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Rapid detection of melamine adulteration in dairy milk by SB-ATR–Fourier transform infrared spectroscopy
Food Chemistry 141 (2013) 3066–3071
Contents lists available at SciVerse ScienceDirect
Food Chemistry journal homepage: www.elsevier.com/locate/foodchem
Analytical Methods
Rapid detection of melamine adulteration in dairy milk by SB-ATR–Fourier transform infrared spectroscopy Sana Jawaid, Farah N. Talpur ⇑, S.T.H. Sherazi, Shafi M. Nizamani, Abid A. Khaskheli National Center of Excellence in Analytical Chemistry, University of Sindh, Jamshoro 76080, Pakistan
a r t i c l e
i n f o
Article history: Received 11 July 2012 Received in revised form 18 March 2013 Accepted 22 May 2013 Available online 2 June 2013 Keywords: Melamine Dairy milk Adulteration SB-ATR–FTIR spectroscopy
a b s t r a c t Melamine is a nitrogenous chemical substance used principally as a starting material for the manufacture of synthetic resins. Due to its very high proportion of nitrogen melamine has been added illegitimately to foods and feeds to increase the measured protein content, which determines the value of the product. These issues prompted private as well as governmental laboratories to develop methods for the analysis of melamine in a wide variety of food products and ingredients. Owing to this fact present study is aimed to use single bounce attenuated total reflectance (SB-ATR) Fourier transform infrared spectroscopy (FTIR) method as an effective rapid tool for the detection and quantification of melamine in milk (liquid and powder). Partial least-squares (PLS) models were established for correlating spectral data to melamine concentration with R2 > 0.99, and RMSEC 0.370. Linear calibration curves were obtained over the calibration range of 25–0.0625%. The LOD and LOQ of the method was 0.00025% (2.5 ppm) and 0.0015% (15 ppm) respectively. Proposed SB-ATR–FTIR method requires little or no sample preparation with an assay time of 1–2 min. Ó 2013 Published by Elsevier Ltd.
1. Introduction Melamine (2,4,6-triamino-1,3,5-triazine) is an inexpensive synthetic molecule commonly used as an industrial chemical in the production of melamine formaldehyde resins for manufacturing laminates, plastics, coatings, commercial filters, adhesives, kitchenware, flame-retardants, fertiliser and other products (Sun et al., 2010). Melamine (MEL) is not approved as an ingredient in food, but some manufacturers illegally used it as an adulterant to increase the apparent protein content. In 2008, a large-scale MEL contamination incident was made public in China and many other countries (Yan, Zhou, Zhu, & Chen, 2009). It is found in a variety of food sources, including raw milk, ammonium bicarbonate, protein powder, and non-dairy creamer (NDC). These food sources had also been used in the production of processed foodstuffs, such as infant formula, milk-containing foods, biscuits, instant beverages, frozen yoghourt, candy, coffee drinks, cereal-based ingredient and soup products. A motivating force for the adulteration of a food product with MEL because of its high nitrogen level (66% by mass) increases the discernible protein content measured by standard protein analysis tests, such as Kjeldahl or Dumas that measure total nitrogen content as an indication of protein levels (Mauer, Chernyshova, Hiatt, Deering, & Davis, 2009). Safety limit for MEL ⇑ Corresponding author. Tel.: +92 222 772065; fax: +92 22 9213431. E-mail address: fi[email protected] (F.N. Talpur). URL: http://www.ceacsu.edu.pk (F.N. Talpur). 0308-8146/$ - see front matter Ó 2013 Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.foodchem.2013.05.106
level in milk and milk based products were set by both the US Food and Drug Administration (FDA) and the European Union at 2.5 mg/ kg (Vaclavik, Rosmus, Popping, & Hajslova, 2010). WHO/FAO experts stated that a limit of 1 mg/kg in infant formula would provide a sufficient margin of safety for dietary exposure relative to the tolerable daily intake (TDI) (Lutter et al., 2011). Ingestion of MEL at levels above the safety limit may cause kidney failure and even death, particularly for vulnerable individuals such as infants and young children (Ding, Yan, Ren, & Chen, 2010). Moreover reports have shown MEL toxicity resulted in kidney illness of varying degrees affecting about 300,000 babies, 6 of whom died (Elvira, Rodriguez, & Lynnworth, 2009). Various methods for the analysis of melamine and related compounds in foods for human consumption and animal feeds have been reported, including high-performance liquid chromatography (HPLC) or gas chromatography (GC) combined with a selective detection technique, such as tandem mass spectrometry (MS/ MS), single-stage mass spectrometry (MS), diode array detection (DAD) and ultraviolet absorption (UV) (Sun et al., 2010), enzymelinked immunosorbent assay (ELISA) (Yin et al., 2010), capillary electrophoresis (CE) (Chen & Yan, 2009), spectroscopic methods (Cheng et al., 2010), chemiluminescence (CL) (Wang, Chen, Gao, & Song, 2009), colorimetric nanoparticals (Ai, Liu, & Lu, 2009), nuclear magnetic resonance (NMR) spectroscopy (Lachenmeier et al., 2009), sweeping-micelles electro kinetic chromatography (SMEC) (Wu, Tsai, Sun, & Kuo, 2011) and molecularly imprinted polymer film (MIP) (Pietrzyk et al., 2009). However, the high cost of
S. Jawaid et al. / Food Chemistry 141 (2013) 3066–3071
