Effect of Non-thermal Atmospheric Plasma on Viability and Histamine-Producing Activity of Psychotrophic Bacteria in Mackerel Fillets.

Non-thermal atmospheric plasma (NTAP) has gained attention as a decontamination and shelf-life extension technology. In this study its effect on psychrotrophic histamine-producing bacteria (HPB) and histamine formation in fish stored at 0-5°C was evaluated. Mackerel filets were artificially inoculated with Morganella psychrotolerans and Photobacterium phosphoreum and exposed to NTAP to evaluate its effect on their viability and the histidine decarboxylase (HDC) activity in broth cultures and the accumulation of histamine in fish samples, stored on melting ice or at fridge temperature (5°C). NTAP treatment was made under wet conditions for 30 min, using a dielectric barrier discharge (DBD) reactor. The voltage output was characterized by a peak-to-peak value of 13.8 kV (fundamental frequency around 12.7 KHz). This treatment resulted in a significant reduction of the number of M. psychrotolerans and P. phosphoreum (≈3 log cfu/cm2) on skin samples that have been prewashed with surfactant (SDS) or SDS and lactic acid. A marked reduction of their histamine-producing potential was also observed in HDC broth incubated at either 20 or 5°C. Lower accumulation of histamine was observed in NTAP-treated mackerel filets that have been inoculated with M. psychrotolerans or P. phosphoreum and pre-washed with either normal saline or SDS solution (0.05% w/v) and stored at 5°C for 10 days. Mean histamine level in treated and control groups for the samples inoculated with either M. psychrotolerans or P. phosphoreum (≈5 log cfu/g) varied from 7 to 32 and from 49 to 66 µg/g, respectively. No synergistic effect of SDS was observed in the challenge test on meat samples. Any detectable amount of histamine was produced in the meat samples held at melting ice temperature (0-2°C) for 7 days. The effects of NTAP on the quality properties of mackerel's filets were negligible, whereas its effect on the psychrotrophic HPB might be useful when time and environmental conditions are challenging for the cool-keeping capacity throughout the transport/storage period.

Modelling Volume Change and Deformation in Food Products/Processes: An Overview.

Volume change and large deformation occur in different solid and semi-solid foods during processing, e.g., shrinkage of fruits and vegetables during drying and of meat during cooking, swelling of grains during hydration, and expansion of dough during baking and of snacks during extrusion and puffing. In addition, food is broken down during oral processing. Such phenomena are the result of complex and dynamic relationships between composition and structure of foods, and driving forces established by processes and operating conditions. In particular, water plays a key role as plasticizer, strongly influencing the state of amorphous materials via the glass transition and, thus, their mechanical properties. Therefore, it is important to improve the understanding about these complex phenomena and to develop useful prediction tools. For this aim, different modelling approaches have been applied in the food engineering field. The objective of this article is to provide a general (non-systematic) review of recent (2005-2021) and relevant works regarding the modelling and simulation of volume change and large deformation in various food products/processes. Empirical- and physics-based models are considered, as well as different driving forces for deformation, in order to identify common bottlenecks and challenges in food engineering applications.

Fatty Acid Ethyl Esters in Virgin Olive Oils: In-House Validation of a Revised Method.

The content of fatty acid ethyl esters (FAEEs) is one of the quality parameters to define if an olive oil can be classified as extra virgin as these compounds are considered markers for virgin olive oils obtained from poor-quality olives. In addition, FAEEs can also be indirect markers to detect soft deodorization treatment. In this study, an off-line HPLC-GC-FID method for determination of FAEEs is presented, revising the preparative step and the GC injector required by the official method (EU Reg. 61/2011). After optimization, the method was validated in-house by analyzing several parameters (linearity, limit of detection LOD, limit of quantification LOQ, robustness, recovery, precision, and accuracy) to determine its effectiveness. Linearity was measured in the 2.5-50 mg/L range; furthermore, intra-day and inter-day precision values were lower than 15%, while the LOD and LOQ were lower than 1 and 1.5 mg/kg, respectively, for all compounds considered. The main advantages of this revised protocol are: (i) significant reduction in time and solvents needed for each analytical determination; (ii) application of HPLC as an alternative to traditional LC, carried with manually packed glass columns, thus simplifying the separation step.

Flash Gas Chromatography in Tandem with Chemometrics: A Rapid Screening Tool for Quality Grades of Virgin Olive Oils.

This research aims to develop a classification model based on untargeted elaboration of volatile fraction fingerprints of virgin olive oils (n = 331) analyzed by flash gas chromatography to predict the commercial category of samples (extra virgin olive oil, EVOO; virgin olive oil, VOO; lampante olive oil, LOO). The raw data related to volatile profiles were considered as independent variables, while the quality grades provided by sensory assessment were defined as a reference parameter. This data matrix was elaborated using the linear technique partial least squares-discriminant analysis (PLS-DA), applying, in sequence, two sequential classification models with two categories (EVOO vs. no-EVOO followed by VOO vs. LOO and LOO vs. no-LOO followed by VOO vs. EVOO). The results from this large set of samples provide satisfactory percentages of correctly classified samples, ranging from 72% to 85%, in external validation. This confirms the reliability of this approach in rapid screening of quality grades and that it represents a valid solution for supporting sensory panels, increasing the efficiency of the controls, and also applicable to the industrial sector.

