Analysis of food components

Otles, S., Ed., Methods of Analysis of Food Components and Additives, CRC Press, Boca Raton, FL, 2005. 

Capillary supercritical fluid chromatography has been demonstrated as a viable alternative for the analysis of food components which are sensitive to temperature such as flavors and fragrances. Supercritical fluids have long been recognized for their unique solvating characteristics. One of the most common uses of supercritical fluids is for the extraction of components of interest from natural materials (i.e. caffeine from coffee or oil from soybeans). Early in its development supercritical fluid chromatography (SPC) was used for the analysis of natural materials such as flavors and other food components because the technique is well suited for the analysis of compounds which thermally degrade. In this paper, the use of capillary SFC for the analysis of food components is discussed. Examples of the capillary SFC analysis of fats and flavors as well as food contaminants such as pesticides are presented. 

Applications of CE techniques to food analysis is rapidly increasing and recent progresses have been reviewed [61,62]—a detailed discussion of this topic can be found in Chapter 30 by Vargas and Cordoba. The analysis of food components or nutrients does not require high sensitivity but does... 

Ruiter, A. and A. A. Bergwerff. 2005. Analysis of chemical preservatives in food. In Methods of Analysis of Food Components and Additives, ed. S. Otles, Chapter 14. Boca Raton, FL CRC Press, pp. 379-402. 

Spectroscopy was the early technique and tool of choice in food analysis. Specifically, near-infiaied (NIR) spectroscopy was used with many applications for the rapid analysis of foods. NIR was used in the systematic analysis of food components such as moisture, protein, and fat, and also sugars and organic acids. The advantages of this technique were its simplicity and versatility. It is still used along with other spectroscopic techniques such as Fourier transform infrared (FTIR) and nuclear magnetic resonance (NMR) spectroscopies. 

Often, planar chromatography is used as a preparative step for the isolation of single components or classes of components for further chromatographic separation or spectroscopic elucidation. Many planar chromatographic methods have been developed for the analysis of food products, bioactive compounds from plant materials, and essential oils. 

On-line SFE-pSFC-FTIR was used to identify extractable components (additives and monomers) from a variety of nylons [392]. SFE-SFC-FID with 100% C02 and methanol-modified scC02 were used to quantitate the amount of residual caprolactam in a PA6/PA6.6 copolymer. Similarly, the more permeable PS showed various additives (Irganox 1076, phosphite AO, stearic acid - ex Zn-stearate - and mineral oil as a melt flow controller) and low-MW linear and cyclic oligomers in relatively mild SCF extraction conditions [392]. Also, antioxidants in PE have been analysed by means of coupling of SFE-SFC with IR detection [121]. Yang [393] has described SFE-SFC-FTIR for the analysis of polar compounds deposited on polymeric matrices, whereas Ikushima et al. [394] monitored the extraction of higher fatty acid esters. Despite the expectations, SFE-SFC-FTIR hyphenation in on-line additive analysis of polymers has not found widespread industrial use. While applications of SFC-FTIR and SFC-MS to the analysis of additives in polymeric matrices are not abundant, these techniques find wide application in the analysis of food and natural product components [395]. 

The most basic method for the determination of the methylxanthines is ultraviolet (UV) spectroscopy. In fact, many of the HPLC detectors that will be mentioned use spectroscopic methods of detection. The sample must be totally dissolved and particle-free prior to final analysis. Samples containing more than one component can necessitate the use of extensive clean-up procedures, ajudicious choice of wavelength, the use of derivative spectroscopy, or some other mathematical manipulation to arrive at a final analytical measurement. A recent book by Wilson has a chapter on the analysis of foods using UV spectroscopy and can be used as a suitable reference for those interested in learning more about this topic.1... 

A number of criteria could be apphed to organize this chapter, depending on the point of view by which foods are considered. In this chapter, application of HPLC to food analysis will be described considering homogeneous classes of food components lipids, carbohydrates and related substances, proteins, peptides, amino acids, biogenic amines, phenolics, vitamins, and some selected contaminants. 

