doi: 10.1111/j.1471-0307.2011.00711.x
ORIGINAL RESEARCH
An assessment of Fourier Transform Infrared spectroscopy to identify adulterated raw milk in Brazil LAERTE D CASSOLI,* BEATRIZ SARTORI, ALINE ZAMPAR and PAULO F MACHADO Department of Animal Science, University of Sao Paulo, ESALQ, PO Box 9, Piracicaba, Sao Paulo, Brazil
The aim of this study was to evaluate the application of the methodology of Fourier Transform Infrared spectroscopy (FT-IR) to the identification of adulterated raw milk. A reference spectrum with 800 representative samples of the study area was built. Through the analysis of principal components, equations with a distinct number of factors were developed. For the validation test, 100 adulterated samples were used at three different concentrations of sodium bicarbonate, sodium citrate and non-acid cheese whey. Results indicate that the FT-IR can be used for the identification of adulterated milk with 0,05% and 0,075% of sodium bicarbonate and citrated respectively. Keywords Adulterated raw milk, Fourier Transform Infrared, Sodium Bicarbonate, Sodium Citrate, Non-acid cheese whey, Principal component analysis.
INTRODUCTION
point of milk, which is directly correlated with the concentration of solutes (IDF 2002). Solutes such as sugar and salt then began to be used to restore the freezing point: this was countered by developing methods that would identify the presence of sugar, salts and other compounds added for such a purpose (Pereira et al. 2001; Veloso et al. 2002). More recently adulteration in milk has become more sophisticated, and other materials began to be added with different purposes (Xin and Stone 2008). In 2008, melamine was detected in milk in China, its use being to increase apparent protein content, and thereby raising the value of milk, with severe adverse effects to health of those who consumed the milk (Xin and Stone 2008; Tunick 2009). Soon after the discovery of such tampering, a new analytical method was developed and incorporated to measure the concentration of melamine, which is now being adopted by some industries in the quality control process of their raw materials (Bradley 2008; Garber 2008). The introduction of each new adulterant requires an analytical method to be developed and incorporated into the quality control programme of the industry. These methods, which generally have low analytical performance, require the use of reagents and show high dependence on labour force (Harding 1995; Ashurst and Dennis 1998).
! 2011 Society of Dairy Technology
Food adulteration is an ancient practice that concerns not only consumers but also producers and processing plants. This topic has been gaining attention, and therefore, there is growing demand for methods to detect adulteration and ensure the authenticity of products (Karoui and Baerdemaeker 2007). Adulteration has been reported in the milk chain production since the 19th century: in 1859, the American state of Massachusetts was among the first in the country to pass a law prohibiting milk adulteration. At that time, the addition of water and other compounds such as formaldehyde, starch and acidity neutralisers to milk was a common practice (Anonymous, 1916). In 1906, the first federal law to deal with safe food production was passed and the first quality parameters began to be monitored (Tunick 2009). Following the regulation of milk production and the definition of quality parameters, the development of quantitative and qualitative analytical methods was one of the pillars to the process of searching for safe dairy products. The earliest adulterations in milk, reported in the literature, concerned adding water to increase volume and skimming for cream production (Anonymous 1882, 1890; Sommerfeld 1901). The addition of water was controlled by determining the freezing
480
Vol 64, No 4 November 2011 International Journal of Dairy Technology
*Author for correspondence. Email:
[email protected]
Vol 64, No 4 November 2011
An alternative physical method is the use of the Fourier transform infrared spectroscopy (FT-IR), based on the emission of electromagnetic energy that interacts with a matrix that absorbs some of this energy, thus generating the absorption spectrum (Mendenhall and Brown 1991; Gunasekaran and Irudayaraj 2000; Karoui and Baerdemaeker 2007). The spectrum generated is a feature of the matrix and can undergo slight variations depending on the chemical composition. In adulterating the matrix with a given compound, the generated spectrum can be significantly different from the reference spectrum, which reflects the presence of an adulterant. To date, studies indicate that there is high potential for the application of the FT-IR methodology to monitor milk adulteration (Luo et al. 2006). The development of reference spectra for milk could anticipate the discovery of a new adulterant. Furthermore, this methodology is widely used in automated equipment to determine milk composition, providing high analytical capacity and low operational cost (Sa´nchez et al. 2007). Other studies report the potential of FT-IR to identify adulterants in milk products. Chen et al. (2008), using methodology of infrared coupled with discriminant analysis, developed a calibration able to differentiate adulterated milk in milk already reconstituted at concentrations of 0.55% of adulterant. Similarly, Mauer et al. (2009) found that melamine can be identified from the concentration of 1 ppm for infant formula using the infrared method. The application of FT-IR to monitor raw milk quality was reported by Luo et al. (2006), who developed a reference spectrum for nonadulterated milk. To validate the model, they used samples adulterated with urea, vegetable oil and hydrolysed protein. All the adulterated samples were identified as such, and the authors also report a detection limit of 0.02% for these adulterants. In a similar study carried out by He et al. (2010), using FT-IR, raw milk samples adulterated with melamine, glucose and urea and contaminated with tetracycline were also successfully identified. A similar study using FT-IR for the identification of whey in powdered milk showed that the method allowed the identification of the contaminant at concentrations above 5% (Mendenhall and Brown 1991), despite the similarity between the matrix and milk whey. Studies show that to identify components at low concentrations, it is required to use a larger number of factors in the model. Hansen (1998) studied the determination of milk urea nitrogen and he developed models with 20 factors. He also found a high number of factors were required for the determination of free fatty acids, with 16 factors being necessary for better prediction response (Hansen et al. 1999). Chen et al. (2008), seeking to develop calibration to individuate natural milk from adulterated milk with reconstituted milk, observed that a model with 19 factors was the most effective. Therefore, the objective of this research was to develop a calibration to identify adulterated raw milk by comparing it the reference spectrum, in automated equipment with technology of FT-IR. Milk samples were adulterated with each of three ! 2011 Society of Dairy Technology
different compounds, commonly used in adulterating raw milk: sodium bicarbonate (SB), sodium citrate (SC) and nonacid cheese whey (W) (Cerda´n et al. 1992; Veloso et al. 2002). MATERIAL AND METHODS Source of milk samples The building of the reference spectrum requires samples that represent the variability in milk composition (Soyeurt et al. 2009). Factors affecting this variability (geographical location, time of year and animal breed) were considered when collecting the samples. To comply with standard procedures (IDF 1995), samples from 800 farms located in three Brazilian states, Sa˜o Paulo, Minas Gerais and Bahia, were collected between August 2009 and March 2010. Fifty millilitres of milk samples, from each farm bulk tank, was collected in a flask containing, and the preservative bronopol was added. The samples were kept under refrigeration (