operation and maintenance of GC/LC–MS systems as well as the labour intensive derivatization that GC–MS requires limits their use in the milk product factories (Venkatasami & Sowa, 2010). An HPLC method can be used to quantitatively analyse melamine at ppm level but it is inadequate for qualitative analysis and trace-level analysis (Yan et al., 2009). Currently, the FDA uses a liquid chromatography–triple-quadrupole tandem mass spectrometry (LC–MS/MS) method to detect residues of melamine in dry infant formula. Although this method provides limits of detection as low as 250 ppb, the sample preparation and cleanup procedures are time-consuming and labour-intensive. Therefore, the use of this method as a screening tool for a large number of samples is not practical or cost-effective. Regardless of the chromatographic approach used, sample pretreatment is relatively time-demanding: one or more extraction steps are required to decrease matrix interference and preconcentration is required to obtain an adequate detection level. Moreover, most of these procedures require large volumes of organic solvent, which might be harmful to the environment and human health (Chao, Lee, Wei, Kou, & Huang, 2011). Thus, there is still a need for a rapid, high-throughput, widely available, cost effective method for detecting melamine in infant formula and dairy milk. Rapid infrared spectroscopy methods have been successfully used in adulteration detection for a wide range of complex food products, including oils, carbohydrate powders, juices, honey, coffee, milk, vinegar, crab meat, and wheat (Ellis et al., 2012). Mauer et al. (2009) have reported MEL detection in infant formula powder using near and mid IR regions with PLS model, however no liquid milk samples were tested. Recently a method has been reported for MEL detection by mid and near-IR region in liquid and powder milk samples with glass cell accessory. In addition authors have also used expensive statistical approaches and special software complex for spectra computing and pretreatment of non-linear regressions models to achieve 1 ppm detection limit (Balabin & Smirnov, 2011). However FDA and European Union have established a threshold of 2.5 ppm. Therefore in present work we have used simple and more versatile single bounce attenuated total reflectance (SB-ATR) sample-handling accessory with PLS model, thereby reducing the cost of implementing FTIR melamine analysis. Furthermore, a ZnSe SB-ATR accessory provides access to much more spectral information than the transmission cell employed in commercial FTIR analyzers owing to its very short path length, as well as the much lower transmission cutoff of ZnSe compared to that of CaF2. On the basis of these considerations, the present study was carried out to evaluate the utility of SB-ATR–FTIR spectroscopy to quantify and detect melamine in raw and powder milk samples without using any toxic solvents, and having the advantage of low operational cost and green chemistry. 2. Materials and Methods 2.1. Reagent and samples Analytical grade melamine (purity 99%) was procured from Sigma–Aldrich (St. Louis, Missouri, USA). All other reagents were of high purity available. Raw milk sample from dairy farm was used as stock milk for dilution of standards. The raw milk samples were freeze dried through Labcon freeze dryer (Labcon corporation Kansas city, Missouri, USA). The safe temperature for drying of milk sample was 5 to 40 °C. 2.2. Analytical protocol for standard A stock powder was prepared by intermingles of a 1:1 w/w ratio of melamine and the powder/freeze dried milk sample. This mixture was further diluted to 25%, 22%, 18%, 14%, 11%, 8%, 5%, 2%,
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1%, 0.5%, 0.25%, 0.125%, and 0.0625% melamine by geometric mixing of equal mass ratios of freeze dried milk sample blend to a final mass of 2 g. The sample with the lowest concentration of melamine was prepared by diluting a 0.0625% w/w melamine stock powder to a melamine level of 0.00025% w/w (2.5 ppm). All samples were prepared in duplicate and stored in sealed glass vials at room temperature prior to analysis, and all dilutions were analysed on FTIRATR. 2.3. Sample preparation Five different brand milk samples (2 liquid and 3 in powder form) were purchased from local retails. The liquid milk samples were freeze dried with the addition of known amount (2.5– 15 lg mL1) of melamine. Also the powder milk samples were mixed with different proportion (2.5–25 lg g1) of melamine. 2.4. FTIR spectral measurements Spectra of samples in the mid-infrared region (4000–650 cm1) were collected using a Thermo Nicolet Avatar 330 FTIR spectrometer outfitted with a removable ZnSe crystal, deuterated triglycine sulfate (DTGS) detector controlled by OMNIC software (Thermo Nicolet Analytical Instruments, Madison, WI). The spectrum of all the standard or sample was proportion touching an open beam fresh background spectrum recorded from the bare ATR crystal; earlier to collection of each background spectrum, the ATR crystal was cautiously cleaned with hexane, methanol and acetone to remove any lingering involvement of the preceding sample, and remaining solvent was then evaporated using a brook of nitrogen gas. 2.5. FTIR calibrations/validation A series of 14 calibration standards covering the range of 0.0625–25% melamine was analysed by SB-ATR–FTIR instrumental method. This spectrum along with their respective reference melamine spectra was input into the TQ Analyst program to develop partial least squares (PLS) calibrations. Correlation and variance spectra were generated to identify spectral regions that contained information related to the grouped and ungrouped data and subsequently explored for calibration development and refinement. The performance of the calibrations was assessed by linear regression, and evaluated by running the samples of known melamine profile. To evaluate the competence of the models to fit the calibration data and to calculate the deviation of the models, root mean square error of calibration (RMSEC), root mean square error of cross validation (RMSECV) and root mean square error of prediction (RMSEP) were used. 2.6. Limit of detection and quantification The limit of detection and quantization was calculated as described previously (Saba Naz, Sherazi, Talpur, & Mahesar, 2011). Briefly the limit of detection (LOD), described as the minimum concentration from which it is possible to deduce the presence of the analyte with reasonable statistical certainty. To determine the limit of detection (LOD) and limit of quantification (LOQ) of proposed method, the selected band area was measured at low concentrations of standards, until the melamine related signal disappeared. The analysis at the lowest amount which produced substantial signal was repeated eleven times and calculated by the following formula:
LOD ¼ 3 SD C=M where SD is the standard deviation of the band area; C is the concentration of analyte and M is the mean band area.
