Developments and Challenges in Online NIR Spectroscopy for Meat Processing

Dixit, Yash; Casado-Gavalda, Maria P.; Cama-Moncunill, Raquel; Cama-Moncunill, Xavier; Markiewicz-Kęszycka, Maria; Cullen, Patrick J.; Sullivan, Carl

doi:10.1111/1541-4337.12295

Cited by 99 publications

(43 citation statements)

References 89 publications

(134 reference statements)

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“…The comparison of these findings with the raw spectra shown in Figure 2 confirms the significant role of reflectance bands in the range 570-700 nm and 700-970 nm for the development of PLS-R models [38,68]. As mentioned above, absorption bands at NIR region of 910 nm seemed to be associated with proteins, which are in abundance in chicken meat, especially in chicken breast [61].…”

Section: Discussionsupporting

confidence: 74%

“…More specifically, reflectance at 570-700 nm is related to respiratory pigments such as myoglobin (570 nm), oxymyoglobin (590 nm) and metmyoglobin (630 nm) [23,24,59]. In the NIR region, absorption bands at 910 nm are linked to denaturation of proteins [60,64] while at 750 and 970 nm, O-H second overtones are related to the moisture content in the samples [26,38,53]. In addition, absorption bands observed in the NIR region (928 and 940 nm) are correlated to the presence of fatty acids and fat within the sample matrix [14,60,65].…”

Section: Discussionmentioning

confidence: 99%

“…So far there are limited studies on the implementation of spectroscopic methods during processing at meat industries [38] and the majority is focused on the determination of fat and fatty acids in pork and chicken breast fillets with near-infrared sensors [39][40][41][42]. Hence, the aim of this research was to investigate the potential of multispectral imaging, applied in a poultry processing industry, to determine the time from slaughter of four different poultry products and develop PLS-R models assessing the time from slaughter directly from spectral data.…”

Section: Introductionmentioning

confidence: 99%

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Implementation of Multispectral Imaging (MSI) for Microbiological Quality Assessment of Poultry Products

Spyrelli

Doulgeraki²,

Argyri³

et al. 2020

Microorganisms

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The aim of this study was to investigate on an industrial scale the potential of multispectral imaging (MSI) in the assessment of the quality of different poultry products. Therefore, samples of chicken breast fillets, thigh fillets, marinated souvlaki and burger were subjected to MSI analysis during production together with microbiological analysis for the enumeration of Total Viable Counts (TVC) and Pseudomonas spp. Partial Least Squares Regression (PLS-R) models were developed based on the spectral data acquired to predict the “time from slaughter” parameter for each product type. Results showed that PLS-R models could predict effectively the time from slaughter in all products, while the food matrix and variations within and between batches were identified as significant factors affecting the performance of the models. The chicken thigh model showed the lowest RMSE value (0.160) and an acceptable correlation coefficient (r = 0.859), followed by the chicken burger model where RMSE and r values were 0.285 and 0.778, respectively. Additionally, for the chicken breast fillet model the calculated r and RMSE values were 0.886 and 0.383 respectively, whereas for chicken marinated souvlaki, the respective values were 0.934 and 0.348. Further improvement of the provided models is recommended in order to develop efficient models estimating time from slaughter.

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Section: Discussionsupporting

confidence: 74%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Implementation of Multispectral Imaging (MSI) for Microbiological Quality Assessment of Poultry Products

Spyrelli

Doulgeraki²,

Argyri³

et al. 2020

Microorganisms

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“…Analyses of the NIR spectra can be performed using mathematical models and multivariate analysis (chemometrics). Chemometrics utilizes various multivariate techniques, such as principal component regression (PCR) and partial least squares (PLS), in order to build models with the use of reference chemical data obtained through other analytical techniques 29 . However, in the case of the high non-linearity, the mentioned techniques lead to substantial errors.…”

Section: Introductionmentioning

confidence: 99%

Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves

Valinger

Kušen²,

Tušek

et al. 2019

Chem.Biochem.Eng.Q.