HPLC analysis of food proteins and peptides can be performed for different purposes to characterize food, to detect frauds, to assess the severity of thermal treatments, etc. To detect and/or quantify protein and peptide components in foods, a number of different analytical techniques (chromatography, electrophoresis, mass spectrometry, immunology) have been used, either alone or in combination. The main advantages of HPLC analysis lie in its high resolution power and versatility. In a single chromatographic run, it is possible to obtain both the composition and the amount of the protein fraction and analysis can be automated. 

Detection of peptides in HPLC can be achieved by measuring natural absorbance of peptide bonds at 200-220 nm. Unfortunately at these wavelengths a lot of food components and also the solvents used for analysis absorb, demanding an intensive sample pretreatment and clean-up [129]. Peptides with aromatic residues can be detected at 254 nm (phenylalanine, tyrosine, and tryptophan) or 280 nm (tyrosine and tryptophan). Taking advantage of the natural fluorescence shown by some amino acids (tyrosine and tryptophan), detection by fluorescence can also be used for peptides containing these amino acids [106]. 

The name carbohydrate dates back to a time when it was thought that all of these molecules were hydrates of carbon. For example the molecular formula for glucose is C6H1206, or six carbons plus six water molecules (H20). While these molecules make up the largest component of most foods, especially when calculated on a dry basis, their analysis was often avoided. For example, proximate analysis of food frequently involved analysis for moisture, fat, ash, and protein with the remaining portion considered carbohydrate of one form or another. 

Fluorescence microspectrophotometry typically provides chemical information in three modes spectral characterization, constituent mapping in specimens, and kinetic measurements of enzyme systems or photobleaching. All three approaches assist in defining chemical composition and properties in situ and one or all may be incorporated into modem instruments. Software control of monochrometers allows precise analysis of absoiption and/or fluorescence emission characteristics in foods, and routine detailed spectral analysis of large numbers of food elements (e.g., cells, fibers, fat droplets, protein bodies, crystals, etc.) is accomplished easily. The limit to the number of applications is really only that which is imposed by the imagination - there are quite incredible numbers of reagents which are capable of selective fluorescence tagging of food components, and their application is as diverse as the variety of problems in the research laboratory. 

Why use MS/MS analysis of volatile components frcm food and flavor components Figure 1 provides the answer. Hie top trace is the capillary column gas chromatographic profile of the concentrated volatiles fran a knockwurst sausage sanple. The tenperature program of 55 C to 180 C at 5° per minute establishes the time scale frcm beginning to end of run as 25 minutes. Coupled to a mass spectrometer for identification, each of the many conpounds can be examined by the mass spectrometer for only a few seconds. 

Fretz, C., Kanel, S., Luisier, J. L., Amado, R. (2005). Analysis of volatile components of Petite Arvine wine. Fur. Food Res. Technol., 221, 3. ... 

Chemometrics is a branch of science and technology dealing with the extraction of useful information from multidimensional measurement data using statistics and mathematics. It is applied in numerous scientific disciplines, including the analysis of food [313-315]. The most common techniques applied to multidimensional analysis include principal components analysis (PCA), factor analysis (FA), linear discriminant analysis (LDA), canonical discriminant function analysis (DA), cluster analysis (CA) and artificial neurone networks (ANN). 

Changes in the focus of SFE can be easily followed through its reported applications. Thus, in 1993 [3], environmental applications prevailed (45.9% versus 21.9% devoted to foods and 11.6% to industrial analyses). By 1996, however, SFE applications to food analysis had risen to 38%, environmental uses fallen to 41% and industrial analyses levelled off at 11% [48]. More recently [17], the extraction of food components (particularly fat) has become one of the major applications of SFE, so much so that the current boom in SF extractor sales has been ascribed to it. The book by Luque de Castro et al. [3] contains comprehensive tables of SFE applications in various fields. Also, one review of SFE in food analysis [148] includes four tables with applications involving the extraction of fat from various types of sample (viz. meat and animal products, fish, cereal, seed and animal feed, plants and vegetables). On a more specific level, Eller and King reviewed determinations of the fat content in foods [149]. Finally, the Analytical Chemistry issues devoted to reviewing techniques provide periodic updates on SFE and SFC [150]. 

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