An HS-GC-IMS Method for the Quality Classification of Virgin Olive Oils as Screening Support for the Panel Test.

Sensory evaluation, carried out by panel tests, is essential for quality classification of virgin olive oils (VOOs), but is time consuming and costly when many samples need to be assessed; sensory evaluation could be assisted by the application of screening methods. Rapid instrumental methods based on the analysis of volatile molecules might be considered interesting to assist the panel test through fast pre-classification of samples with a known level of probability, thus increasing the efficiency of quality control. With this objective, a headspace gas chromatography-ion mobility spectrometer (HS-GC-IMS) was used to analyze 198 commercial VOOs (extra virgin, virgin and lampante) by a semi-targeted approach. Different partial least squares-discriminant analysis (PLS-DA) chemometric models were then built by data matrices composed of 15 volatile compounds, which were previously selected as markers: a first approach was proposed to classify samples according to their quality grade and a second based on the presence of sensory defects. The performance (intra-day and inter-day repeatability, linearity) of the method was evaluated. The average percentages of correctly classified samples obtained from the two models were satisfactory, namely 77% (prediction of the quality grades) and 64% (prediction of the presence of three defects) in external validation, thus demonstrating that this easy-to-use screening instrumental approach is promising to support the work carried out by panel tests.

Glass transition of green and roasted coffee investigated by calorimetric and dielectric techniques.

Solid and liquid components coexist into glassy and amorphous structures of food complex matrixes. Both states admit movements, promoting physical modifications to a more thermodynamically stable system. Green and roasted coffee beans are principally characterized by a glassy structure that slowly evolves during storage. The aim of this study was to assess calorimetric and dielectric properties in combination, as a useful multi-analytical technique to improve the understanding of the motion mechanism of localized molecules. After equilibration at different water activities (aw) for the determination of sorption isotherms of green and roasted coffee, the glass transition temperature (Tg) of the samples has been measured by using differential scanning calorimetry (DSC). Increasing the aw from 0.155 to 0.512, the Tg shifted from 48.76 (±0.04) to 34.89 (±0.02) °C for green coffee and from 45.73 (±0.05) to 40.15 (±0.10) °C for the roasted one. The spectroscopic fingerprint of the matrix has been determined by dielectric measurements in terms of "gain" spectra (related to the imaginary part of permittivity). The maximum values of the determination coefficient (R2), obtained by linear correlation between spectral data and water activity or glass transition values for a specific frequency of the whole range (1.6 GHz-2.7 GHz), were 0.999 and 0.943 for green, and 0.997 R2 and 0.925 R2 for roasted coffee respectively.

Influence of an innovative and promising gas clarification process on the quality of stored extra virgin olive oils.

Filtration of extra virgin olive oil is a process that may improve preservation of the quality during storage. In the current study, different aliquots of extra virgin olive oils were subjected to filtration with a traditional filter press or an innovative patented alternative process of clarification by insufflating inert gas such as nitrogen and argon; all treated samples and, as control unfiltered ones, were stored for one year to evaluate the effects of these technologies on the quality of oil during shelf-life. Basic quality indexes, diglycerides, phenolics and volatiles, as well as the sensory characteristics of samples, were determined at 4 month intervals during storage. According to the volatile compounds, phenolics and sensory analysis, the novel technique had a beneficial effect on the storage of extra virgin olive oils; accordingly, this process could be exploited by the olive oil industry.

Freshness assessment of European hake (Merluccius merluccius) through the evaluation of eye chromatic and morphological characteristics.

The most commonly used method for fish freshness determination is the sensory inspection; alternative sensory methods such as the Quality Index Method (QIM), based on the significant sensory parameters of one specific species, have been recently suggested. Considering that most of the sensory parameters are based on chromatic and morphological visual impression, the set-up of an objective method using computer vision techniques is very promising. The objective of this research was to characterize the changes in eye chromatic and morphological characteristics of European hake (Merluccius merluccius) during 13 days of storage on ice, using a tailored computer vision technique and a 3D scanner. Results obtained by multivariate statistical analysis of the colour spectra of eye images and by the eye concavity index using a 3D scanner permitted to estimate fish unacceptability after 7 days of storage, in agreement with results obtained by QIM sensory analysis. Moreover, 1H NMR was used to evaluate the production of trimethylamine (TMA) and the Ki index, confirming a good correlation with eye chromatic and morphological features. This preliminary study showed the high potentiality of the developed method as a non-destructive technique for raw fish freshness characterization / prediction, being a promising approach to create a robust portable instrument for the evaluation of fish freshness in real transport and marketing conditions.

Analysis of oligomer proanthocyanidins in different barley genotypes using high-performance liquid chromatography-fluorescence detection-mass spectrometry and near-infrared methodologies.

