Application of Laser Spectrochemical Analytical Techniques to Follow Up Spoilage of White Meat in Chicken

Adulteration Detection and Quantification in Olive Oil Using Excitation-Emission Matrix Fluorescence Spectroscopy and Chemometrics

This research investigates the use of excitation-emission matrix fluorescence (EEMF) in conjunction with chemometric models to rapidly identify and quantify adulteration in olive oil, a critical concern where sample availability is limited. Adulteration is simulated by blending soybean, peanut, and linseed oils into olive oil, creating diverse adulterated samples. Principal component analysis (PCA) was applied to the EEMF spectral data as an initial exploratory measure to cluster and differentiate adulterated samples. Spatial clustering enabled vivid visualization of the variations and trends in the spectra. The novel application of parallel factor analysis (PARAFAC) for data decomposition in this paper focuses on unraveling correlations between the decomposed components and the actual adulterated components, which offers a novel perspective for accurately quantifying adulteration levels. Additionally, a comparative analysis was conducted between the PCA and PARAFAC methodologies. Our study not only unveils a new avenue for the quantitative analysis of adulterants in olive oil through spectral detection but also highlights the potential for applying these insights in practical, real-world scenarios, thereby enhancing detection capabilities for various edible oil samples. This promises to improve the detection of adulteration across a range of edible oil samples, offering significant contributions to food safety and quality assurance.

Investigating the effect of changing the substrate material analyzed by laser-induced breakdown spectroscopy on the antenna performance

Miniaturized microstrip antennas are efficiently utilized in MICS band wearable and implantable medical applications. However, the properties of the materials employed for antenna fabrication influence its resultant parameters and play a vital role in its performance. Rogers have been widely used as a substrate material in various antenna designs. In this work, a proof of concept study has been conducted to determine how altering the substrate used in antenna construction affects antenna performance. Using the laser-induced breakdown spectroscopy (LIBS) approach, the elements present in the two distinct substrate raw materials were compared to investigate potential effects on the antenna's performance. Given their accessibility and widespread use, two types of Rogers' substrates, RO 3210 and RO 4003, were selected. Furthermore, two identical antenna designs were modeled and fabricated using the two substrate materials. The reflection coefficient (S11) and other antenna parameters were determined and compared. Moreover, the recorded LIBS spectra were evaluated using principle component analysis and partial least square regression techniques. The LIBS spectra showed different copper and iron contents between the two Rogers (i.e., other dielectric properties), leading to a frequency shift. Additionally, impurities in the fabricated material increase the possible losses. Consequently, the elemental contents of the utilized Rogers control the antenna's performance and can ensure its safety in wearable and implant applications.

Post-heating Fluorescence-based Alteration and Adulteration Detection of Extra Virgin Olive Oil

Olive oils are more expensive compared with other vegetable oils. Therefore, adulterating such expensive oil is prevalent. The traditional methods for olive oil adulteration detection are complex and require pre-analysis sample preparation. Therefore, simple and precise alternative techniques are required. In the present study, the Laser-induced fluorescence (LIF) technique was implemented for detecting alteration and adulteration of olive oil mixed with sunflower or corn oil based on the post-heating emission characteristics. Diode-pumped solid-state laser (DPSS, λ = 405 nm) was employed for excitation and the fluorescence emission was detected via an optical fiber connected to a compact spectrometer. The obtained results revealed alterations in the recorded chlorophyll peak intensity due to olive oil heating and adulteration. The correlation of the experimental measurements was evaluated via partial least-squares regression (PLSR) with an R-squared value of 0.95. Moreover, the system performance was evaluated using receiver operating characteristics (ROC) with a maximum sensitivity of 93%.

