha S, Goetghebeur M and Dumont J, Determination phenolic compound profiles in maple products by high performance liquid chromatography. J Agric Food Chem 43: (1995). 6 Filipic VJ, Underwood JC and Dooley CJ, Trace components of the flavor fraction of maple syrup. J Food Sci 34: (1969). 7 Underwood JC and Filipic VJ, Source of aromatic compounds in maple syrup flavor. J Food Sci 29: (1964). 8 Underwood JC, Effect of heat on the flavoring compounds of maple syrups. J Food Sci 36: (1971). 9 Stuckel JG and Low NH, The chemical composition of 80 pure maple syrup samples produced in North America. Food Res Int 29: (1996). 10 Koelling MR and Heiligmann RB, North American Maple Syrup Producers Manual. Appendix 2 Maple Chemistry and Quality Chemical Composition of Maple Sap. Bulletin 856, pp 1 2. [Online]. The Ohio State University Extension (1996). Available: b856_74.html [11 December 2000]. 11 Koelling MR and Heiligmann RB, North American Maple Syrup Producers Manual. Appendix 2 Maple Chemistry and Quality Adulteration. Bulletin 856, p 1. [Online]. The Ohio State University Extension (1996). Available: [11 December 2000]. 12 Carro O, Hillaire-Marcel C and Gagnon M, Detection of adulterated maple products by stable carbon isotope ratio. J Assoc Off Anal Chem 63: (1980). 13 Morselli MF and Baggett KL, Mass spectroscopic determination of cane sugar and corn syrup in maple syrup by use of 13 C/ 12 C ratio: collaborative study. J Assoc Off Anal Chem 67:22 24 (1984). 14 Whalen ML, Maple sap, maple syrup, and maple syrup products. J Assoc Off Anal Chem 72:89 91 (1989). 15 Stuckel JG and Low NH, Maple syrup authenticity analysis by anion-exchange liquid chromatographywith pulsed amperometric detection. J Agric Food Chem 43: (1995). 16 Downey G, Authentification of food and food ingredients by near infrared spectroscopy. J Near Infrared Spectrosc 4:47 61 (1996). 17 Wilson RH, Fourier transform mid-infrared spectroscopy for food analysis. Trends Anal Chem 9: (1990). 18 Lai YW, Kemsley EK and Wilson RH, Potential of Fourier transform infrared spectroscopy for the authentication of vegetable oils. J Agric Food Chem 42: (1994). 720 J Sci Food Agric 83: (online: 2003)

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