Rapid determination of the fatty acid profile in pork dry-cured sausages by NIR spectroscopy

Evaluating near-infrared spectroscopy as a rapid and cost-effective method for fatty acid profiling in Senegalese sole (Solea senegalensis)

This study evaluates the potential of near-infrared spectroscopy (NIRS) as a rapid and cost-effective technique for estimating the fatty acid profile of Senegalese sole (Solea senegalensis). Traditionally, lipid profiling in aquaculture products has relied on gas chromatography (GC), a highly accurate but time-consuming, costly and complex method requiring extensive sample preparation. In contrast, NIRS offers a non-invasive, rapid and accurate alternative for predicting chemical composition. While NIRS has shown success in lipid profiling for fatty fish species, its application to lean fish, such as Senegalese sole, presents challenges due to low lipid concentrations and overlapping spectral signals. In this study, Senegalese sole were fed experimental diets varying in marine protein and lipid content. Lipid profiles of 75 tissue samples were analysed using both GC and NIRS, with fatty acid content expressed as percentage of total fatty acids (% TFA) and as µg fatty acid per mg dry tissue (µg FA/mg dry tissue). Calibrations were developed using Modified Partial Least Squares Regression (MPLSR) and the prediction accuracy was assessed using calibration statistics. The results showed that dietary lipids significantly influenced the fatty acid composition of Senegalese sole, consistent with previous findings for marine fish. NIRS calibrations were most accurate when fatty acid content was expressed as µg FA/mg dry tissue, giving better predictions than % TFA. The best calibrations were obtained for oleic acid, the dominant fatty acid in Senegalese sole, with an R2cv of 0.83 and a ratio of standard deviation/cross validation error (RPD) of 2.44. Fatty acid group predictions were more accurate for monounsaturated fatty acids (MUFA) than for the other groups, with an R2cv of 0.85 and an RPD of 2.60. These results demonstrate the potential of NIRS as a rapid and cost-effective method for fatty acid profiling in Senegalese sole, particularly for the estimation of mono- and polyunsaturated fatty acids (MUFA and PUFA). However, further research is needed to improve the accuracy and robustness of NIRS prediction models. Expanding the calibration dataset to include greater variability in diet, season and cultivation conditions will improve the reliability of the method for wider applications.

The Role of Near-Infrared Spectroscopy in Food Quality Assurance: A Review of the Past Two Decades

During food quality control, NIR technology enables the rapid and non-destructive determination of the typical quality characteristics of food categories, their origin, and the detection of potential counterfeits. Over the past 20 years, the NIR results for a variety of food groups-including meat and meat products, milk and milk products, baked goods, pasta, honey, vegetables, fruits, and luxury items like coffee, tea, and chocolate-have been compiled. This review aims to give a broad overview of the NIRS processes that have been used thus far to assist researchers employing non-destructive techniques in comparing their findings with earlier data and determining new research directions.

Prediction of fatty acid composition in intact and minced fat of European autochthonous pigs breeds by near infrared spectroscopy

The fatty acids profile has been playing a decisive role in recent years, thanks to technological, sensory and health demands from producers and consumers. The application of NIRS technique on fat tissues, could lead to more efficient, practical, and economical in the quality control. The study aim was to assess the accuracy of Fourier Transformed Near Infrared Spectroscopy technique to determine fatty acids composition in fat of 12 European local pig breeds. A total of 439 spectra of backfat were collected both in intact and minced tissue and then were analyzed using gas chromatographic analysis. Predictive equations were developed using the 80% of samples for the calibration, followed by full cross validation, and the remaining 20% for the external validation test. NIRS analysis of minced samples allowed a better response for fatty acid families, n6 PUFA, it is promising both for n3 PUFA quantification and for the screening (high, low value) of the major fatty acids. Intact fat prediction, although with a lower predictive ability, seems suitable for PUFA and n6 PUFA while for other families allows only a discrimination between high and low values.