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While LOQ was determined by the same way with following equation:
LOQ ¼ 10 SD C=M
3. Results and discussion Infrared Spectroscopy is an important tool for the analyst to provide detailed information about structure of organic compound with their specific finger print pattern. Fig. 1(a) depicts the ATRFTIR spectra of melamine, the 3000–3633 cm1 band is assigned to N–H stretching vibration modes, the 1100–1630 cm1 band corresponds to the stretching vibrations related to C–N, C@N, and is generally associated with the skeletal stretching vibrations of these aromatic rings. Furthermore the absorption band present at 1630 cm1 results from the stretching vibrations of >C–N– bonds present in the triazine ring of melamine (Zhao, Yu, Zhou, Tian, & Yanagisawa, 2005). The Fig. 1(b) shows the comparative spectra of raw milk and melamine + milk (1:1 w/w) in the region of 860– 660 cm1. The absorption at 806 cm1 is characteristic of out-ofplane bending modes of the triazine ring of melamine, this band was absent in raw milk. The 1300–910 cm1 region is considered to be the fingerprint region: absorption in this region includes contributions from complex interacting vibrations, giving rise to the generally unique fingerprint for each compound. The results were verified with statistical parameters and quantified through highly developed PLS calibration model to attain the best regression equation. FTIR spectral characteristics of different ratios of melamine at various concentrations were investigated, initially full region (4000–650 cm1) and then three different selective regions of the mid IR spectrum were used to construct PLS calibration. The region from 840.78 to 726.09 cm1 was selected due to the fact it offered improved regression result as compare to other regions. The maximum number of factors used in PLS models were automatically selected by TQ software for use in regression analysis. The factor selection was based on attaining minimum RMSEP predicted residual error of sum of squares (PRESS) values. The PRESS value indicates how well a model fits calibration data. Table 1 illustrates the parameters used for calibration model, which include the number of factors employed; R2, RMSEC,
RMSECV and the RMSEP obtained for MEL in PLS models of different selected region of mid IR. The best regression coefficient R2 0.99996 with minimal RMSEC 0.370 of the method was achieved in the region of 840.78–726.09 cm1 than other selective regions. Fig. 2 represents the spectra of 14 calibration standards prepared with root mean square error of calibration freeze dried milk with different concentration of melamine in the selected region of 860–760cm1. The spectra show the good linearity of the calibration model in proposed method. The LOD and LOQ were determined as 0.00025% and 0.0015% correspond to 2.5 and 15 ppm respectively. A threshold of 2.5 ppm for melamine in dairy milk has been set by the FDA.4 The present method was able to distinguish between unadulterated milk samples and that containing 2.5 ppm MEL, with no misclassifications. The proposed detection limit is more sensitive than some previously published methods that have LOD’s in the range 5–10 ppm, such as using HPLC for the determination of melamine in rice, corn flours (Ehling, Tefera, & Ho, 2007) and HPLC-DAD for plant origin powders (Ding et al., 2008).The assay time for melamine detection for proposed FTIR method is 2 min which is quite faster compared with most of the common methods. The current FDA LC–MS/MS method has a detection limit of 250 ppb in infant formula powder, but the total time to detection is >3 h (Turnipseed, Casey, Nochetto, & Heller, 2008). The obvious advantages revealed in the established ATR-FTIR method, such as easy sample preparation without solid phase extraction, short analysis time and low cost etc., could facilitate future development of rapid screening of melamine residues in food. For validation of the method, two standards from the calibration set were selected automatically and used as validation standards to cheque the accuracy of the models. Interestingly, it was observed that both PLS calibration models have a R2 in the range of 0.99893–0.99996 and were considered as an excellent regressions. The PLS model in which calibration was done without baseline showed very low RMSEC and RMSECV in comparison to the PLS model, in which calibration done with baseline, except the RMSEP for the former model was comparatively higher shown in Table 2. For that reason, the PLS model without baseline was selected as optimum for the determination of MEL in milk samples. The quantitative results and the recoveries of the method, which were determined by adding different amounts of MEL in
Fig. 1a. ATR-FTIR spectra of melamine standard.
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Fig. 1b. Comparative ATR-FTIR spectra of selected region of melamine standard, 1:1 melamine + milk and raw milk.
