Antimicrobial Effects and Antioxidant Activity of Myrtus communis L. Essential Oil in Beef Stored under Different Packaging Conditions.

The aim of this study was to assess the antimicrobial effects of myrtle (Myrtus communis L.) essential oil (EO) on pathogenic (E. coli O157:H7 NCTC 12900; Listeria monocytogenes ATCC BAA-679) and spoilage microbiota in beef and determine its minimum inhibitory concentration (MIC) and antioxidant activity. The behavior of LAB, Enterobacteriaceae, Pseudomonas spp., and fungi, as well as total mesophilic (TM) and total psychotropic (TP) counts, in beef samples, was analyzed during storage at 2 and 8 °C in two different packaging systems (aerobiosis and vacuum). Leaves of myrtle were dried, its EO was extracted by hydrodistillation using a Clevenger-type apparatus, and the chemical composition was determined using chromatographical techniques. The major compounds obtained were myrtenyl acetate (15.5%), ß-linalool (12.3%), 1,8-cineole (eucalyptol; 9.9%), geranyl acetate (7.4%), limonene (6.2%), α-pinene (4.4%), linalyl o-aminobenzoate (5.8%), α-terpineol (2.7%), and myrtenol (1.2%). Myrtle EO presented a MIC of 25 µL/mL for E. coli O157:H7 NCTC 12900, E. coli, Listeria monocytogenes ATCC BAA-679, Enterobacteriaceae, and E. coli O157:H7 ATCC 35150 and 50µL/mL for Pseudomonas spp. The samples packed in aerobiosis had higher counts of deteriorative microorganisms than samples packed under vacuum, and samples with myrtle EO presented the lowest microbial contents, indicating good antimicrobial activity in beef samples. Myrtle EO is a viable natural alternative to eliminate or reduce the pathogenic and deteriorative microorganisms of meat, preventing their growth and enhancing meat safety.

Refractometric sensitivity of Bloch surface waves: perturbation theory calculation and experimental validation.

The sensitivity of one-dimensional Bloch surface wave (BSW) sensors to external refractive index variations using Kretschmann's configuration is calculated analytically by employing first-order perturbation theory for both TE and TM modes. This approach is then validated by comparison with both transfer matrix method simulations and experimental results for a chosen photonic crystal structure. Experimental sensitivities of (8.4±0.2)×102 and (8.4±0.4)×102 nm/RIU were obtained for the TE and TM BSW modes, corresponding to errors of 0.02% and 4%, respectively, when comparing with the perturbation theory approach. These results provide interesting insights into photonic crystal design for Bloch surface wave sensing by casting light into the important parameters related with sensor performance.

Spectral Analysis Methods for Improved Resolution and Sensitivity: Enhancing SPR and LSPR Optical Fiber Sensing.

Biochemical-chemical sensing with plasmonic sensors is widely performed by tracking the responses of surface plasmonic resonance peaks to changes in the medium. Interestingly, consistent sensitivity and resolution improvements have been demonstrated for gold nanoparticles by analyzing other spectral features, such as spectral inflection points or peak curvatures. Nevertheless, such studies were only conducted on planar platforms and were restricted to gold nanoparticles. In this work, such methodologies are explored and expanded to plasmonic optical fibers. Thus, we study-experimentally and theoretically-the optical responses of optical fiber-doped gold or silver nanospheres and optical fibers coated with continuous gold or silver thin films. Both experimental and numerical results are analyzed with differentiation methods, using total variation regularization to effectively minimize noise amplification propagation. Consistent resolution improvements of up to 2.2× for both types of plasmonic fibers are found, demonstrating that deploying such analysis with any plasmonic optical fiber sensors can lead to sensing resolution improvements.

Consumer Knowledge about Food Labeling and Fraud.

Food fraud is a growing problem and happens in many ways including mislabelling. Since lack of consumers' knowledge about mandatory food labeling information and different types of food fraud may impact public health, the present work assesses consumers' knowledge about these issues. Principal component analysis was performed to obtain a smaller number of uncorrelated factors regarding the usefulness and confidence of information displayed in food labels and the perception of food fraud. Results indicated that information displayed in food labels is useful, however the way it is presented may decrease consumer interest and understanding. Regarding respondents' confidence in foodstuffs, over half of them stated that information provided in food labels is reliable. However, a lack of confidence about food composition is observed in those processed foodstuffs such as meat products. Food fraud is recognized by more than half of respondents with a higher perception of those practices that imply a risk to public health than those related to economic motivation. Age and education of consumers influenced the perception of the information displayed in the food labels, their confidence and knowledge about food fraud. Implementation of education programs to increase consumer knowledge about food labelling and fraud is essential. Respondents' perception results could be use as guidelines by the food industry to improve food label design in order to enhance consumer understanding.

