infrared spectroscopy for food quality analysis and control || meat and meat products

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  • PART

    IIApplications

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  • Meat and Meat Products Rahul Reddy Gangidi and Andrew Proctor

    Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181Beef and beef products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Proximate composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Quality attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 Detection of adulteration and contamination . . . . . . . . . . . . . . . . . . . . . . 188 Beef adulteration with other meat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 Distinguishing fresh from frozen-then-thawed beef . . . . . . . . . . . . . . . . . . . 191 Microbial spoilage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191Pork and pork products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Proximate composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Quality attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194Chicken and chicken products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Proximate composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Quality attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Microbial spoilage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203Miscellaneous applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 Bone adulteration of meat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 Dimensions of the NIR fi ber-optic refl ectance probe . . . . . . . . . . . . . . . . . 203 FTIR-photoacoustic spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206

    Introduction

    Meat is a premium, high-demand food throughout the world. Meats have high-quality proteins, which contain essential amino acids, and are a very good source of vitamin B, dietary iron, and zinc. The meat-processing industry is one of the largest agricul-tural and food-processing industries in the world and infrared (IR) spectroscopy can play an important role in maintaining consistent product quality. For example, deter-mination of fat content is an important quality factor that can be measured quickly by Fourier transform infrared spectroscopy (FTIR). A typical fat measurement by a chemical extraction takes 34 h, and is laborious and off-line, involving toxic and

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    Infrared Spectroscopy for Food Quality Analysis and Control Copyright 2009, Elsevier Inc.ISBN: 978-0-12-374136-3 All rights reserved

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  • 182 Meat and Meat Products

    hazardous chemicals. With the use of rapid spectroscopic methods, the same results could be obtained in 25 minutes. In addition, other characteristics of the sample can be determined simultaneously. Although, IR spectroscopic methods are just one of many spectroscopic methods, IR-based methods are well accepted due to their versatility in predicting multiple attributes accurately and precisely in processing plants and laboratories.

    Infrared spectroscopy involves absorption of a certain wavelength of IR radiation by the specifi c chemical functional groups, based on their dipole moment. The advan-tages of using IR spectroscopy for meat and meat product quality and control are its simplicity (does not require sample preparation) and speed, it is non-destructive to the sample, and it is non-invasive. It can also be used as an online, at-line, and inline process analyzer with additional fi ber-optic capability, the cost of analysis is low per sample, it is non-ionizing, non-chemical reaction inducing, non-heating, and safe (low intensity of energy), and it does not require hazardous gas cylinders or toxic chemicals (i.e. it is green technology). Most IR instruments are bench top with some models being portable.

    IR refl ectance spectroscopy has the limitation that it is a surface analysis technique, with little depth penetration into the sample, it is affected by high moisture content, which absorbs IR radiation and by the surface free water, due to specular refl ectance from refl ective surfaces and high absorption. Although near-infrared (NIR) transmittance has better penetration, it is also affected by the higher depth, high moisture content, and less energy transmission due to refl ectance from partially transparent meat matrices.

    Near-infrared (0.72.5 m; 12 9004000 cm 1 ) spectroscopy is often coupled with visible spectroscopy (0.380.7 m) to measure the components and quality attributes of meat and meat products. It is further classifi ed into NIR refl ectance spectroscopy and NIR transmission spectroscopy. NIR can be non-dispersive (fi lter-based instru-mentation), dispersive and use Fourier transform-based instrumentation. Mid-infrared (MIR) (2.550 m; 4000200 cm 1 ) spectroscopy, on the other hand, is generally used with Fourier transformation, a complex mathematical technique converting time domain data into frequency domain, and refl ectance-based techniques, dif-fuse refl ectance and attenuated total refl ectance; and very rarely with dispersive and non-dispersive instrumentation. Most recent advanced instrumentation involves combining mid- and near-infrared spectroscopy (FTIR and FT-NIR). Fourier transform and dispersive, NIR and MIR spectroscopy often require the application of chemo-metrics (multivariate statistics) to extract the spectral information for qualitative and quantitative analysis. NIR and MIR spectroscopy is often complemented with visible spectroscopy, nuclear magnetic resonance spectroscopy, Raman spectroscopy and gas chromatography for specifi c applications.

    Far-infrared (2.550 m; 20010 cm 1 ) radiation is used for the processing and cooking of meat and food products and has very limited practical spectroscopic application.

    Infrared spectroscopy is utilized for proximate analysis of meat and meat products, mainly moisture, fat, and protein, and in some cases minerals. It has been used to deter-mine meat quality, pH, fatty acid profi le, appearance and color, muscle characteristics,

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  • such as water-holding capacity, intramuscular fat, tenderness, and microbial spoilage. In addition, it has been used to detect the adulteration of low-cost meat in premium meat, such as adulteration of beef with kangaroo and pork or skeletal muscle with organ meat, and to identify fresh meats from frozen-then thawed meats, adulteration with non-meat protein (e.g. from vegetable and dairy origin) and fecal contamina-tion. It has also been used to detect spinal cord, which is a central nervous system tissue and is prohibited in meat due to concerns about the transmission of bovine spongiform encephalopathy (BSE). Proximate and quality attributes of meats from other species have also been analyzed with IR spectroscopy.

    It is beyond the scope of this chapter to include all the meat-related applications of IR. However, an effort has been made to include the common applications and solutions to the problems. Most of the IR meat applications are tabulated for quick reference. Thermo Fisher Scientifi c Inc. is not responsible for the contents in this chapter. NIR refl ectance and NIR transmission spectroscopy instruments were from NIR Systems Inc. (Silver Springs, Maryland, USA), unless mentioned otherwise.

    Beef and beef products

    Proximate composition

    Norriss group demonstrated the applicability of NIR transmission spectroscopy to the measurement of the fat, protein, water content in emulsifi ed meats ( Ben-Gera and Norris, 1968 ). This work was further advanced by Kruggel et al. (1981) in emulsifi ed and ground meats; and by Lanza (1983) in ground and homogenized meats with NIR refl ectance spectroscopy. Moisture was predicted using multiple linear regression with 1732, 1700, 1990, and 1218 nm with an r 0.985 and standard error of prediction (SEP) of 0.48%. Similarly protein (1376, 1772, 1524, 1804 nm) was predicted with an r 0.899 and SEP of 0.53%, and fat content (1720, 1308, 2388, 1890 nm) was predicted with an r 0.998 and SEP of 0.23% ( Lanza, 1983 ). Since the moisture and fat content were predicted with a low error compared with the protein content, it would be advantageous to measure the protein from mois-ture and fat.

    Packaged beef Much of the meat in grocery stores is packaged with polyethylene and related mate-rials to prevent oxygen from interacting with the meat, to hold meat odors within the package, and to provide a clear view of the meat. Isaksson et al. (1992) used NIR (11002500 nm) and NIR transmission spectroscopy (8501100 nm) to meas-ure the protein, fat, and water content in packaged homogenized beef. The laminate of polyamide (PA)/ethylenevinyl alcohol (EVOH)/PA/ polyethylene (PE) was applied to the beef that was 85 m thick. The PE layer was in contact with the beef whereas the PA lay