Table 1 Prediction ability of melamine in milk samples by ATR-FTIR. Spectral region cm1
Baseline type
Factors
R2
RMSEC
RMSECV
RMSEP
4000–650 1321–983.5 860.34–750.27 840.78–726.09
None None None None
1 1 1 7
0.98710 0.98335 0.98408 0.99996
5.00 5.68 5.55 0.370
6.897 7.448 7.486 5.751
4.10 8.01 4.50 1.55
raw and powder milk are listed in Table 3. It is shown that the average total recoveries of MEL ranged from 95.44% to 102.07%. In addition, no melamine was found within the LOD of proposed method in branded milk available locally, indicating that the proposed FTIR-ATR method has promising feasibility for rapid detection of melamine in milk.
4. Conclusions Here we have investigated accurate, reproducible and sensitive analytical method for the determination of melamine in dairy milk. The results indicated that SB-ATR FTIR and PLS calibration method could be applied for rapid and precise assessment of melamine
Fig. 2. Calibration spectrum of different dilution of milk containing melamine on SB-ATR–FTIR spectroscopy.
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S. Jawaid et al. / Food Chemistry 141 (2013) 3066–3071 Table 2 Prediction capabilities of PLS-FT-IR of the two measurement model for the determination of melamine. Spectral region (cm1)
840.78–726.09 (cm1)
840.78–726.09 (cm1)
Baseline Factors Validation standard R2 RMSEC RMSECV RMSEP
None 7 3 0.99996 0.370 5.75 1.55
Two points 840.78–726.09 (cm1) 4 4 0.99893 1.55 6.68 3.48
Table 3 Result of the determination of melamine in raw and powder milk. Original amount
Added (lg mL1 or g)a
– –
2.5 05
– –
10 15
– –
2.5 05
P2
– –
P3
– –
Milk sample Raw milk M1 M2
Powder milk P1
a
Found (lg mL1 or g1)
Recovery (%)
RSD %
2.39 5.10
95.44 102.00
2.14 1.62
10.12 15.31
101.20 102.07
2.69 2.76
2.44 5.01
97.60 100.24
2.63 3.44
10 15
10.12 15.22
101.20 101.47
3.14 1.31
20 25
20.01 25.14
100.06 100.56
2.26 2.00
lg mL1 for raw milk and lg g1 for powder milk sample.
present in dairy milk. Furthermore proposed method is very simple, environmental friendly and devoid of any sample pretreatment. For food labelling point of view the proposed method could be easily applied on dairy milk for fast analysis of melamine alternative technique to commonly used methods.
References Ai, K., Liu, Y., & Lu, L. (2009). Hydrogen-bonding recognition-induced color change of gold nanoparticles for visual detection of melamine in raw milk and infant formula. Journal of the American Chemical Society, 27, 9496–9497. Balabin, R. M., & Smirnov, S. V. (2011). Melamine detection by mid- and nearinfrared (MIR/NIR) spectroscopy: A quick and sensitive method for dairy products analysis including liquid milk, infant formula, and milk powder. Talanta, 1, 562–568. Chao, Y.-Y., Lee, C.-T., Wei, Y.-T., Kou, H.-S., & Huang, Y.-L. (2011). Using an on-line microdialysis/HPLC system for the simultaneous determination of melamine and cyanuric acid in non-dairy creamer. Analytica Chimica Acta, 1, 56–61. Chen, Z., & Yan, X. (2009). Simultaneous determination of melamine and 5hydroxymethylfurfural in milk by capillary electrophoresis with diode array detection. Journal of Agricultural and Food Chemistry, 19, 8742–8747. Cheng, Y., Dong, Y., Wu, J., Yang, X., Bai, H., Zheng, H., et al. (2010). Screening melamine adulterant in milk powder with laser Raman spectrometry. Journal of Food Composition and Analysis, 2, 199–202. Ding, T., Xu, J., Li, J., Shen, C., Wu, B., Chen, H., et al. (2008). Determination of melamine residue in plant origin protein powders using high performance liquid chromatography-diode array detection and high performance liquid chromatography–electrospray ionization tandem mass spectrometry. Chinese Journal of Chromatography, 6–9. Ding, N., Yan, N., Ren, C., & Chen, X. (2010). Colorimetric determination of melamine in dairy products by Fe3O4 magnetic nanoparticles–H2O2–ABTS detection system. Analytical Chemistry, 13, 5897–5899. Ehling, S., Tefera, S., & Ho, I. P. (2007). High-performance liquid chromatographic method for the simultaneous detection of the adulteration of cereal flours with melamine and related triazine by-products ammeline, ammelide, and cyanuric acid. Food Additives and Contaminants, 1319–1325. Ellis, D. I., Brewster, V. L., Dunn, W. B., Allwood, J. W., Golovanov, A. P., & Goodacre, R. (2012). Fingerprinting food: Current technologies for the detection of food adulteration and contamination. Chemical Society Reviews, 17, 5706–5727.
