Application of NIR spectroscopy coupled with DD-SIMCA class modelling for the authentication of pork meat

Totaro, Michela Pia; Squeo, Giacomo; Angelis, Davide De; Pasqualone, Antonella; Caponio, Francesco; Summo, Carmine

doi:10.1016/j.jfca.2023.105211

Cited by 9 publications

(2 citation statements)

References 44 publications

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“…Chicken Status identification: fresh or frozen NIR PLS-DA, CPANN, SVM [125] Sausages (pork and beef mix) Soy protein adulteration E-nose PCA, PNN [126] Beef meat preparation Wild boar meat adulteration FTIR PCA, PLS [127] Beef, lamb and venison Discrimination red meats Spectroscopy Raman PCA, PLS-DA και SVM [128] Beef mixture Chicken adulteration ATR-FTIR PCA, PLSR, ANN [129] Beef meat preparation Adulteration with another type of meat FTIR PCA, PLS-DA και SIMCA [130] Minced pork Aging and wear, characterization of changes during storage and spoilage HS-SPME-GC-MS PCA, OPLS-DA [131] Beef meat Adulteration with maltodextrin MIR PLS-DA [132] Beef, pork, chicken and turkey meat Physicochemical characteristics FTIR PCA, PLSR [118] Sausages Radiation treatment process NIR PCA, OPLS-DA [119] Beef muscle Bacterial growth at two storage temperatures Vis-NIR HIS TVC, PLSR [120] Hamburger Sodium content NIR PLS, PLS-DA [121] Ground beef Adulteration with pork and duck meat NIR DA, PLS [122] Beef sausage Adulteration with pork LC-HRMS PLS-DA [133] Sausage products Adulteration with pork GC-MS, FTIR PCA [134] Pork meat Authenticity of pork fat according to the rearing system NIR DD-SIMCA [135] Chicken Geographical origin ICP-OES, ICP-MS OPLS-DA, CDA [136] 3.5. Current Analytical Methods for Fish and Fishery Products Authentication and Chemometrics…”

Section: Type Of Matrix Purpose Of Study Methods Of Analysis Chemomet...mentioning

confidence: 99%

Current State of Milk, Dairy Products, Meat and Meat Products, Eggs, Fish and Fishery Products Authentication and Chemometrics

Smaoui,

Tarapoulouzi,

Agriopoulou

et al. 2023

Foods

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Food fraud is a matter of major concern as many foods and beverages do not follow their labelling. Because of economic interests, as well as consumers’ health protection, the related topics, food adulteration, counterfeiting, substitution and inaccurate labelling, have become top issues and priorities in food safety and quality. In addition, globalized and complex food supply chains have increased rapidly and contribute to a growing problem affecting local, regional and global food systems. Animal origin food products such as milk, dairy products, meat and meat products, eggs and fish and fishery products are included in the most commonly adulterated food items. In order to prevent unfair competition and protect the rights of consumers, it is vital to detect any kind of adulteration to them. Geographical origin, production methods and farming systems, species identification, processing treatments and the detection of adulterants are among the important authenticity problems for these foods. The existence of accurate and automated analytical techniques in combination with available chemometric tools provides reliable information about adulteration and fraud. Therefore, the purpose of this review is to present the advances made through recent studies in terms of the analytical techniques and chemometric approaches that have been developed to address the authenticity issues in animal origin food products.

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Section: Type Of Matrix Purpose Of Study Methods Of Analysis Chemomet...mentioning

confidence: 99%

Current State of Milk, Dairy Products, Meat and Meat Products, Eggs, Fish and Fishery Products Authentication and Chemometrics

Smaoui,

Tarapoulouzi,

Agriopoulou

et al. 2023

Foods

View full text Add to dashboard Cite

show abstract

“…In this context, the dry-cured loins' spectra obtained after each pre-treatment are presented in Figure 1. The NIR spectra of the samples present typical broader peaks related to major constituents of proteins, lipids and water [20,60,61]. The major peaks are assigned in Figure 1c; C-H bonds correspond to 1200 nm, 1710-1760 nm and 2300-2350 nm (first overtone, second overtone and combination band, respectively).…”

Section: Nir Spectramentioning

confidence: 97%

Can Near-Infrared Spectroscopy Replace a Panel of Tasters in Sensory Analysis of Dry-Cured Bísaro Loin?