Reflection-enhanced laser-induced fluorescence spectroscopy to improve the analytical sensitivity in liquids

The current work demonstrates a novel approach to enhancing the analytical sensitivity of the laser-induced fluorescence (LIF) technique in liquids. An increase in the fluorescence spectral band intensity of about sixfold compared to the conventional LIF has been achieved. Such betterment has been accomplished by having the fluorophore liquid in a cuvette having a reflecting mirror-like side facing the exciting incident laser beam. The silvered or aluminized reflecting side of the cuvette was tested. The pilot test of the proposed cuvette was performed using an excitation laser light of 405 nm wavelength and five mW average power on chlorophyll-a (Chl-a) samples of different concentrations. As a result, a pronounced improvement in the Chl-a fluorescence spectral band intensity is achieved. Such a novel approach, the reflection-enhanced laser-induced fluorescence (RELIF), has been used to analyze six Egyptian brands of extra virgin olive oil (EVOO). Compared to the LIF measurement results on the same EVOO, the RELIF was superior in terms of the fluorescence-spectrum intensity enhancement factor. Both Ag and Al coatings of the cuvette revealed similar results. Statistical analysis of the measured fluorescence spectra via the partial least square regression (PLSR) method for LIF and RELIF revealed a higher coefficient of determination R² for both RELIF measurements (with silver and aluminum coating) than for LIF. The proposed novel RELIF approach can be utilized for other fluorophore liquids at higher analytical sensitivity than conventional LIF. On the other hand, the RELIF technique is straightforward, cost-effective, and does not complicate the traditional LIF setup.

Adaptive optics-based wavefront-enhanced laser-induced fluorescence (WELIF) for improved analytical performance

The current study proposes a novel optical approach based on an adaptive optics (AO) system to enhance the fluorescence intensity in the laser-induced fluorescence (LIF) technique. The proposed method, wavefront-enhanced LIF (WELIF), relies mainly on compensating for the aberrations arising from the excitation-laser wavefront. The AO system consists of an active correction element (deformable mirror (DM)) integrated with a Shack-Hartmann wavefront sensor (SHWFS). The overall system operates in a closed-loop configuration to compensate for the laser beam aberrations in real time. The performance of the interaction of the aberration-free excitation laser beam with solid samples, e.g., bone, leaf, polymer sheet, and with liquid samples, e.g., extra virgin olive oil (EVOO), showed a pronounced improvement in the fluorescence peak intensity. As an analytical application example, detailed WELIF measurements have been performed on five EVOO brands to demonstrate the validity of the new approach. Furthermore, the effectiveness of the proposed system was evaluated by measuring the enhancement factor, i.e., the ratio between the fluorescence peak intensity after aberration compensation (AC) relative to the initial peak intensity before aberration compensation (BC). The results reveal that the fluorescence peak intensities have been enhanced with ranges from 20% to 98% after compensation (AC). Besides, the results were statistically assessed based on the receiver operator characteristic (ROC) curve (84% sensitivity AC and 82% BC) and partial least squares regression, PLSR, with a 0.94 coefficient of determination AC compared to 0.90 BC.

Utilization of laser-induced breakdown spectroscopy, with principal component analysis and artificial neural networks in revealing adulteration of similarly looking fish fillets

Fish is an essential source of many nutrients necessary for human health. However, the deliberate mislabeling of similar fish fillet types is common in markets to make use of the relatively high price difference. This is a type of explicit food adulteration. In the present work, spectrochemical analysis and chemometric methods are adopted to disclose this type of fish species cheating. Laser-induced breakdown spectroscopy (LIBS) was utilized to differentiate between the fillets of the low-priced tilapia and the expensive Nile perch. Furthermore, the acquired spectroscopic data were analyzed statistically using principal component analysis (PCA) and artificial neural network (ANN) showing good discrimination in the PCA score plot and a 99% classification accuracy rate of the implemented ANN model. The recorded spectra of the two fish indicated that tilapia has a higher fat content than Nile perch, as evidenced by higher CN and C2 bands and an atomic line at 247.8 nm in its spectrum. The obtained results demonstrated the potential of using LIBS as a simple, fast, and cost-effective analytical technique, combined with statistical analysis for the decisive discrimination between fish fillet species.