Across countries implementation of handheld near-infrared spectrometer for the on-line prediction of beef marbling in slaughterhouse

Only few studies have used Near-Infrared (NIR) spectroscopy to assess meat quality traits directly in the chiller. The aim of this study was therefore to investigate the ability of a handheld NIR spectrometer to predict marbling scores on intact meat muscles in the chiller. A total of 829 animals from 2 slaughterhouses in France and Italy were involved. Marbling was assessed according to the 3G (Global Grading Guaranteed) protocol using 2 different scores. NIR measurements were collected by performing 5 scans at different points of the Longissimus thoracis. An average MSA marbling score of 330-340 was obtained in the two countries. The prediction models provided a R² in external validation between 0.46 and 0.59 and a standard error of prediction between 83.1 and 105.5. Results did provide a moderate prediction of the marbling scores but can be useful in the European industry context to predict classes of MSA marbling.

Near-Infrared Reflectance Spectroscopy for Quantitative Analysis of Fat and Fatty Acid Content in Living Tenebrio molitor Larvae to Detect the Influence of Substrate on Larval Composition

Several studies have shown that mealworms (Tenebrio molitor L.) could provide animals and humans with valuable nutrients. Tenebrio molitor larvae were studied to determine whether their rearing diets affected their fat and fatty acid content and to ascertain if it is possible to detect the changes in the larval fat composition using near-infrared reflectance spectroscopy (NIRS). For this reason, a standard control diet (100% wheat bran) and an experimental diet, consisting of wheat bran and the supplementation of a different substrate (coconut flour, flaxseed flour, pea protein flour, rose hip hulls, grape pomace, or hemp protein flour) were used. The results showed lesser weight gain and slower growth rates for larvae raised on diets with a high fat content. A total of eight fatty acids were identified and quantified, where palmitic, oleic, and linoleic acids were the most prevalent and showed a correlation between larval content and their content in the rearing diets. There was a high content of lauric acid (3.2-4.6%), myristic acid (11.4-12.9%), and α-linolenic acid 8.4-13.0%) in mealworm larvae as a result of the high dietary content of these fatty acids. NIR spectra were also influenced by the fat and fatty acid composition, as larval absorbance values differed greatly. The coefficient of the determination of prediction (R²_P) was over 0.97, with an RPD value of 8.3 for the fat content, which indicates the high predictive accuracy of the NIR model. Furthermore, it was possible to develop calibration models with great predictive efficiency (R²_P = 0.81-0.95, RPD = 2.6-5.6) for all fatty acids, except palmitoleic and stearic acids which had a low predictive power (R²_P < 0.5, RPD < 2.0). The detection of fat and fatty acids using NIRS can help insect producers to quickly and easily analyze the nutritional composition of mealworm larvae during the rearing process.

Estimating Fat Components of Potato Chips Using Visible and Near-Infrared Spectroscopy and a Compositional Calibration Model

When aiming to assess the fat composition of commercial potato chip products, their diversity and the difficulties to verify the nutritional label of batches of chips by official methods are main challenges. Thus, the possibility of using alternative technologies is of great interest for both the industry and the public administration. Near-infrared spectroscopy (NIRS) is a rapid and non-destructive technique that has been proven useful in different applications in the food industry. However, suitable specific treatments of compositional references with NIRS methods have been until now very scarce in the literature. The nutritional label information is commonly given as percentage content values across several nutritional categories. This formally corresponds with the class of so-called compositional data, for which there are specific statistical methods. This study contributes to ongoing research on the feasibility of Vis/NIR spectroscopy for food nutritional labelling. In particular, a calibration model is formulated to estimate the relative content of fat in potato chips products based on NIR spectral signal that integrates a consistent statistical treatment of the nutritional reference data. The method provides accurate estimates of the fat composition, with this including saturated, monounsaturated, and polyunsaturated types of fat, as well as their total fat percentage (cross-validated overall R2 = 0.88 and R2 = 0.82 from ground and fragmented samples respectively) and shows its potential for both nutritional labelling and verification in a rapid and inexpensive manner.

