Methods for detection of pork adulteration in veal product based on FT-NIR spectroscopy for laboratory, industrial and on-site analysis

Schmutzler, Matthias; Beganović, Anel; Bohler, G.; Huck, Christian W.

doi:10.1016/j.foodcont.2015.04.019

Cited by 110 publications

(54 citation statements)

References 29 publications

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“…Recently, the performance of three different methods based on NIR spectroscopy was evaluated for detecting adulteration of pure veal sausages with pork meat or fat, namely, a high-performance Fourier-transform-NIR (FT-NIR) laboratory desktop device, an FT-NIR equipped with a fiber-optic probe suitable for industrial application and a handheld FT-NIR spectrometer for on-site use (Schmutzler et al, 2015). After pretreatment of spectral data, PCA scores were used as input data for support vector machines classification and validation.…”

Section: Spectroscopic Methodsmentioning

confidence: 99%

Advances in Authenticity Testing for Meat Speciation

Amaral

Meira

Oliveira

et al. 2016

Advances in Food Authenticity Testing

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Section: Spectroscopic Methodsmentioning

confidence: 99%

Advances in Authenticity Testing for Meat Speciation

Amaral

Meira

Oliveira

et al. 2016

Advances in Food Authenticity Testing

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“…However, although the demand for portable devices has increased (Bouyé & d'Humières, 2017), its focus has been the evaluation of food quality and composition, especially in meat, dairy products, and fruits and vegetables (Abasi et al, 2018;Capitani, Sobolev, Di Tullio, Mannina, & Proietti, 2017;Porep, Kammerer, & Carle, 2015). In addition, there are works based on portable/handheld spectrometer for food authentication (Basri et al, 2017;Correia et al, 2018;Grassi & Alamprese, 2018;Limm, Karunathilaka, Yakes, & Mossoba, 2018;Liu et al, 2018;Manfredi et al, 2018;Nieuwoudt, Holroyd, McGoverin, Simpson, & Williams, 2016;Picouet, Gou, Hyypiö, & Castellari, 2018;Schmutzler, Beganovic, Böhler, & Huck, 2015;Shotts, Plans Pujolras, Rossell, & Rodriguez-Saona, 2018;Vargas Jentzsch, Torrico-Vallejos, Mendieta-Brito, Ramos, & Ciobotȃ, 2016).…”

Section: Portable/handheld Spectrometers For Spice's Authenticationmentioning

confidence: 99%

Nontargeted Analytical Methods as a Powerful Tool for the Authentication of Spices and Herbs: A Review

Oliveira

Cruz-Tirado

Barbin

2019

Comp Rev Food Sci Food Safe

108

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Food fraud in herbs and spices is an important topic, which has led to new technologies being studied as potential tools for fraud identification. Nontargeted technologies have proven to be a useful tool for the authentication of herbs and spices. The present review focuses on the use of near‐infrared, hyperspectral imaging, Fourier‐transform infrared, Raman, nuclear magnetic resonance, and electron spin resonance spectroscopy for the authentication of spices, which includes the determination of origin and irradiated spices and the identification of adulterants. The methods developed based on vibrational spectroscopy combined with chemometric techniques seem to be promising tools for determining the presence of adulterants and contaminants in herbs and spices. On the other hand, nuclear magnetic resonance seems to be the most efficient technology to determine the origin of herbs and spices although, for some cases, studies with near‐infrared spectroscopy can be a viable substitute. Electron spin resonance spectroscopy is the technique par excellence used for the authentication of irradiated herbs and spices, so its use should be expanded to many more spices’ varieties. Portable devices are preferred by those involved in the food industry, due to its manageability and low cost. Data fusion and big data are shown as promising tools for spice fraud control. In conclusion, spectroscopic techniques show a great efficiency to authenticate spices, although their evaluation must be expanded to other spice varieties, to new strategies of data analysis (as data fusion and big data), and to the use of portable devices.

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“…Many researchers successfully used spectroscopic techniques for predicting adulteration in minced meat. Schmutzler et al 35 successfully applied Fourier transform-NIR (FT-NIR) spectroscopy for the detection of pork adulteration in veal products. Schmutzler et al 35 successfully applied Fourier transform-NIR (FT-NIR) spectroscopy for the detection of pork adulteration in veal products.…”

Section: Spectral Analysis In the Full Wavelength Rangementioning

confidence: 99%

Hyperspectral imaging in tandem with multivariate analysis and image processing for non-invasive detection and visualization of pork adulteration in minced beef

2015

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Pork adulteration in minced beef was detected for the first time using a hyperspectral imaging (HIS) technique. Minced beef samples were adulterated with minced pork in the range of 2-50% (w/w) at approximately 2% intervals. Images were acquired using a visible near-infrared hyperspectral imaging (VNIR-HSI) system and their spectral data were extracted. Several data pre-treatments and different linear multivariate analyses, namely partial least squares regression (PLSR), principal component regression (PCR), and multiple linear regression (MLR), were investigated to determine the predictive ability of VNIR-HSI in detecting pork meat adulteration in minced beef. PLSR had a better performance than PCR for predicting pork adulteration in minced beef. Only four wavelengths centered at 430, 605, 665, and 705 nm were selected as the important wavelengths to build the MLR model for visualizing the distribution of adulteration. The results confirm that HSI can be used to provide a rapid, low cost, and nondestructive testing technique for detection of adulteration in minced meat.

show abstract

Methods for detection of pork adulteration in veal product based on FT-NIR spectroscopy for laboratory, industrial and on-site analysis

Cited by 110 publications

References 29 publications

Advances in Authenticity Testing for Meat Speciation

Advances in Authenticity Testing for Meat Speciation

Nontargeted Analytical Methods as a Powerful Tool for the Authentication of Spices and Herbs: A Review

Hyperspectral imaging in tandem with multivariate analysis and image processing for non-invasive detection and visualization of pork adulteration in minced beef

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