Optical Characterization of Biological Tissues Based on Fluorescence, Absorption, and Scattering Properties

Optical diagnostics methods are significantly appealing in biological applications since they are non-destructive, safe, and minimally invasive. Laser-induced fluorescence is a promising optical spectrochemical analytical technique widely employed for tissue classification through molecular analysis of the studied samples after excitation with appropriate short-wavelength laser light. On the other hand, diffuse optics techniques are used for tissue monitoring and differentiation based on their absorption and scattering characteristics in the red to the near-infrared spectra. Therefore, it is strongly foreseen to obtain promising results by combining these techniques. In the present work, tissues under different conditions (hydrated/dry skin and native/boiled adipose fat) were distinguished according to their fluorescence emission, absorption, and scattering properties. The selected tissues' optical absorption and scattering parameters were determined via Kubelka-Munk mathematical model according to the experimental tissue reflectance and transmittance measurements. Such measurements were obtained using an optical configuration of integrating sphere and spectrometer at different laser wavelengths (808, 830, and 980 nm). Moreover, the diffusion equation was solved for the fluence rate at the sample surface using the finite element method. Furthermore, the accuracy of the obtained spectroscopic measurements was evaluated using partial least squares regression statistical analysis with 0.87 and 0.89 R-squared values for skin and adipose fat, respectively.

Utilization of gold nanoparticles for the detection of squamous cell carcinoma of the tongue based on laser-induced fluorescence and diffuse reflectance characteristics: an in vitro study

Squamous cell carcinoma is a very common type of oral cancer that affects the health of people with an unacceptably high mortality rate attributed to the difficulties in detecting the disease at an early stage. Therefore, effective techniques for early diagnosis and effective therapy of oral cancer are necessary. In the present study, we exploit the ability of gold nanoparticles (AuNPs) to undergo coupled surface plasmon resonance when closely spaced to improve diagnosing squamous cell carcinoma of the tongue. The prepared AuNPs are characterized by UV-VIS spectroscopy, dynamic light scattering, Fourier transform infrared spectroscopy, and transmission electron microscopy. The size of the prepared AuNPs is 12 ± 2 nm with narrow size distributions and exhibited high stability with a zeta potential of - 16.5 mV. The light fluorescence of the normal and cancer cells is recorded before and after NP addition using a spectrometer upon excitation by 405-nm laser irradiation. Furthermore, the light reflectance of the examined samples is measured at different laser wavelengths (red to NIR region). The obtained results show that the cancer cells mixed with AuNPs produce a higher fluorescence peak at 489.2 nm than the cancer cells without AuNPs. Moreover, the optical diffuse reflectance analyses reveal that the addition of AuNPs enhances cancer detection especially at the 635-nm irradiation with sensitivity (94%), specificity (87%), and overall accuracy (91%).

Applications of Fluorescence Spectroscopy, RGB- and MultiSpectral Imaging for Quality Determinations of White Meat: A Review

Fluorescence spectroscopy, color imaging and multispectral imaging (MSI) have emerged as effective analytical methods for the non-destructive detection of quality attributes of various white meat products such as fish, shrimp, chicken, duck and goose. Based on machine learning and convolutional neural network, these techniques can not only be used to determine the freshness and category of white meat through imaging and analysis, but can also be used to detect various harmful substances in meat products to prevent stale and spoiled meat from entering the market and causing harm to consumer health and even the ecosystem. The development of quality inspection systems based on such techniques to measure and classify white meat quality parameters will help improve the productivity and economic efficiency of the meat industry, as well as the health of consumers. Herein, a comprehensive review and discussion of the literature on fluorescence spectroscopy, color imaging and MSI is presented. The principles of these three techniques, the quality analysis models selected and the research results of non-destructive determinations of white meat quality over the last decade or so are analyzed and summarized. The review is conducted in this highly practical research field in order to provide information for future research directions. The conclusions detail how these efficient and convenient imaging and analytical techniques can be used for non-destructive quality evaluation of white meat in the laboratory and in industry.