Near-Infrared Spectroscopy (NIRS) as a Tool for Classification of Pre-Sliced Iberian Salchichón, Modified Atmosphere Packaged (MAP) According to the Official Commercial Categories of Raw Meat

This study evaluates near-infrared spectroscopy (NIRS) feasibility in combination with various pre-treatments and chemometric approaches for pre-sliced Iberian salchichón under modified atmosphere (MAP) classification according to the official commercial category (defined by the combination of genotype and feeding regime) of the raw material used for its manufacturing (Black and Red purebred Iberian and Iberian × Duroc crossed (50%) pigs, respectively, reared outdoors in a Montanera system and White Iberian × Duroc crossed (50%) pigs with feed based on commercial fodder) without opening the package. In parallel, NIRS feasibility in combination with partial least squares regression (PLSR) to predict main quality traits was assessed. The best-fitting models developed by means of partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) yielded high discriminant ability and thus offered a tool to support the assignment of pre-sliced MAP Iberian salchichón according to the commercial category of the raw material. In addition, good predictive ability for C18:3 n-3 was obtained, which may help to support quality control.

Near infrared spectroscopy (NIRS) as tool for classification into official commercial categories and shelf-life storage times of pre-sliced modified atmosphere packaged Iberian dry-cured loin

The potential of Near Infrared Spectroscopy combining different spectral treatments and classification models was assessed for the classification of individual pre-sliced Iberian dry-cured loin packaged under modified atmosphere packaging (MAP) into three official commercial categories (which involve the breed purity and production system) according to the current Iberian Quality Standard (Black, Red and White) and for the assignment to the shelf-life time (0, 4, 8 and 12 months). External validation results provided acceptable results, with up to 100% of samples correctly assigned to Black and White official commercial category and into all storage times. Actually the 100% assignments were obtained using more than one approach (SIMCA and LDA for commercial categories and PLS-DA, SIMCA and LDA for storage times). These results might contribute to support the on-line control of authenticity of official commercial category and to facilitate the monitoring of the quality of pre-package dry-cured products throughout the shelf-life prediction.

Physico-chemical and sensory characterization of sliced Iberian chorizo from raw material of three commercial categories and stability during refrigerated storage packaged under vacuum and modified atmospheres

Physico-chemical and sensory analysis of Iberian chorizo manufactured from three commercial categories raw material compiled in the current Spanish Iberian Quality standard (Black, Red; 100% Iberian and 50% Iberian × Duroc pigs, respectively, under Montanera, and White; 50% Iberian × Duroc pigs commercially fed) and packed under vacuum and modified atmosphere (MAP) were carried out, in order to address the influence of the genotype and animal production system and packaging on quality parameters, as well as the stability of these throughout long-term storage. Montanera categories showed higher values of γ-tocopherol, mono- and poly-unsaturated fatty acids, greater scores of flavour and taste and higher lipid oxidation during the whole storage. MAP preserved better colour, especially redness and lipid oxidative status. Iberian chorizo could attain a differentiated quality because of physico-chemical and sensorial characteristics derived from the Montanera that would be adequate preserved in both vacuum and MAP throughout long-term storage.

Prediction of stable isotopes and fatty acids in subcutaneous fat of Iberian pigs by means of NIR: A comparison between benchtop and portable systems

The potential of a portable Near Infrared spectrophotometer compared with that of NIR benchtop equipment is assessed to determine the¹³C/¹²C relationship of stable isotopes and the fatty acid content. 105 samples of subcutaneous fat of Iberian pigs collected at the time of their slaughter have been analyzed. The analysis of stable isotopes and gas chromatography were the methods of reference used. The samples were analyzed without prior handling (portable and benchtop NIR) and after extracting the fat (benchtop NIR). The results show that with the portable equipment it is possible to determine δ¹³C (‰), 12 fatty acids, and 5 summations of fatty acids (SFA, MUFA, PUFA, w3, and w6), while with the benchtop NIR equipment it is possible to measure δ¹³C (‰), 16 fatty acids, and the 5 summationsof fatty acids. The correlation coefficients of the portable equipment were slightly lower than those of the NIR benchtop equipment.