Biosensors for Biogenic Amines: A Review.

Biogenic amines (BAs) are well-known biomolecules, mostly for their toxic and carcinogenic effects. Commonly, they are used as an indicator of quality preservation in food and beverages since their presence in higher concentrations is associated with poor quality. With respect to BA's metabolic pathways, time plays a crucial factor in their formation. They are mainly formed by microbial decarboxylation of amino acids, which is closely related to food deterioration, therefore, making them unfit for human consumption. Pathogenic microorganisms grow in food without any noticeable change in odor, appearance, or taste, thus, they can reach toxic concentrations. The present review provides an overview of the most recent literature on BAs with special emphasis on food matrixes, including a description of the typical BA assay formats, along with its general structure, according to the biorecognition elements used (enzymes, nucleic acids, whole cells, and antibodies). The extensive and significant amount of research that has been done to the investigation of biorecognition elements, transducers, and their integration in biosensors, over the years has been reviewed.

Low-Cost Interrogation System for Long-Period Fiber Gratings Applied to Remote Sensing.

We present a portable and low-cost system for interrogation of long-period fiber gratings (LPFGs) costing around a 30th of the price of a typical setup using an optical spectrum analyzer and a broadband light source. The unit is capable of performing real-time monitoring or as a stand-alone data-logger. The proposed technique uses three thermally modulated fiber-coupled laser diodes, sweeping a few nanometers around their central wavelength. The light signal is then modulated by the LPFG and its intensity is acquired by a single photo-detector. Through curve-fitting algorithms the sensor transmission spectrum is reconstructed. Testing and validation were accomplished by inducing variations in the spectral features of an LPFG through changes either in external air temperature from 22 to 425 °C or in refractive index (RI) of the surrounding medium from 1.3000 to 1.4240. A dynamic resolution between 3.5 and 1.9 °C was achieved, in temperatures from 125 to 325 °C. In RI measurements, maximum wavelength and optical power deviations of 2.75 nm and 2.86 dB, respectively, were obtained in the range from 1530 to 1570 nm. The worse RI resolution obtained was 3.47 × 10 - 3 . The interrogation platform was then applied in the detection of iron corrosion, expressing wavelength peak values within 1.12 nm from the real value in the region between 1530 and 1570 nm.

Applying Fourier Transform Mid Infrared Spectroscopy to Detect the Adulteration of Salmo salar with Oncorhynchus mykiss.

The aim of this study was to evaluate the potential of Fourier transform infrared (FTIR) spectroscopy coupled with chemometric methods to detect fish adulteration. Muscles of Atlantic salmon (Salmo salar) (SS) and Salmon trout (Onconrhynchus mykiss) (OM) muscles were mixed in different percentages and transformed into mini-burgers. These were stored at 3 °C, then examined at 0, 72, 160, and 240 h for deteriorative microorganisms. Mini-burgers was submitted to Soxhlet extraction, following which lipid extracts were analyzed by FTIR. The principal component analysis (PCA) described the studied adulteration using four principal components with an explained variance of 95.60%. PCA showed that the absorbance in the spectral region from 721, 1097, 1370, 1464, 1655, 2805, to 2935, 3009 cm−1 may be attributed to biochemical fingerprints related to differences between SS and OM. The partial least squares regression (PLS-R) predicted the presence/absence of adulteration in fish samples of an external set with high accuracy. The proposed methods have the advantage of allowing quick measurements, despite the storage time of the adulterated fish. FTIR combined with chemometrics showed that a methodology to identify the adulteration of SS with OM can be established, even when stored for different periods of time.

Plasmonic Optical Fiber Sensor Based on Double Step Growth of Gold Nano-Islands.

It is presented the fabrication and characterization of optical fiber sensors for refractive index measurement based on localized surface plasmon resonance (LSPR) with gold nano-islands obtained by single and by repeated thermal dewetting of gold thin films. Thin films of gold deposited on silica (SiO2) substrates and produced by different experimental conditions were analyzed by Scanning Electron Microscope/Dispersive X-ray Spectroscopy (SEM/EDS) and optical means, allowing identifying and characterizing the formation of nano-islands. The wavelength shift sensitivity to the surrounding refractive index of sensors produced by single and by repeated dewetting is compared. While for the single step dewetting, a wavelength shift sensitivity of ~60 nm/RIU was calculated, for the repeated dewetting, a value of ~186 nm/RIU was obtained, an increase of more than three times. It is expected that through changing the fabrication parameters and using other fiber sensor geometries, higher sensitivities may be achieved, allowing, in addition, for the possibility of tuning the plasmonic frequency.