Proanthocyanidins are a class of polyphenols present in many foodstuffs (i.e., tea, cocoa, berries, etc.) that may reduce the risk of several chronic diseases. Barley, with sorghum, rice, and wheat, are the only cereals that contain these compounds. Because of that, two barley genotypes, named waxy and non-waxy, were analyzed by normal-phase high-performance liquid chromatography-fluorescence detection-mass spectrometry (NP-HPLC-FLD-MS). Total proanthocyanidin content ranged between 293.2 and 652.6 µg/g of flour. Waxy samples reported the highest content (p < 0.05) of proanthocyanidins. Dimer compounds were the principal proanthocyanidin constituents of barley samples. Moreover, the possibility to use near-infrared (NIR) spectroscopy as a rapid method to discriminate between waxy and non-waxy samples and to predict quantitatively proanthocyanidins in barley samples was evaluated. Partial least squares (PLS) models were built to predict the proanthocyanidin constituent, obtaining determination coefficients (R(2)) ranging from 0.92 to 0.97, in test set validation. Because of that, this study highlights that NIR spectroscopy technology with multivariate calibration analysis could be successfully applied as a rapid method to determine proanthocyanidin content in barley.

Evaluation of coffee roasting degree by using electronic nose and artificial neural network for off-line quality control.

UNLABELLED: An electronic nose (EN) based on an array of 10 metal oxide semiconductor sensors was used, jointly with an artificial neural network (ANN), to predict coffee roasting degree. The flavor release evolution and the main physicochemical modifications (weight loss, density, moisture content, and surface color: L*, a*), during the roasting process of coffee, were monitored at different cooking times (0, 6, 8, 10, 14, 19 min). Principal component analysis (PCA) was used to reduce the dimensionality of sensors data set (600 values per sensor). The selected PCs were used as ANN input variables. Two types of ANN methods (multilayer perceptron [MLP] and general regression neural network [GRNN]) were used in order to estimate the EN signals. For both neural networks the input values were represented by scores of sensors data set PCs, while the output values were the quality parameter at different roasting times. Both the ANNs were able to well predict coffee roasting degree, giving good prediction results for both roasting time and coffee quality parameters. In particular, GRNN showed the highest prediction reliability. PRACTICAL APPLICATION: Actually the evaluation of coffee roasting degree is mainly a manned operation, substantially based on the empirical final color observation. For this reason it requires well-trained operators with a long professional skill. The coupling of e-nose and artificial neural networks (ANNs) may represent an effective possibility to roasting process automation and to set up a more reproducible procedure for final coffee bean quality characterization.

Cytogenetic biomonitoring on a group of petroleum refinery workers.

Workers employed in petroleum refineries are exposed to a wide range of toxic compounds (benzene, polycyclic aromatic hydrocarbons, heavy metals, etc.) with known mutagenic and carcinogenic potential. In this study, we investigated by using the cytokinesis block micronucleus (CBMN) assay on human peripheral blood lymphocytes (PBL) whether general occupational exposure in petroleum refineries resulted in early biological effects, which would be indicative of adverse health effects in the long term. In this study, out of more 500 workers enrolled in the study, 79 male subjects (46 nonsmokers and 33 smokers), employed in two different Italian petroleum refineries, and a total of 50 male control subjects (34 nonsmokers and 16 smokers) were selected by using very strict selection criteria. The comparison of chromosome damage in PBL between exposed and control populations pointed out a significant increase of micronuclei in the exposed group, correlated with the length of employment. Results confirm that smoking is the principal confounding factor for the responses. In conclusion, our results are indicative of a potential genotoxic risk related to the complex occupational exposure in petroleum refineries, despite the measures adopted in the plants, and corroborate the need to increase safety measures to avoid exposure to chemical agents.

FT-NIR spectroscopy for the quality characterization of apricots (Prunus armeniaca L.).

UNLABELLED: The nondestructive assessment of apricot fruit quality (Bora cultivar) was carried out by means of FT-NIR reflectance spectroscopy in the wavenumber range 12000 to 4000 cm⁻¹. Samples were harvested at four different ripening stages and scanned by a fiber optical probe immediately after harvesting and after a storage of 3 d (2 d at 4 °C and 1 d at 18 °C); the flesh firmness (FF), the soluble solids content (SSC), the acidity (A), and the titratable acidity (malic and citric acids) were then measured by destructive methods. Soft independent modeling of class analogy (SIMCA) analysis was used to classify spectra according to the ripening stage and the storage: partial least squares regression (PLS) models to predict FF, SSC, A, and the titratable acidity were also set-up for both just harvested and stored apricots. Spectral pretreatments and wavenumber selections were conducted on the basis of explorative principal component analysis (PCA). Apricot spectra were correctly classified in the right class with a mean classification rate of 87% (range: 80% to 100%). Test set validations of PLS models showed R2 values up to 0.620, 0.863, 0.842, and 0.369 for FF, SSC, A, and the titratable acidity, respectively. The best models were obtained for the SSC and A and are suitable for rough screening; a lower power prediction emerged for the other maturity indices and the relative predictive models are not recommended. PRACTICAL APPLICATION: The results of the study could be used as a tool for the assessment of the ripening stage during the harvest and the quality during the postharvest storage of apricot fruits.