Potential Use of Near-Infrared Spectroscopy to Predict Fatty Acid Profile of Meat from Different European Autochthonous Pig Breeds

Autochthonous pig breeds provide products of differentiated quality, among which quality control is difficult to perform and insufficient for current market requirements. The present research evaluates the predictive ability of near-infrared (NIR) spectroscopy, combined with chemometric methods as a rapid and affordable tool to assure traceability and quality control. Thus, NIR technology was assessed for intact and minced muscle Longissimus thoracis et lumborum samples collected from 12 European autochthonous pig breeds for the quantification of lipid content and fatty acid composition. Different tests were performed using different numbers of samples for calibration and validation. The best predictive ability was found using minced presentation and set with 80% of the samples for the calibration and the remaining 20% for the external validation test for the following traits: lipid content and saturated and polyunsaturated fatty acids, which attained both the highest determination coefficients (0.89, 0.61, and 0.65, respectively) and the lowest root mean square errors in external validation (0.62, 1.82, and 1.36, respectively). Lower predictive ability was observed for intact muscles. These results could contribute to improve the management of autochthonous breeds and to ensure quality of their products by traditional meat industry chains.

A sound approach: Exploring a rapid and non-destructive ultrasonic pulse echo system for vegetable oils characterization

A rapid and non-destructive ultrasonic pulse echo system was developed for vegetable oils characterization. To understand the differences in the ultrasonic properties of the oils, physical traits, such as their viscosity and density, were related to the ultrasonic data. In turn, these physical traits were correlated with the fatty acid compositions of the oils. Eighty oil samples, including 30 extra virgin olive oil (EVOO), 15 refined olive oil, 15 pomace olive oil, 10 rapeseed oil, 5 sunflower oil and 5 peanut oil samples, were analysed for their sound properties, viscosities, densities and fatty acid compositions. It was observed that the ultrasonic velocity of EVOO decreased linearly with increase in temperature, the temperature coefficient of ultrasonic velocity in EVOO was -2.92 m·s^-1·°C^-1. The ultrasonic velocity of EVOO (1453 ± 2 m/s) differed significantly from those of pomace olive oil and the oils of other botanical origin, but not from the velocity of refined olive oil. Ultrasonic velocity was positively correlated with the density and negatively correlated with the viscosity of the oils. The higher density and lower viscosity of the oils were in turn related to a higher unsaturation degree of the oils. Hence, oils with a higher proportion of unsaturated fat present higher densities and lower viscosities, which resulted in higher ultrasonic velocity values. Ultrasonic measurements allow rapid, non-destructive analysis, and this first application for characterization of these oils is promising.

Assessing the influence of temperature on NIRS prediction models for the determination of sodium content in dry-cured ham slices

Temperature fluctuations are a key factor in the development of prediction models using near infrared spectroscopy (NIRS). In the present study, this influence has been investigated and a methodology has been proposed to reduce the effect of sample temperature on NIRS model prediction of the sodium content in dry-cured ham slices. Spectra were taken directly from the slices using a remote measurement probe (for non-contact analysis) at three different temperature ranges: -12 °C to -5°C, -5°C to 10 °C and 10 °C to 20 °C. Local and global temperature compensation methods were established. Partial-least squares (PLS) regression was used as a chemometrics tool to perform the calibrations. The results showed that local models were sensitive to changes in temperature, while a global temperature model using sample spectra over the entire temperature range showed good prediction ability, reducing the error caused by temperature fluctuations to acceptable levels for practical applications.

