Rapid Identification of Pork Adulterated in the Beef and Mutton by Infrared Spectroscopy

Yang, Ling; Wu, Ting; Liu, Yun; Zou, Juan; Huang, Yunmao; V., Sarath Babu; Li, Lin

doi:10.1155/2018/2413874

Cited by 34 publications

(18 citation statements)

References 43 publications

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“…However, pork adulteration in beef has been discovered in the market [3], [6]. The practice of mixing beef with pork is sometimes done for economic reasons [7], [8]; the seller adulterates pork in beef because pork is cheaper than beef [9]. Recent research has discussed meat authentication using visual detection.…”

Section: Introductionmentioning

confidence: 99%

Detecting Pork Adulteration in Beef for Halal Authentication Using an Optimized Electronic Nose System

et al. 2020

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Recently, the issue of food authentication has gained attention, especially halal authentication, because of cases of pork adulteration in beef. Many studies have developed rapid detection for adulterated meat. However, these studies are not yet practical and economical methods and instruments and a faster analysis process. In this context, this paper proposes the Optimized Electronic Nose System (OENS) for more accurately detecting pork adulteration in beef. OENS has advantages such as proper noise filtering, an optimized sensor array, and optimized support vector machine (SVM) parameters. Noise filtering is carried out by cross-validation with different mother wavelets, i.e., Haar, dmey, coiflet, symlet, and Daubechies. The sensor array was optimized by dimension reduction using principal component analysis (PCA). An algorithm is proposed for the optimization of the SVM parameters. An experiment was conducted by analyzing seven classes of meat, comprising seven different mixtures of beef and pork. The first and seventh classes were 100% beef and 100% pork, respectively, while the second, third, fourth, fifth, and sixth classes contained 10%, 25%, 50%, 75%, and 90% of beef in a sample of 100 grams, respectively. Sample testing was carried out for 15 minutes for each sample. The classification test results to detect beef and pork had an accuracy of 98.10% using the optimized support vector machine. Thus, OENS has a favorable performance to detect pork adulteration in beef for halal authentication.

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Section: Introductionmentioning

confidence: 99%

Detecting Pork Adulteration in Beef for Halal Authentication Using an Optimized Electronic Nose System

et al. 2020

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“…While using SVM, the classification models were worse than using PLS-DA with R 2 calibration, R 2 prediction, RMSEC, RMSECV, and RMSEP were of 0.97, 0.96, 0.15, 0.17, and 0.24, respectively. Therefore, it can be concluded that FTIR spectroscopy coupled with PLS-DA provided better classification method than SVM method, which can be used as effective tools to identify beef, mutton and that adulterated with pork [46].…”

Section: Methodsmentioning

confidence: 99%

Application of FTIR spectroscopy and chemometrics for authentication of meat and meat products: a review

Rohman

2019

J Adv Vet Anim Res

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Meat-based food such as meatball and sausages are important sources of protein needed for the human body. Due to different prices, some unethical producers try to adulterate high-price meat such as beef with lower priced meat like pork and rat meat to gain economical profits, therefore, reliable and fast analytical techniques should be developed, validated, and applied for meat traceability and authenticity. Some instrumental techniques have been applied for the detection of meat adulteration, mainly relied on DNA and protein using polymerase chain reaction and chromatographic methods, respectively. But, this method is time-consuming, needs a sophisticated instrument, involves complex sample preparation which make the method is not suitable for routine analysis. As a consequence, a simpler method based on spectroscopic principles should be continuously developed. Food samples are sometimes complex which resulted in complex chemical responses. Fortunately, a statistical method called with chemometrics could solve the problems related to complex chemical data. This mini-review highlights the application of Fourier-transform infrared spectroscopy coupled with numerous chemometrics techniques for authenticity and traceability of meat and meat-based products.

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“…Authentication in meats is required for foods that are labeled as individual meats [71]. Horsemeat in minced beef [72], beef and mutton in pork [73], and rainbow trout in Atlantic salmon [74] each require sufficient data specific to substances to be labeled to assure the meat contaminant is properly characterized in order to identify markers characteristic of each additional component. Spectral data on the primary meat preferentially needs to be oversampled relative to that of a contaminant, or of minor or occasional components that could be misinterpreted as unrelated to the original meat.…”

Section: Vibrational Spectroscopymentioning

confidence: 99%

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

Hassoun

Måge

Schmidt

et al. 2020

Foods

105

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Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance. Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud. It is the aim of the present manuscript to review the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions will also be discussed.

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Rapid Identification of Pork Adulterated in the Beef and Mutton by Infrared Spectroscopy

Cited by 34 publications

References 43 publications

Detecting Pork Adulteration in Beef for Halal Authentication Using an Optimized Electronic Nose System

Detecting Pork Adulteration in Beef for Halal Authentication Using an Optimized Electronic Nose System

Application of FTIR spectroscopy and chemometrics for authentication of meat and meat products: a review

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

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