Elvira, L., Rodriguez, J., & Lynnworth, L. C. (2009). Sound speed and density characterization of milk adulterated with melamine. The Journal of the Acoustical Society of America, 5, EL177–EL182. Lachenmeier, D. W., Humpfer, E., Fang, F., Schutz, B., Dvortsak, P., Sproll, C., et al. (2009). NMR-Spectroscopy for nontargeted screening and simultaneous quantification of health-relevant compounds in foods: The example of melamine. Journal of Agricultural and Food Chemistry, 16, 7194–7199. Lutter, P., Savoy-Perroud, M.-C., Campos-Gimenez, E., Meyer, L., Goldmann, T., Bertholet, M.-C., et al. (2011). Screening and confirmatory methods for the determination of melamine in cow’s milk and milk-based powdered infant formula: Validation and proficiency-tests of ELISA, HPLC-UV, GC–MS and LC– MS/MS. Food Control, 6, 903–913. Mauer, L. J., Chernyshova, A. A., Hiatt, A., Deering, A., & Davis, R. (2009). Melamine detection in infant formula powder using near- and mid-infrared spectroscopy. Journal of Agricultural and Food Chemistry, 10, 3974–3980. Pietrzyk, A., Kutner, W., Chitta, R., Zandler, M. E., D’Souza, F., Sannicolo, F., et al. (2009). Melamine acoustic chemosensor based on molecularly imprinted polymer film. Analytical Chemistry, 24, 10061–10070. Saba Naz Sherazi, S. T. H., Talpur, Farah N., & Mahesar, Sarfaraz A. (2011). Rapid determination of free fatty acid content in waste deodorizer distillates using SBATR–FTIR. Journal of AOAC International. Sun, F., Ma, W., Xu, L., Zhu, Y., Liu, L., Peng, C., et al. (2010). Analytical methods and recent developments in the detection of melamine. Trends in Analytical Chemistry, 11, 1239–1249. Turnipseed, S., Casey, C., Nochetto, C., & Heller, D. N. (2008). Determination of melamine and cyanuric acid residues in infant formula using LC–MS/MS. United States Food and Drug Administration, 1–14. Vaclavik, L., Rosmus, J., Popping, B., & Hajslova, J. (2010). Rapid determination of melamine and cyanuric acid in milk powder using direct analysis in real timetime-of-flight mass spectrometry. Journal of Chromatography A, 25, 4204–4211. Venkatasami, G., & Sowa, J. R. Jr, (2010). A rapid, acetonitrile-free, HPLC method for determination of melamine in infant formula. Analytica Chimica Acta, 2, 227–230. Wang, Z., Chen, D., Gao, X., & Song, Z. (2009). Subpicogram determination of melamine in milk products using a luminol–myoglobin chemiluminescence system. Journal of Agricultural and Food Chemistry, 9, 3464–3469. Wu, W.-C., Tsai, I. L., Sun, S.-W., & Kuo, C.-H. (2011). Using sweeping-micellar electrokinetic chromatography to determine melamine in food. Food Chemistry, 3, 783–789. Yan, N., Zhou, L., Zhu, Z., & Chen, X. (2009). Determination of melamine in dairy products, fish feed, and fish by capillary zone electrophoresis with diode array detection. Journal of Agricultural and Food Chemistry, 3, 807–811.
S. Jawaid et al. / Food Chemistry 141 (2013) 3066–3071 Yin, W., Liu, J., Zhang, T., Li, W., Liu, W., Meng, M., et al. (2010). Preparation of monoclonal antibody for melamine and development of an indirect competitive ELISA for melamine detection in raw milk, milk powder, and animal feeds. Journal of Agricultural and Food Chemistry, 14, 8152–8157.
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Contents lists available at SciVerse ScienceDirect
Food Chemistry journal homepage: www.elsevier.com/locate/foodchem
Analytical Methods
Rapid detection of melamine adulteration in dairy milk by SB-ATR–Fourier transform infrared spectroscopy Sana Jawaid, Farah N. Talpur ⇑, S.T.H. Sherazi, Shafi M. Nizamani, Abid A. Khaskheli National Center of Excellence in Analytical Chemistry, University of Sindh, Jamshoro 76080, Pakistan
a r t i c l e
i n f o
Article history: Received 11 July 2012 Received in revised form 18 March 2013 Accepted 22 May 2013 Available online 2 June 2013 Keywords: Melamine Dairy milk Adulteration SB-ATR–FTIR spectroscopy
a b s t r a c t Melamine is a nitrogenous chemical substance used principally as a starting material for the manufacture of synthetic resins. Due to its very high proportion of nitrogen melamine has been added illegitimately to foods and feeds to increase the measured protein content, which determines the value of the product. These issues prompted private as well as governmental laboratories to develop methods for the analysis of melamine in a wide variety of food products and ingredients. Owing to this fact present study is aimed to use single bounce attenuated total reflectance (SB-ATR) Fourier transform infrared spectroscopy (FTIR) method as an effective rapid tool for the detection and quantification of melamine in milk (liquid and powder). Partial least-squares (PLS) models were established for correlating spectral data to melamine concentration with R2 > 0.99, and RMSEC 0.370. Linear calibration curves were obtained over the calibration range of 25–0.0625%. The LOD and LOQ of the method was 0.00025% (2.5 ppm) and 0.0015% (15 ppm) respectively. Proposed SB-ATR–FTIR method requires little or no sample preparation with an assay time of 1–2 min. Ó 2013 Published by Elsevier Ltd.