Non-Destructive Spectroscopic Techniques and Multivariate Analysis for Assessment of Fat Quality in Pork and Pork Products: A Review

Fat is one of the most important traits determining the quality of pork. The composition of the fat greatly influences the quality of pork and its processed products, and contribute to defining the overall carcass value. However, establishing an efficient method for assessing fat quality parameters such as fatty acid composition, solid fat content, oxidative stability, iodine value, and fat color, remains a challenge that must be addressed. Conventional methods such as visual inspection, mechanical methods, and chemical methods are used off the production line, which often results in an inaccurate representation of the process because the dynamics are lost due to the time required to perform the analysis. Consequently, rapid, and non-destructive alternative methods are needed. In this paper, the traditional fat quality assessment techniques are discussed with emphasis on spectroscopic techniques as an alternative. Potential spectroscopic techniques include infrared spectroscopy, nuclear magnetic resonance and Raman spectroscopy. Hyperspectral imaging as an emerging advanced spectroscopy-based technology is introduced and discussed for the recent development of assessment for fat quality attributes. All techniques are described in terms of their operating principles and the research advances involving their application for pork fat quality parameters. Future trends for the non-destructive spectroscopic techniques are also discussed.

Feasibility of near infrared transmittance spectroscopy to predict fatty acid composition of commercial processed meat

BACKGROUND

The new European Regulation 1169/2011 concerning nutrition declaration of food products compels the addition of saturated fatty acids, whereas the declaration of monounsaturated and polyunsaturated fatty acids remains voluntary. Therefore, the industry is interested in a more rapid, easy and less cost-effective analysis method for accomplishing this labelling regulation. The present study aimed to evaluate the ability of near infrared transmittance spectroscopy (wavelengths between 850 and 1050 nm) to predict the fatty acid (FA) composition of commercial processed meat samples (n = 310).

RESULTS

Good predictions were achieved for the absolute content of saturated, unsaturated, monounsaturated and polyunsaturated FA, as well as ω-6 groups, and also for a few individual FA (C16:0, C18:0, C18:1n9, C18:2n6 and 18:1n7), with the coefficient of determination in cross-validation being > 0.90 and the residual prediction deviation being > 3.15. Unsatisfactory models were obtained for the relative content of FA.

CONCLUSION

Near infrared transmittance spectroscopy can be considered as a reliable method for predicting the main groups of FA in processed meat products, whereas predictions of individual FA are less reliable. © 2017 Society of Chemical Industry.

Grading of Chinese Cantonese Sausage Using Hyperspectral Imaging Combined with Chemometric Methods

Fast and accurate grading of Chinese Cantonese sausage is an important concern for customers, organizations, and the industry. Hyperspectral imaging in the spectral range of 874–1734 nm, combined with chemometric methods, was applied to grade Chinese Cantonese sausage. Three grades of intact and sliced Cantonese sausages were studied, including the top, first, and second grades. Support vector machine (SVM) and random forests (RF) techniques were used to build two different models. Second derivative spectra and RF were applied to select optimal wavelengths. The optimal wavelengths were the same for intact and sliced sausages when selected from second derivative spectra, while the optimal wavelengths for intact and sliced sausages selected using RF were quite similar. The SVM and RF models, using full spectra and the optimal wavelengths, obtained acceptable results for intact and sliced sausages. Both models for intact sausages performed better than those for sliced sausages, with a classification accuracy of the calibration and prediction set of over 90%. The overall results indicated that hyperspectral imaging combined with chemometric methods could be used to grade Chinese Cantonese sausages, with intact sausages being better suited for grading. This study will help to develop fast and accurate online grading of Cantonese sausages, as well as other sausages.