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The objective of this work was to evaluate the ability of artificial neural networks (ANN) in near infrared (NIR) spectra calibration models to predict the total polyphenolic content, antioxidant activity, and extraction yield of the olive leaves aqueous extracts prepared with three extraction procedures (conventional extraction, microwave-assisted extraction, and microwave-ultrasound-assisted extraction). Partial least squares (PLS) models were developed from principal component analyses (PCA) scores of NIR spectra of olive leaf aqueous extracts in terms of total polyphenols concentration, antioxidant activity, and extraction yield for each extraction procedure. PLS models were used to view which PCA scores are the best suited as input for ANN based on three output variables. ANN showed very good correlation of NIRs and all tested variables, especially in the case of total polyphenolic content (TPC). Therefore, ANN can be used for the prediction of total polyphenol concentrations, antioxidant activity, and extraction yield of plant extracts based on the NIR spectra.

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“…Applications of the NIR technique to the evaluation of meat quality have been reviewed. (23) The NIR technique has the potential of detecting meat adulteration, (24,25) assessing meat microbial spoilage, (26,27) and estimating meat quality. (28,29) Nowadays, several research studies on Japanese wagyu beef have shown that NIR spectroscopy can be applied to predict the fat content and quantify the fatty acid composition.…”

mentioning

confidence: 99%

Prediction of Glycogen and Moisture Contents in Japanese Wagyu Beef by Fourier Transform Near-infrared Spectroscopy for Quality Evaluation

Yao¹,

Oe²,

Ye³

et al. 2019

Sensors and Materials

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Keywords: glycogen, moisture content, Japanese wagyu beef, FT-NIR, PLSR (MSC) yielded optimum results with R p 2 of 0.795, RMSEP of 2.669%, and RPD of 2.008. The results of this study demonstrated that NIR spectroscopy offers great potential for the prediction of glycogen and moisture contents in Japanese wagyu beef samples. effect on Japanese consumers' preference owing to the improvement in beef quality such as tenderness. (2)(3)(4)(5)(6)(7) This is consistent with the conclusion that tenderness is the most important factor affecting beef palatability. (8)(9)(10)(11) However, additional studies have shown that when tenderness is at an acceptable level, flavor becomes the next most important factor affecting the beef preference of consumers. (10)(11)(12)(13)(14)(15) Flavor is a complex concept, which is composed of taste, odor, and the interaction of these factors. In our previous work, a sensory panel test was used to determine the relationship between sensory attributes (e.g., sweetness, fattiness, aroma, tenderness, flavor, and overall evaluation) and chemical composition characteristics (e.g., moisture, protein, free amino acid, glycogen, and fatty acid contents) of Japanese wagyu beef by the simmering method. (16) We demonstrated that the 'flavor' of sensory attributes was associated with glycogen and moisture contents. It has been widely reported that pre rigor muscle glycogen content has a negative curvilinear relationship with ultimate pH, (17) which is an indicator of the final palatability of meat. (18,19) In addition, the glycogen content in the muscle is related to the amounts of monosaccharides such as glucose and fructose after slaughter, which affect the development of meat flavor via the Maillard reaction; therefore, glycogen contributes to beef palatability. (20) Moisture content is often used to assess meat quality. (21) It also has a strong relationship with the contents of lipids that affect sensory attributes such as flavor, juiciness, texture, and appearance. (22) Therefore, to satisfy an increasing demand for evaluating meat quality by either the meat processing industry or consumers, fast, accurate, and nondestructive methods are urgently required.In recent years, near-infrared (NIR) spectroscopy, which is based on optical measurements of reflectance, transmittance, and interactance, has been considered as a nondestructive, fast, convenient, inexpensive, and precise technique. NIR spectroscopy combined with various multivariable data processing techniques has been effectively employed. Applications of the NIR technique to the evaluation of meat quality have been reviewed. (23) The NIR technique has the potential of detecting meat adulteration, (24,25) assessing meat microbial spoilage, (26,27) and estimating meat quality. (28,29) Nowadays, several research studies on Japanese wagyu beef have shown that NIR spectroscopy can be applied to predict the fat content and quantify the fatty acid composition. Kobayashi et al. have demonstrated the correlation between fat content and spectral infor...

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Developments and Challenges in Online NIR Spectroscopy for Meat Processing

Cited by 99 publications

References 89 publications

Implementation of Multispectral Imaging (MSI) for Microbiological Quality Assessment of Poultry Products

Implementation of Multispectral Imaging (MSI) for Microbiological Quality Assessment of Poultry Products

Development of Near Infrared Spectroscopy Models for Quantitative Prediction of the Content of Bioactive Compounds in Olive Leaves

Prediction of Glycogen and Moisture Contents in Japanese Wagyu Beef by Fourier Transform Near-infrared Spectroscopy for Quality Evaluation

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