Challenges in Model Development for Meat Composition Using Multipoint NIR Spectroscopy from At‐Line to In‐Line Monitoring

This study evaluates the efficiency of multipoint near‐infrared spectroscopy (NIRS) to predict the fat and moisture content of minced beef samples both in at‐line and on‐line modes. Additionally, it aims at identifying the obstacles that can be encountered in the path of performing in‐line monitoring. Near‐infrared (NIR) reflectance spectra of minced beef samples were collected using an NIR spectrophotometer, employing a Fabry‐Perot interferometer. Partial least squares regression (PLSR) models based on reference values from proximate analysis yielded calibration coefficients of determination of 0.96 for both fat and moisture. For an independent batch of samples, fat was estimated with a prediction coefficient of determination of 0.87 and 0.82 for the samples in at‐line and on‐line modes, respectively. All the models were found to have good prediction accuracy; however, a higher bias was observed for predictions under on‐line mode. Overall results from this study illustrate that multipoint NIR systems combined with multivariate analysis has potential as a process analytical technology (PAT) tool for monitoring process parameters such as fat and moisture in the meat industry, providing real‐time spectral and spatial information. Citing Literatur

Laser-induced breakdown spectroscopy for food authentication

With the globalisation of food markets, food authentication has become a significant concern worldwide to ensure food safety and to avoid origin and quality fraud. A multi-elemental fingerprint is a powerful tool for detection of adulterants and geographical origin of foods. Laser-induced breakdown spectroscopy (LIBS) is a promising technique that can provide a mineral fingerprint of food products. LIBS allows a rapid, high-throughput, micro-destructive and multi-elemental analysis of a wide range of samples type. It has already been demonstrated by several authors that LIBS can be successfully used for food authentication. Although LIBS shows excellent potential for at-line or portable applications, improvement in sensitivity of trace elements detection, sample preparation, data analysis and instrument miniaturisation are needed

Direct analysis of calcium in liquid infant formula via laser-induced breakdown spectroscopy (LIBS)

The present work illustrates the potential of laser-induced breakdown spectroscopy (LIBS) for the direct analysis of liquid food products. The aim of the experiment was to predict calcium content in ready-to-feed infant formula. The analysis was performed by a LIBS system coupled to a liquid sample chamber with a rotatory wheel that presents the liquid to the laser beam as a thin film. Multivariate analysis with partial least squares regression (PLSR) was performed to correlate LIBS spectral data to reference calcium contents. The obtained PLSR model exhibited a good fit and linearity, as indicated by the coefficients of determination for calibration (Rc 2) and cross-validation (Rcv 2), with values of 0.96 and 0.89, respectively. The robustness of the calibration model was assessed by external validation showing a root-mean-square error of prediction of 6.45 mg 100 mL−1. These results demonstrated the potential of LIBS for real-time analysis of liquid food products

Laser Induced Breakdown Spectroscopy for Quantification of Sodium and Potassium in Minced Beef: a Potential Technique for Detecting Beef Kidney Adulteration

Beef is a rich source of important minerals, with potassium (K) being the most abundant mineral quantitatively except in cured meats where sodium (Na) from the added salt predominates. This study evaluates the capability of LIBS for quantification of the Na and K contents of minced beef as a potential method of detecting beef kidney adulteration. Additionally, the study aims to demonstrate the ability of LIBS to provide spatial mineral information of minced beef. A LIBS system was employed to collect spectral information of adulterated minced beef samples. Atomic absorption spectroscopy (AAS) was used to obtain reference values for Na and K. The chemometric technique of partial least squares regression (PLSR) was used to build the prediction models. Spatial mineral maps of minced beef samples were generated based on the predicted percentages of Na and K. The models for Na and K yielded calibration coefficients of determination (Rc2) of 0.97 and 0.91 respectively. Similarly, a good calibration model was obtained for adulteration yielding a Rc2 of 0.97. Good prediction accuracy was observed for all models. Spatial mapping provided two major advantages: (a) representative measurements of samples and (b) spatial distribution of multi-elements. The results observed illustrate the ability of LIBS combined with chemometrics as a potential monitoring tool for mineral quantification as well as adulteration detection for the meat processing industry

Quantification of rubidium as a trace element in beef using laser induced breakdown spectroscopy