A Review of the Principles and Applications of Near-Infrared Spectroscopy to Characterize Meat, Fat, and Meat Products

Consumer demand for quality and healthfulness has led to a higher need for quality assurance in meat production. This requirement has increased interest in near-infrared (NIR) spectroscopy due to the ability for rapid, environmentally friendly, and noninvasive prediction of meat quality or authentication of added-value meat products. This review includes the principles of NIR spectroscopy, pre-processing methods, and multivariate analyses used for quantitative and qualitative purposes in the meat sector. Recent advances in portable NIR spectrometers that enable new online applications in the meat industry are shown and their performance evaluated. Discrepancies between published studies and potential sources of variability are discussed, and further research is encouraged to face the challenges of using NIRS technology in commercial applications, so that its full potential can be achieved.

Rapid and non-destructive determination of drip loss and pH distribution in farmed Atlantic salmon (Salmo salar) fillets using visible and near-infrared (Vis-NIR) hyperspectral imaging

Drip loss and pH are important indices in quality assessment of salmon products. This work was carried out for rapid and non-destructive determination of drip loss and pH distribution in salmon fillets using near-infrared (Vis-NIR) hyperspectral imaging. Hyperspectral images were acquired for salmon fillet samples and their spectral signatures in the 400-1700nm range were extracted. Partial least square regression (PLSR) was used to correlate the spectra with reference drip loss and pH values. Important wavelengths were selected using the regression coefficients method to develop new PLSR models, leading to a correlation coefficient of cross-validation (rCV) of 0.834 with root-mean-square errors by cross-validation (RMSECV) of 0.067 for drip loss and a rCV of 0.877 with RMSECV of 0.046 for pH, respectively. Distribution maps of drip loss and pH were generated based on the new PLSR models using image processing algorithms. The results showed that Vis-NIR hyperspectral imaging technique combined with PLSR calibration analysis offers an effective quantitative capability for determining the spatial distribution of drip loss and pH in salmon fillets.

A correlative study on data from pork carcass and processed meat (Bauernspeck) for automatic estimation of chemical parameters by means of near-infrared spectroscopy

The use of near-infrared spectroscopy (NIRS) is proposed in this study for the characterization of the quality parameters of a smoked and dry-cured meat product known as Bauernspeck (originally from Northern Italy), as well as of some technological traits of the pork carcass used for its manufacturing. In particular, NIRS is shown to successfully estimate several key quality parameters (including water activity, moisture, dry matter, ash and protein content), suggesting its suitability for real time application in replacement of expensive and time consuming chemical analysis. Furthermore, a correlative approach based on canonical correlation analysis was used to investigate the spectral regions that are mostly correlated to the characteristics of interest. The identification of these regions, which can be linked to the absorbance of the main functional chemical groups, is intended to provide a better understanding of the chemical structure of the substrate under investigation.

Ultrasonic characterization of the fat source and composition of formulated dry-cured meat products

The aim of this work was to test the feasibility of using ultrasonic measurements to estimate the fat content and identify the fat sources used in formulated dry-cured pork meat products. For that purpose, dry-cured sausages were prepared using different fat sources (two Iberian pork backfats, Iberian lard, and sunflower oil) and contents (fat content from 3% to 17% wet basis) and characterized by measuring the ultrasonic velocity (at 2 ℃, 6 ℃, 10 ℃, 15 ℃, 20 ℃, and 25 ℃), fatty acid profile, thermal behavior, and composition. The fatty acid composition affected the melting behavior of the sausages, which also involved different ultrasonic velocities, depending on the fat source used for the sausage formulation. Significant ( p < 0.05) linear relationships were established between the ultrasonic velocity and the percentage of melted fat, by means of which the sausage batches were differentiated according to the fat source used. The ultrasonic velocity temperature dependence allowed the determination of the fat content (explained variance 96.1%) by measuring the ultrasonic velocity in the dry-cured sausages at 2 ℃ and 25 ℃ and using a semi-empirical equation. Therefore, the ultrasonic measurements could be considered as a reliable tool for the characterization and differentiation of formulated dry-cured meat products with different fat sources and contents.