A chemometrics approach applied to Fourier transform infrared spectroscopy (FTIR) for monitoring the spoilage of fresh salmon (Salmo salar) stored under modified atmospheres.

The aim of this work was to investigate the potential of Fourier transform infrared spectroscopy (FTIR) to detect and predict the bacterial load of salmon fillets (Salmo salar) stored at 3, 8 and 30°C under three packaging conditions: air packaging (AP) and two modified atmospheres constituted by a mixture of 50%N2/40%CO2/10%O2 with lemon juice (MAPL) and without lemon juice (MAP). Fresh salmon samples were periodically examined for total viable counts (TVC), specific spoilage organisms (SSO) counts, pH, FTIR and sensory assessment of freshness. Principal components analysis (PCA) allowed identification of the wavenumbers potentially correlated with the spoilage process. Linear discriminant analysis (LDA) of infrared spectral data was performed to support sensory data and to accurately identify samples freshness. The effect of the packaging atmospheres was assessed by microbial enumeration and LDA was used to determine sample packaging from the measured infrared spectra. It was verified that modified atmospheres can decrease significantly the bacterial load of fresh salmon. Lemon juice combined with MAP showed a more pronounced delay in the growth of Brochothrix thermosphacta, Photobacterium phosphoreum, psychrotrophs and H2S producers. Partial least squares regression (PLS-R) allowed estimates of TVC and psychrotrophs, lactic acid bacteria, molds and yeasts, Brochothrix thermosphacta, Enterobacteriaceae, Pseudomonas spp. and H2S producer counts from the infrared spectral data. For TVC, the root mean square error of prediction (RMSEP) value was 0.78logcfug-1 for an external set of samples. According to the results, FTIR can be used as a reliable, accurate and fast method for real time freshness evaluation of salmon fillets stored under different temperatures and packaging atmospheres.

Short wavelength Raman spectroscopy applied to the discrimination and characterization of three cultivars of extra virgin olive oils in different maturation stages.

Extra virgin olive oils produced from three cultivars on different maturation stages were characterized using Raman spectroscopy. Chemometric methods (principal component analysis, discriminant analysis, principal component regression and partial least squares regression) applied to Raman spectral data were utilized to evaluate and quantify the statistical differences between cultivars and their ripening process. The models for predicting the peroxide value and free acidity of olive oils showed good calibration and prediction values and presented high coefficients of determination (>0.933). Both the R(2), and the correlation equations between the measured chemical parameters, and the values predicted by each approach are presented; these comprehend both PCR and PLS, used to assess SNV normalized Raman data, as well as first and second derivative of the spectra. This study demonstrates that a combination of Raman spectroscopy with multivariate analysis methods can be useful to predict rapidly olive oil chemical characteristics during the maturation process.

Discrimination and characterisation of extra virgin olive oils from three cultivars in different maturation stages using Fourier transform infrared spectroscopy in tandem with chemometrics.

A methodology based on Fourier transform infrared (FTIR) spectroscopy, combined with multivariate analysis methods, was applied in order to monitor extra virgin olive oils produced from three distinct cultivars on different maturation stages. For the first time, this kind of methodology is used for the simultaneous discrimination of the maturation stage, and different cultivars. Principal component analysis and discriminant analysis were utilised to create a model for the discrimination of olive oil samples. Partial least squares regression was employed to design calibration models for the determination of chemical parameters. The performance of these models was based on the multiple coefficient of determination (R(2)), the root mean square error of calibration (RMSEC) and root mean square error of cross validation (RMSECV). The prediction models for the chemical parameters resulted in a R(2) ranged from 0.93 to 0.99, a RMSEC ranged from 1% to 4% and a RMSECV from 2% to 5%. It has been shown that this kind of approach allows to distinguish the different cultivars, and to clearly discern the different maturation stages, in each one of these distinct cultivars. Furthermore, the results demonstrated that FTIR spectroscopy in tandem with chemometric techniques allows the creation of viable and accurate models, suitable for correlating the data collected by FTIR spectroscopy, with the chemical composition of the EVOOs, obtained by standard methods.