Back-reflection-enhanced laser-induced breakdown spectroscopy (BRELIBS) on transparent materials: Application on archaeological glass

A straightforward and simple method has been proposed in the current work to improve the signal-to-noise ratio of the LIBS spectrum of transparent samples. The idea is to benefit from a highly polished metallic reflector in direct contact with the rear surface of the transparent target. Copper and silver metals have been used as reflectors for the focused laser beam and force it to pass through the plasma plume induced initially onto the front surface of the target. The reflected laser beam reheats the plasma plume increasing the intensity of the light emitted from it. In such a case, the obtained LIBS spectrum accomplishes a pronounced increase in the signal-to-noise ratio compared to the spectrum obtained without a reflector. The new amendment of the LIBS technique setup has been exploited for the elemental analysis of colored glass fragments from archaeological Egyptian Synagogue windows. Quantitative analysis of the samples using the calibration-free LIBS (CF-LIBS) approach has been performed. The results depicted three-to four-fold enhancement in the spectral lines' intensity depending on the glass color and thickness. The results have been validated by the quantitative analysis of the same samples via the Energy-Dispersive X-ray spectroscopy (EDX). The CF-BRELIBS results were in pronounced agreement with that of the EDX. The back-reflection-enhanced laser-induced breakdown spectroscopy (BRELIBS) can be applied to analyze numerous transparent target types such as different glass types, gemstone, plastics, polymers, etc.

Preliminary investigation of the use of Raman spectroscopy to predict beef spoilage in different types of packaging

In this study, pH, meat color analysis, microbial counts and Raman spectroscopic data were obtained from beef steaks stored at 4 °C for up to 21 days using two different packaging methods: vacuum (VP) and modified atmosphere packaging (MAP). Models using partial least square regression (PLSR), indicated that Raman spectroscopy was able to predict total viable counts (TVC) and lactic acid bacteria (LAB) measured at 21d post mortem (TVC in VP: R²_cv = 0.99, RMSEP = 0.61; TVC in MAP: R²_cv = 0.90, RMSEP = 0.38; LAB in VP: R²_cv = 0.99, RMSEP = 0.54; LAB in MAP: R²_cv = 0.75, RMSEP = 0.60). The results of this study demonstrate that Raman spectroscopy may have potential for the rapid determination of meat spoilage.

Evaluation of proteins in sheep colostrum via laser-induced breakdown spectroscopy and multivariate analysis

Colostrum is essential to guarantee normal and healthy feeding in newborn ruminants during the first hours. In the present work, Laser-Induced Breakdown Spectroscopy (LIBS), as a spectrochemical analytical technique, and principal component analysis (PCA) as a multivariate analysis method were used to evaluate colostrum compared to mature milk of sheep to plan the nutritional strategies for newly born lambs. Samples of colostrum have been collected from thirty-three Barki ewes. The sheep were milked every 12 h three times after birth, the fourth sample of mature milk is taken from milking in the 7th day postpartum. The spectrochemical analytical results depicted that the intensities of CN and C₂ spectral bands, and C 247.86 nm atomic line (as an indicator for protein content in LIBS spectra) are higher in colostrum than that in milk. This relationship has been confirmed by measuring the total protein in the same samples conventionally. The relation between calcium and protein percentage has also been demonstrated. Moreover, it has been shown that the higher is the CN bands' intensity the lower is the bacteria count in colostrum samples, owing to the high levels of lactoferrin with its antibacterial effect. The qualitative analysis of LIBS data using PCA led to a pronounced discrimination between colostrum and mature milk. The present study demonstrates that it is, in principle, possible to make use of the analytical and chemometric results in dairy farms to evaluate sheep colostrum to manage the nutritional strategies for the lambs.