This study evaluates the potential of laser induced breakdown spectroscopy (LIBS) coupled with chemometrics to develop a quantification model for rubidium (Rb) in minced beef. A LIBSCAN 150 system was used to collect LIBS spectra of minced beef samples. Beef liver was used to spike the Rb levels in minced beef. All samples were dried, powdered and pelleted using a hydraulic press. Measurements were conducted by scanning 100 different locations with an automated XYZ sample chamber. Partial least squares regression (PLSR) was used to develop the calibration model, yielding a calibration coefficient of determination (Rc2) of 0.99 and a root mean square error of calibration (RMSEC) of 0.05ppm. The model also showed good results with leave-one-out cross validation, yielding a cross-validation coefficient of determination (Rcv2) of 0.90 and a root mean square error of cross-validation (RMSECV) of 0.22ppm. The current study shows the potential of LIBS as a rapid analysis tool for the meat processing industry

Quantification of trace metals in infant formula premixes using laser-induced breakdown spectroscopy

Infant formula is a human milk substitute generally based upon fortified cow milk components. In order to mimic the composition of breast milk, trace elements such as copper, iron and zinc are usually added in a single operation using a premix. The correct addition of premixes must be verified to ensure that the target levels in infant formulae are achieved. In this study, a laser-induced breakdown spectroscopy (LIBS) system was assessed as a fast validation tool for trace element premixes. LIBS is a promising emission spectroscopic technique for elemental analysis, which offers real-time analyses, little to no sample preparation and ease of use. LIBS was employed for copper and iron determinations of premix samples ranging approximately from 0 to 120mg/kg Cu/1640mg/kg Fe. LIBS spectra are affected by several parameters, hindering subsequent quantitative analyses. This work aimed at testing three matrix-matched calibration approaches (simple-linear regression, multi-linear regression and partial least squares regression (PLS)) as means for precision and accuracy enhancement of LIBS quantitative analysis. All calibration models were first developed using a training set and then validated with an independent test set. PLS yielded the best results. For instance, the PLS model for copper provided a coefficient of determination (R2) of 0.995 and a root mean square error of prediction (RMSEP) of 14mg/kg. Furthermore, LIBS was employed to penetrate through the samples by repetitively measuring the same spot. Consequently, LIBS spectra can be obtained as a function of sample layers. This information was used to explore whether measuring deeper into the sample could reduce possible surface-contaminant effects and provide better quantifications

Laser-induced breakdown spectroscopy (LIBS) for food analysis: A review

Background Laser-induced breakdown spectroscopy (LIBS) is an atomic emission spectroscopic technique which uses a focused pulsed laser beam to generate plasma from the material. The plasma contains atoms, ions and free electrons which emit electromagnetic radiation as the plasma cools down. The emitted light is resolved by a spectrometer to form a spectrum. Recently, LIBS has become an emerging analytical technique for characterisation and identification of materials; its multi-elemental analysis, fast response, remote sensing, little to no sample preparation, low running cost and ease of use make LIBS a promising technique for the food sector. Scope and approach The present article reviews the feasibility of LIBS for food analysis. It presents recent progress and applications of LIBS as an efficient and reagent-free, at-line tool capable of replacing traditional time-consuming analytical methods for assessing the quality and composition of food products. An overview of LIBS fundamentals, instrumentation and statistical data analysis is also provided. Key findings and conclusions Although LIBS technology shows many advantages, challenges remain in terms of sample preparation, matrix effects, spectral pre-processing, model calibration and instrument development

Quantification of copper content with laser induced breakdown spectroscopy as a potential indicator of offal adulteration in beef

Laser induced breakdown spectroscopy (LIBS) is an emerging technique in the field of food analysis which provides various advantages such as minimal sample preparation, chemical free, rapid detection, provision of spatial information and portability. In this study, LIBS was employed for quantitative analysis of copper content in minced beef samples spiked with beef liver over three independent batches. Copper content was determined with graphite furnace atomic absorption spectroscopy (GFAAS) in order to obtain reference values for modelling. Partial least square regression (PLSR) was performed to build a calibration and validation model. A calibration model with a high Rcv2 of 0.85 and a RMSECV of 43.5ppm was obtained, confirming a good fit for the model. The validation model showed a good prediction accuracy with a high Rp2 of 0.85 and RMSEP of 36.8ppm. Moreover, on a further study to evaluate the spatial capabilities, LIBS was able to successfully map copper content within a pellet, indicating the suitability of LIBS to provide spatial information and therefore potential use on heterogeneous samples. Overall, it can be concluded that LIBS combined with chemometrics demonstrates potential as a quality monitoring tool for the meat processing industry