1. Introduction Melamine (2,4,6-triamino-1,3,5-triazine) is an inexpensive synthetic molecule commonly used as an industrial chemical in the production of melamine formaldehyde resins for manufacturing laminates, plastics, coatings, commercial filters, adhesives, kitchenware, flame-retardants, fertiliser and other products (Sun et al., 2010). Melamine (MEL) is not approved as an ingredient in food, but some manufacturers illegally used it as an adulterant to increase the apparent protein content. In 2008, a large-scale MEL contamination incident was made public in China and many other countries (Yan, Zhou, Zhu, & Chen, 2009). It is found in a variety of food sources, including raw milk, ammonium bicarbonate, protein powder, and non-dairy creamer (NDC). These food sources had also been used in the production of processed foodstuffs, such as infant formula, milk-containing foods, biscuits, instant beverages, frozen yoghourt, candy, coffee drinks, cereal-based ingredient and soup products. A motivating force for the adulteration of a food product with MEL because of its high nitrogen level (66% by mass) increases the discernible protein content measured by standard protein analysis tests, such as Kjeldahl or Dumas that measure total nitrogen content as an indication of protein levels (Mauer, Chernyshova, Hiatt, Deering, & Davis, 2009). Safety limit for MEL ⇑ Corresponding author. Tel.: +92 222 772065; fax: +92 22 9213431. E-mail address: fi[email protected] (F.N. Talpur). URL: http://www.ceacsu.edu.pk (F.N. Talpur). 0308-8146/$ - see front matter Ó 2013 Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.foodchem.2013.05.106
level in milk and milk based products were set by both the US Food and Drug Administration (FDA) and the European Union at 2.5 mg/ kg (Vaclavik, Rosmus, Popping, & Hajslova, 2010). WHO/FAO experts stated that a limit of 1 mg/kg in infant formula would provide a sufficient margin of safety for dietary exposure relative to the tolerable daily intake (TDI) (Lutter et al., 2011). Ingestion of MEL at levels above the safety limit may cause kidney failure and even death, particularly for vulnerable individuals such as infants and young children (Ding, Yan, Ren, & Chen, 2010). Moreover reports have shown MEL toxicity resulted in kidney illness of varying degrees affecting about 300,000 babies, 6 of whom died (Elvira, Rodriguez, & Lynnworth, 2009). Various methods for the analysis of melamine and related compounds in foods for human consumption and animal feeds have been reported, including high-performance liquid chromatography (HPLC) or gas chromatography (GC) combined with a selective detection technique, such as tandem mass spectrometry (MS/ MS), single-stage mass spectrometry (MS), diode array detection (DAD) and ultraviolet absorption (UV) (Sun et al., 2010), enzymelinked immunosorbent assay (ELISA) (Yin et al., 2010), capillary electrophoresis (CE) (Chen & Yan, 2009), spectroscopic methods (Cheng et al., 2010), chemiluminescence (CL) (Wang, Chen, Gao, & Song, 2009), colorimetric nanoparticals (Ai, Liu, & Lu, 2009), nuclear magnetic resonance (NMR) spectroscopy (Lachenmeier et al., 2009), sweeping-micelles electro kinetic chromatography (SMEC) (Wu, Tsai, Sun, & Kuo, 2011) and molecularly imprinted polymer film (MIP) (Pietrzyk et al., 2009). However, the high cost of
S. Jawaid et al. / Food Chemistry 141 (2013) 3066–3071
operation and maintenance of GC/LC–MS systems as well as the labour intensive derivatization that GC–MS requires limits their use in the milk product factories (Venkatasami & Sowa, 2010). An HPLC method can be used to quantitatively analyse melamine at ppm level but it is inadequate for qualitative analysis and trace-level analysis (Yan et al., 2009). Currently, the FDA uses a liquid chromatography–triple-quadrupole tandem mass spectrometry (LC–MS/MS) method to detect residues of melamine in dry infant formula. Although this method provides limits of detection as low as 250 ppb, the sample preparation and cleanup procedures are time-consuming and labour-intensive. Therefore, the use of this method as a screening tool for a large number of samples is not practical or cost-effective. Regardless of the chromatographic approach used, sample pretreatment is relatively time-demanding: one or more extraction steps are required to decrease matrix interference and preconcentration is required to obtain an adequate detection level. Moreover, most of these procedures require large volumes of organic solvent, which might be harmful to the environment and human health (Chao, Lee, Wei, Kou, & Huang, 2011). Thus, there is still a need for a rapid, high-throughput, widely available, cost effective method for detecting melamine in infant formula and dairy milk. Rapid infrared spectroscopy methods have been successfully used in adulteration detection for a wide range of complex food products, including oils, carbohydrate powders, juices, honey, coffee, milk, vinegar, crab meat, and wheat (Ellis et al., 2012). Mauer et al. (2009) have reported MEL detection in infant formula powder using near and mid IR regions with PLS model, however no liquid milk samples were tested. Recently a method has been reported for