Vasconcelos,

Dias,

Leite

et al. 2023

Foods

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This study involved a comprehensive examination of sensory attributes in dry-cured Bísaro loins, including odor, androsterone, scatol, lean color, fat color, hardness, juiciness, chewiness, flavor intensity and flavor persistence. An analysis of 40 samples revealed a wide variation in these attributes, ensuring a robust margin for multivariate calibration purposes. The respective near-infrared (NIR) spectra unveiled distinct peaks associated with significant components, such as proteins, lipids and water. Support vector regression (SVR) models were methodically calibrated for all sensory attributes, with optimal results using multiplicative scattering correction pre-treatment, MinMax normalization and the radial base kernel (non-linear SVR model). This process involved partitioning the data into calibration (67%) and prediction (33%) subsets using the SPXY algorithm. The model parameters were optimized via a hybrid algorithm based on particle swarm optimization (PSO) to effectively minimize the root-mean-square error (RMSECV) derived from five-fold cross-validation and ensure the attainment of optimal model performance and predictive accuracy. The predictive models exhibited acceptable results, characterized by R-squared values close to 1 (0.9616–0.9955) and low RMSE values (0.0400–0.1031). The prediction set’s relative standard deviation (RSD) remained under 5%. Comparisons with prior research revealed significant improvements in prediction accuracy, particularly when considering attributes like pig meat aroma, hardness, fat color and flavor intensity. This research underscores the potential of advanced analytical techniques to improve the precision of sensory evaluations in food quality assessment. Such advancements have the potential to benefit both the research community and the meat industry by closely aligning their practices with consumer preferences and expectations.

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ATR‐FTIR Spectroscopy Preprocessing Technique Selection for Identification of Geographical Origins of Gastrodia elata Blume

Liu,

et al. 2024

Journal of Chemometrics

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Gastrodia elata Blume from different regions varies in growth conditions, soil types, and climate, which directly affects the content and quality of its medicinal components. Accurately identifying the origin can effectively ensure the medicinal value of G. elata Bl., prevent the circulation of counterfeit products, and thus protect the interests and health of consumers. Attenuated total reflectance Fourier transform infrared (ATR‐FTIR) spectroscopy is a rapid and effective method for verifying the authenticity of traditional Chinese medicines. However, the presence of scattering effects in the spectra poses challenges in establishing reliable discrimination models. Therefore, employing appropriate scattering correction techniques is crucial for improving the quality of spectral data and the accuracy of discrimination models. This study uses two ensemble preprocessing approaches; the first type is series fusion of scatter correction technologies (SCSF), and another method is sequential preprocessing through orthogonalization (SPORT). Four discriminant models were established using a single scattering correction technique and two ensemble preprocessing approaches. The results show that the data‐driven version of the soft independent modeling of class analogy (DD‐SIMCA) model built based on multiplicative scatter correction (MSC) preprocessing has a sensitivity of 0.98 and a specificity of 0.91, able to effectively distinguish whether a sample of G. elata Bl. originates from Zhaotong. In addition, three discriminant models including support vector machine (SVM), partial least squares discriminant analysis (PLS‐DA), and three gradient boosting machine (GBM) algorithms built using the ensemble preprocessing approach have good classification and generalization capabilities. Among them, the SCSF‐PLS‐DA model has the best performance with 99.68% and 98.08% accuracy for the training and test sets, respectively, and F1 of 0.97; the SPORT‐SVM model achieved the second‐best classification ability. The results show that the ensemble preprocessing approach used can improve the success rate of G. elata Bl. geographical origin classification.

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Application of NIR spectroscopy coupled with DD-SIMCA class modelling for the authentication of pork meat

Cited by 9 publications

References 44 publications

Current State of Milk, Dairy Products, Meat and Meat Products, Eggs, Fish and Fishery Products Authentication and Chemometrics

Current State of Milk, Dairy Products, Meat and Meat Products, Eggs, Fish and Fishery Products Authentication and Chemometrics

Can Near-Infrared Spectroscopy Replace a Panel of Tasters in Sensory Analysis of Dry-Cured Bísaro Loin?

ATR‐FTIR Spectroscopy Preprocessing Technique Selection for Identification of Geographical Origins of Gastrodia elata Blume

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