Rapid Identification and Visualization of Jowl Meat Adulteration in Pork Using Hyperspectral Imaging

Jiang, Hongzhe; Cheng, Fengna; Shi, Minghong

doi:10.3390/foods9020154

Cited by 63 publications

(34 citation statements)

References 42 publications

(45 reference statements)

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“…Being rapid, non-invasive, and providing spectral and spatial features simultaneously are some of its significant advantages. Numerous articles describe the pros and cons of HSI-based methods for food authenticity and adulteration analyses [14,15]. Nowadays, low-cost, rapid, and simple multispectral imaging systems are being designed for the determination of particular adulterations [120].…”

Section: Other Spectroscopic Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

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

Hassoun

Måge

Schmidt

et al. 2020

Foods

111

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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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Section: Other Spectroscopic Techniquesmentioning

confidence: 99%

“…One of the main advantages of HSI is the possibility to generate a distribution map, allowing the visualization of adulteration levels [14,20]. On the other hand, the data generated from HSI are extremely vast, requiring complex data handling.…”

Section: Meat and Meat Productsmentioning

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

111

View full text Add to dashboard Cite

show abstract

“…In the study of Jiang et al [7], a hyperspectral imaging (HSI) methodology was proposed to identify and visualize this kind of jowl meat adulteration in pork. Numerous hyperspectral images were acquired from adulterated meat samples in the range of 0-100% (w/w) at 10% increments using a visible and near-infrared (400-1000 nm) HSI system in reflectance mode.…”

Section: General Remarksmentioning

confidence: 99%

Advances of Spectrometric Techniques in Food Analysis and Food Authentication Implemented with Chemometrics

Karabagias

2020

Foods

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Given the continuous consumer demand for products of high quality and specific origin, there is a great tendency for the application of multiple instrumental techniques for the complete characterization of foodstuffs or related natural products. Spectrometric techniques usually offer a full and rapid screenshot of products’ composition and properties by the determination of specific bio-molecules such as sugars, minerals, polyphenols, volatile compounds, amino acids, organic acids, etc. The present special issue aimed firstly to enhance the advances of the application of spectrometric techniques such as gas chromatography coupled to mass spectrometry (GC-MS), inductively coupled plasma optical emission spectrometry (ICP-OES), isotope ratio mass spectrometry (IRMS), nuclear magnetic resonance (NMR), Raman spectroscopy, or any other spectrometric technique, in the analysis of foodstuffs such as meat, milk, cheese, potatoes, vegetables, fruits/fruit juices, honey, olive oil, chocolate, and other natural products. An additional goal was to fill the gap between food composition/food properties/natural products properties and food/natural products authenticity, using supervised and non-supervised chemometrics. Of the 18 submitted articles, nine were eventually published, providing new information to the field.

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“…Hyperspectral imaging (HSI) can integrate traditional image and spectrum to provide information on the spatial and spectral features of an object [24]. Compared with NIR spectroscopy and machine vision, HSI can collect the spectral information of whole seed sample, which is helpful to obtain the more robust detection results in the assessment of MC of seeds [25,26]. In recent years, HSI technology has been widely used to detect quality of many agricultural products such as meat [27,28], fruit [29], vegetables [30] and nut [31].…”

Section: Introductionmentioning

confidence: 99%

Determination of Moisture Content of Single Maize Seed by Using Long-Wave Near-Infrared Hyperspectral Imaging (LWNIR) Coupled With UVE-SPA Combination Variable Selection Method

et al. 2020

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Moisture content (MC) is one of the important factors to assess the quality of maize seeds. In this study, the feasibility of using long-wave near infrared (LWNIR) hyperspectral imaging (HSI) technique with the spectral range of 930-2548 nm for predicting MC of single maize seeds was observed. The averaged spectra extracted from whole and centroid regions in the embryo side of single maize seeds were pretreated by Savizky-Golay smoothing and first derivative (SG-D1). A combination of uninformative variable elimination (UVE) and successive projections algorithm (SPA) was proposed to select feature wavelengths (variables) from LWNIR hyperspectral data. The quantitative relationship between feature wavelengths and MC was established by partial least square (PLSR) and least square-support vector machine (LS-SVM), respectively. Results illustrated that the UVE-SPA-LS-SVM model established based on spectra of centroid region obtained the best performance for MC detection of the single maize seeds. The correlation coefficient of prediction (Rpre) and root mean square error of prediction (RMSEP) were 0.9325 and 1.2109, respectively. Finally, MC distribution of single maize seed was visualized by pseudo-color map. This study showed LWNIR HSI technique was feasible to measure MC of single maize seeds and a robust and accurate model could be established based on UVE-SPA-LS-SVM method with the spectra of centroid regions.

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Rapid Identification and Visualization of Jowl Meat Adulteration in Pork Using Hyperspectral Imaging

Cited by 63 publications

References 42 publications

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

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

Advances of Spectrometric Techniques in Food Analysis and Food Authentication Implemented with Chemometrics

Determination of Moisture Content of Single Maize Seed by Using Long-Wave Near-Infrared Hyperspectral Imaging (LWNIR) Coupled With UVE-SPA Combination Variable Selection Method

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