MEL detection by mid and near-IR region in liquid and powder milk samples with glass cell accessory. In addition authors have also used expensive statistical approaches and special software complex for spectra computing and pretreatment of non-linear regressions models to achieve 1 ppm detection limit (Balabin & Smirnov, 2011). However FDA and European Union have established a threshold of 2.5 ppm. Therefore in present work we have used simple and more versatile single bounce attenuated total reflectance (SB-ATR) sample-handling accessory with PLS model, thereby reducing the cost of implementing FTIR melamine analysis. Furthermore, a ZnSe SB-ATR accessory provides access to much more spectral information than the transmission cell employed in commercial FTIR analyzers owing to its very short path length, as well as the much lower transmission cutoff of ZnSe compared to that of CaF2. On the basis of these considerations, the present study was carried out to evaluate the utility of SB-ATR–FTIR spectroscopy to quantify and detect melamine in raw and powder milk samples without using any toxic solvents, and having the advantage of low operational cost and green chemistry. 2. Materials and Methods 2.1. Reagent and samples Analytical grade melamine (purity 99%) was procured from Sigma–Aldrich (St. Louis, Missouri, USA). All other reagents were of high purity available. Raw milk sample from dairy farm was used as stock milk for dilution of standards. The raw milk samples were freeze dried through Labcon freeze dryer (Labcon corporation Kansas city, Missouri, USA). The safe temperature for drying of milk sample was 5 to 40 °C. 2.2. Analytical protocol for standard A stock powder was prepared by intermingles of a 1:1 w/w ratio of melamine and the powder/freeze dried milk sample. This mixture was further diluted to 25%, 22%, 18%, 14%, 11%, 8%, 5%, 2%,
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1%, 0.5%, 0.25%, 0.125%, and 0.0625% melamine by geometric mixing of equal mass ratios of freeze dried milk sample blend to a final mass of 2 g. The sample with the lowest concentration of melamine was prepared by diluting a 0.0625% w/w melamine stock powder to a melamine level of 0.00025% w/w (2.5 ppm). All samples were prepared in duplicate and stored in sealed glass vials at room temperature prior to analysis, and all dilutions were analysed on FTIRATR. 2.3. Sample preparation Five different brand milk samples (2 liquid and 3 in powder form) were purchased from local retails. The liquid milk samples were freeze dried with the addition of known amount (2.5– 15 lg mL1) of melamine. Also the powder milk samples were mixed with different proportion (2.5–25 lg g1) of melamine. 2.4. FTIR spectral measurements Spectra of samples in the mid-infrared region (4000–650 cm1) were collected using a Thermo Nicolet Avatar 330 FTIR spectrometer outfitted with a removable ZnSe crystal, deuterated triglycine sulfate (DTGS) detector controlled by OMNIC software (Thermo Nicolet Analytical Instruments, Madison, WI). The spectrum of all the standard or sample was proportion touching an open beam fresh background spectrum recorded from the bare ATR crystal; earlier to collection of each background spectrum, the ATR crystal was cautiously cleaned with hexane, methanol and acetone to remove any lingering involvement of the preceding sample, and remaining solvent was then evaporated using a brook of nitrogen gas. 2.5. FTIR calibrations/validation A series of 14 calibration standards covering the range of 0.0625–25% melamine was analysed by SB-ATR–FTIR instrumental method. This spectrum along with their respective reference melamine spectra was input into the TQ Analyst program to develop partial least squares (PLS) calibrations. Correlation and variance spectra were generated to identify spectral regions that contained information related to the grouped and ungrouped data and subsequently explored for calibration development and refinement. The performance of the calibrations was assessed by linear regression, and evaluated by running the samples of known melamine profile. To evaluate the competence of the models to fit the calibration data and to calculate the deviation of the models, root mean square error of calibration (RMSEC), root mean square error of cross validation (RMSECV) and root mean square error of prediction (RMSEP) were used. 2.6. Limit of detection and quantification The limit of detection and quantization was calculated as described previously (Saba Naz, Sherazi, Talpur, & Mahesar, 2011). Briefly the limit of detection (LOD), described as the minimum concentration from which it is possible to deduce the presence of the analyte with reasonable statistical certainty. To determine the limit of detection (LOD) and limit of quantification (LOQ) of proposed method, the selected band area was measured at low concentrations of standards, until the melamine related signal disappeared. The analysis at the lowest amount which produced substantial signal was repeated eleven times and calculated by the following formula:
LOD ¼ 3 SD C=M where SD is the standard deviation of the band area; C is the concentration of analyte and M is the mean band area.
