Maria Markiewicz-Keszycka

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.

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.

NIR spectrophotometry with integrated beam splitter as a process analytical technology for meat composition analysis

This study aims at evaluating the potential of a multipoint NIR spectrophotometer system based on a Fabry–Perot interferometer, which incorporates a beam splitter, combined with a four point photodiode array detector and collimated light for performing on-line analysis of beef composition. Additionally it also aims at analysing the spectral information obtained with the baseline correction setting and compares it to the information obtained using a conventional approach. The system was employed to spatially predict the composition of fat trimmings of mixed minced beef samples at varied path lengths (1, 1.5 and 4 cm). The systems performance was tested in two optional modes; (a) without baseline correction adjustment and (b) with baseline correction adjustment. Both measuring modes of the spectrophotometer demonstrated individual advantages in particular situations; the first situation evaluated the simultaneous analysis of different samples set at different path lengths per probe, whereas a second situation focused on sudden changes of path lengths of the same sample per probe during a single analysis. Partial least squares regression (PLSR) was employed to establish the quantitative relationship between the spectral data and its proximate analysis values. Overall results showed good predictions for all the chemical attributes. It was concluded from the results that a baseline correction adjustment setting is needed when sudden changes in the effective path length occur, while in a case where similar path lengths are encountered, both modes could be used, obtaining good and similar performances.

Laser-induced breakdown spectroscopy (LIBS) for rapid analysis of ash, potassium and magnesium in gluten free flours

Gluten free (GF) diets are prone to mineral deficiency, thus effective monitoring of the elemental composition of GF products is important to ensure a balanced micronutrient diet. The objective of this study was to test the potential of laser-induced breakdown spectroscopy (LIBS) analysis combined with chemometrics for at-line monitoring of ash, potassium and magnesium content of GF flours: tapioca, potato, maize, buckwheat, brown rice and a GF flour mixture. Concentrations of ash, potassium and magnesium were determined with reference methods and LIBS. PCA analysis was performed and presented the potential for discrimination of the six GF flours. For the quantification analysis PLSR models were developed; R2cal were 0.99 for magnesium and potassium and 0.97 for ash. The study revealed that LIBS combined with chemometrics is a convenient method to quantify concentrations of ash, potassium and magnesium and present the potential to classify different types of flours.

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.

Multipoint NIR spectroscopy for simultaneous analyses of dairy products – Part B: Quantification:

This article constitutes the second part of the study multipoint NIR spectroscopy for simultaneous analyses of dairy products. The overall purpose was to assess the suitability of a multipoint NIR approach as an on/in-line tool for simultaneous monitoring of various quality control parameters. In this part, a multipoint NIR system capable of recording 4 spectra concurrently was tested for simultaneous casein determinations of casein-lactose blends. To this end, spectral acquisition was performed so that two sample blends were scanned at a time. Evaluation of the concurrently-recorded spectra together with the partial least squares (PLS) results demonstrated that the system holds potential for simultaneous compositional analysis of dairy powders.

Developments and Challenges in Online NIR Spectroscopy for Meat Processing

Meat and meat products are popular foods due to their balanced nutritional nature and their availability in a variety of forms. In recent years, due to an increase in the consumer awareness regarding product quality and authenticity of food, rapid and effective quality control systems have been sought by meat industries. Near-Infrared (NIR) spectroscopy has been identified as a fast and cost-effective tool for estimating various meat quality parameters as well as detecting adulteration. This review focusses on the on/inline application of single and multiprobe NIR spectroscopy for the analysis of meat and meat products starting from the year 1996 to 2017. The article gives a brief description about the theory of NIR spectroscopy followed by its application for meat and meat products analysis. A detailed discussion is provided on the various studies regarding applications of NIR spectroscopy and specifically for on/inline monitoring along with their advantages and disadvantages. Additionally, a brief description has been given about the various chemometric techniques utilized in the mentioned studies. Finally, it discusses challenges encountered and future prospects of the technology. It is concluded that, advancements in the fields of NIR spectroscopy and chemometrics have immensely increased the potential of the technology as a reliable on/inline monitoring tool for the meat industry.

Evaluating the Performance of Collimated Light for near Infrared Analysis of Minced Beef Samples

I n the last few years, near infrared (NIR) spectroscopy has found its place as a fast and valuable tool for quality monitoring in the food industry. NIR spectroscopy provides many advantages such as being fast, suitable for on/in-line monitoring, requiring little or no sample preparation, nondestructive, non-contact and more in comparison to traditional methods (proximate analysis, high-performance liquid chromatography, gas chromatography). Current NIR systems essentially use a tungsten halogen lamp as a light source. Acquiring a good NIR reflectance spectrum requires proper illumination of the sample and a sufficient amount of diffusively reflected light reaching the detector. In the case of NIR spectrophotometers employing fibreoptic probes, it is important to minimise the loss of incident and reflected light travelling through the fibres in order to attain a good signal. Loss of light when it travels through one end of the fibre to the other is termed attenuation. Attenuation is affected by various factors such as absorption, scattering, dispersion and bending. Absorption is largely related to the fibre material, while bending occurs due to physical stress on the fibre. Temperature and humidity also affect the fibre performance depending on the material. The amount of diffusively reflected light from the sample going back to the detector largely depends on the distance between the sample and the probe (stand-off) and the fibre-optic material. A typical fibre-optic reflectance probe works at stand-off distances in the range of millimetres. The use of collimators allows stand-off distances in the range of centimetres and thus enhances the non-contact nature of the technology. The current study aims at evaluating the performance of a collimator–probe setup in terms of the reflected light signal received at different stand-off distances in relation to spectral signatures obtained for a calibration standard and minced beef samples.

Multipoint near infrared spectroscopy for simultaneous analyses of dairy ingredients. Part A: characterisation

D uring recent decades, near infrared (NIR) spectroscopy has been widely recognised as a well-qualified technique for food quality assessments. NIR spectroscopy is rapid, non-destructive and generally requires only minimal sample preparation. These features make the technology suitable for on/in-line applications. In fact, current challenges are to adapt and attach NIR systems to production lines to facilitate continuous process monitoring. The use of fibre-optic NIR sensors allows signal transmission between the measuring point and the spectrophotometer over large distances, offering the possibility of in-line and real-time measurements with only the sensor in close proximity to the production line. Furthermore, NIR systems equipped with multiple fibre-optic sensors facilitate recording of spectra from different locations in the processing operation. Thus, a feature of interest is the capability of NIR systems to collect multiple spectra simultaneously. Concurrent measurement gives the means to monitor key quality control parameters from different points/stages of a process. In this work, we present a multipoint NIR system equipped with four NIR reflectance probes. The system is based on a Fabry– Perot interferometer, by which the recordings are conducted concurrently rather than consecutively as in the “quasi-simultaneous” multipoint systems which involve fibre switching or use of multiple spectrophotometers. The aim of the study was to show the system’s reliability by recording spectra from two different dairy ingredients simultaneously, and hence demonstrate the independence of each probe and the feasibility of providing qualitative information from various locations of a manufacturing process.