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While LOQ was determined by the same way with following equation:
LOQ ¼ 10 SD C=M
3. Results and discussion Infrared Spectroscopy is an important tool for the analyst to provide detailed information about structure of organic compound with their specific finger print pattern. Fig. 1(a) depicts the ATRFTIR spectra of melamine, the 3000–3633 cm1 band is assigned to N–H stretching vibration modes, the 1100–1630 cm1 band corresponds to the stretching vibrations related to C–N, C@N, and is generally associated with the skeletal stretching vibrations of these aromatic rings. Furthermore the absorption band present at 1630 cm1 results from the stretching vibrations of >C–N– bonds present in the triazine ring of melamine (Zhao, Yu, Zhou, Tian, & Yanagisawa, 2005). The Fig. 1(b) shows the comparative spectra of raw milk and melamine + milk (1:1 w/w) in the region of 860– 660 cm1. The absorption at 806 cm1 is characteristic of out-ofplane bending modes of the triazine ring of melamine, this band was absent in raw milk. The 1300–910 cm1 region is considered to be the fingerprint region: absorption in this region includes contributions from complex interacting vibrations, giving rise to the generally unique fingerprint for each compound. The results were verified with statistical parameters and quantified through highly developed PLS calibration model to attain the best regression equation. FTIR spectral characteristics of different ratios of melamine at various concentrations were investigated, initially full region (4000–650 cm1) and then three different selective regions of the mid IR spectrum were used to construct PLS calibration. The region from 840.78 to 726.09 cm1 was selected due to the fact it offered improved regression result as compare to other regions. The maximum number of factors used in PLS models were automatically selected by TQ software for use in regression analysis. The factor selection was based on attaining minimum RMSEP predicted residual error of sum of squares (PRESS) values. The PRESS value indicates how well a model fits calibration data. Table 1 illustrates the parameters used for calibration model, which include the number of factors employed; R2, RMSEC,
RMSECV and the RMSEP obtained for MEL in PLS models of different selected region of mid IR. The best regression coefficient R2 0.99996 with minimal RMSEC 0.370 of the method was achieved in the region of 840.78–726.09 cm1 than other selective regions. Fig. 2 represents the spectra of 14 calibration standards prepared with root mean square error of calibration freeze dried milk with different concentration of melamine in the selected region of 860–760cm1. The spectra show the good linearity of the calibration model in proposed method. The LOD and LOQ were determined as 0.00025% and 0.0015% correspond to 2.5 and 15 ppm respectively. A threshold of 2.5 ppm for melamine in dairy milk has been set by the FDA.4 The present method was able to distinguish between unadulterated milk samples and that containing 2.5 ppm MEL, with no misclassifications. The proposed detection limit is more sensitive than some previously published methods that have LOD’s in the range 5–10 ppm, such as using HPLC for the determination of melamine in rice, corn flours (Ehling, Tefera, & Ho, 2007) and HPLC-DAD for plant origin powders (Ding et al., 2008).The assay time for melamine detection for proposed FTIR method is 2 min which is quite faster compared with most of the common methods. The current FDA LC–MS/MS method has a detection limit of 250 ppb in infant formula powder, but the total time to detection is >3 h (Turnipseed, Casey, Nochetto, & Heller, 2008). The obvious advantages revealed in the established ATR-FTIR method, such as easy sample preparation without solid phase extraction, short analysis time and low cost etc., could facilitate future development of rapid screening of melamine residues in food. For validation of the method, two standards from the calibration set were selected automatically and used as validation standards to cheque the accuracy of the models. Interestingly, it was observed that both PLS calibration models have a R2 in the range of 0.99893–0.99996 and were considered as an excellent regressions. The PLS model in which calibration was done without baseline showed very low RMSEC and RMSECV in comparison to the PLS model, in which calibration done with baseline, except the RMSEP for the former model was comparatively higher shown in Table 2. For that reason, the PLS model without baseline was selected as optimum for the determination of MEL in milk samples. The quantitative results and the recoveries of the method, which were determined by adding different amounts of MEL in
Fig. 1a. ATR-FTIR spectra of melamine standard.
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Fig. 1b. Comparative ATR-FTIR spectra of selected region of melamine standard, 1:1 melamine + milk and raw milk.
Table 1 Prediction ability of melamine in milk samples by ATR-FTIR. Spectral region cm1
Baseline type
Factors
R2
RMSEC
RMSECV
RMSEP
4000–650 1321–983.5 860.34–750.27 840.78–726.09
None None None None
1 1 1 7
0.98710 0.98335 0.98408 0.99996
5.00 5.68 5.55 0.370
6.897 7.448 7.486 5.751
4.10 8.01 4.50 1.55
raw and powder milk are listed in Table 3. It is shown that the average total recoveries of MEL ranged from 95.44% to 102.07%. In addition, no melamine was found within the LOD of proposed method in branded milk available locally, indicating that the proposed FTIR-ATR method has promising feasibility for rapid detection of melamine in milk.
4. Conclusions Here we have investigated accurate, reproducible and sensitive analytical method for the determination of melamine in dairy milk. The results indicated that SB-ATR FTIR and PLS calibration method could be applied for rapid and precise assessment of melamine
Fig. 2. Calibration spectrum of different dilution of milk containing melamine on SB-ATR–FTIR spectroscopy.
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S. Jawaid et al. / Food Chemistry 141 (2013) 3066–3071 Table 2 Prediction capabilities of PLS-FT-IR of the two measurement model for the determination of melamine. Spectral region (cm1)
840.78–726.09 (cm1)
840.78–726.09 (cm1)
Baseline Factors Validation standard R2 RMSEC RMSECV RMSEP
None 7 3 0.99996 0.370 5.75 1.55
Two points 840.78–726.09 (cm1) 4 4 0.99893 1.55 6.68 3.48
Table 3 Result of the determination of melamine in raw and powder milk. Original amount
Added (lg mL1 or g)a
– –
2.5 05
– –
10 15
– –
2.5 05
P2
– –
P3
– –
Milk sample Raw milk M1 M2
Powder milk P1
a
Found (lg mL1 or g1)
Recovery (%)
RSD %
2.39 5.10
95.44 102.00
2.14 1.62
10.12 15.31
101.20 102.07
2.69 2.76
2.44 5.01
97.60 100.24
2.63 3.44
10 15
10.12 15.22
101.20 101.47
3.14 1.31
20 25
20.01 25.14
100.06 100.56
2.26 2.00
lg mL1 for raw milk and lg g1 for powder milk sample.
present in dairy milk. Furthermore proposed method is very simple, environmental friendly and devoid of any sample pretreatment. For food labelling point of view the proposed method could be easily applied on dairy milk for fast analysis of melamine alternative technique to commonly used methods.
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