New food safety challenges of viral contamination from a global perspective: Conventional,emerging, and novel methods of viral control

Food- and waterborne viruses, such as human norovirus, hepatitis A virus, hepatitis E virus, rotaviruses, astroviruses, adenoviruses, and enteroviruses, are major contributors to all foodborne illnesses. Their small size, structure, and ability to clump and attach to inanimate surfaces make viruses challenging to reduce or eliminate, especially in the presence of inorganic or organic soils. Besides traditional wet and dry methods of disinfection using chemicals and heat, emerging physical nonthermal decontamination techniques (irradiation, ultraviolet, pulsed light, high hydrostatic pressure, cold atmospheric plasma, and pulsed electric field), novel virucidal surfaces, and bioactive compounds are examined for their potential to inactivate viruses on the surfaces of foods or food contact surfaces (tools, equipment, hands, etc.). Every disinfection technique is discussed based on its efficiency against viruses, specific advantages and disadvantages, and limitations. Structure, genomic organization, and molecular biology of different virus strains are reviewed, as they are key in determining these techniques effectiveness in controlling all or specific foodborne viruses. Selecting suitable viral decontamination techniques requires that their antiviral mechanism of action and ability to reduce virus infectivity must be taken into consideration. Furthermore, details about critical treatments parameters essential to control foodborne viruses in a food production environment are discussed, as they are also determinative in defining best disinfection and hygiene practices preventing viral infection after consuming a food product.     

Stability of DON and DON-3-glucoside during baking as affected by the presence of food additives

The mycotoxin deoxynivalenol (DON) is one of the most common mycotoxins of cereals worldwide, and its occurrence has been widely reported in raw wheat. The free mycotoxin form is not the only route of exposure; modified forms can also be present in cereal products. Deoxynivalenol-3-glucoside (DON-3-glucoside) is a common DON plant conjugate. The mycotoxin concentration could be affected by food processing; here, we studied the stability of DON and DON-3-glucoside during baking of small doughs made from white wheat flour and other ingredients. A range of common food additives and ingredients were added to assess possible interference: ascorbic acid (E300), citric acid (E330), sorbic acid (E200), calcium propionate (E282), lecithin (E322), diacetyltartaric acid esters of fatty acid mono- and diglycerides (E472a), calcium phosphate (E341), disodium diphosphate (E450i), xanthan gum (E415), polydextrose (E1200), sorbitol (E420i), sodium bicarbonate (E500i), wheat gluten and malt flour. The DON content was reduced by 40%, and the DON-3-glucoside concentration increased by >100%, after baking for 20 min at 180°C. This confirmed that DON and DON-3-glucoside concentrations can vary during heating, and DON-3-glucoside could even increase after baking. However, DON and DON-3-glucoside are not affected significantly by the presence of the food additives tested.     

sInfluence of starch and protein molecular interactions on the in vitro digestion characteristics of biscuits partially substituted with pulse flours

Recent research has shown that pulse-derived ingredients present a technological alternative to cereals, higher protein and fibre content, and differentiated starch characteristics. In this work, the partial substitution of pulse flours with and without heat moisture treatment (HMT) was evaluated in a biscuit model. The digestion residues at 20 and 120 min that correspond to rapidly, slowly and resistant starch from the Englyst methodology were analysed by DSC, X-Ray and ATR-FTIR. The use of pulse flours in biscuits improved their thermal stability (ΔH = 3.01 and 4.99 J/g for control and Lentil + HMT), preserving a fraction of particularly ling glucans, that influenced the decreasing in the rapidly available starch from 55.26 to 24.11 % (Control and Faba bean + HMT), and enhanced its protein's digestibility from 75.26 to 87.43 % for the same sources. Among pulses, there were similarities regarding their resistance to enzymatic hydrolysis that may help select those with better organoleptic attributes.     

Remodeling of a commercial plug-in battery electric vehicle to a hybrid configuration with a PEM fuel cell

In the present research, a commercial battery-powered pure electric vehicle was suitably modified to convert it into a hybrid one integrating a PEMFC stack. The hydrogen supply system to the stack included a passive recirculation system based on a Ventury-type ejector. Besides, in order to achieve an optimum operation of the PEMFC stack, a discrete state machine model was considered in its control system. The inclusion of a rehabilitation operating mode prevented the stack from possible failures, increasing its lifetime. It was verified that for the rated operating point when supplying power to the vehicle (2.5 kW) the hydrogen consumption decreased, and the actual efficiency (47.9%) PEMFC was increased close to 1%. Field tests performed demonstrate that the range of the hybrid electric vehicle was increased by 78% when compared to the one of the original battery electric car. Also, under the tested experimental conditions in hybrid mode, 34% of the total energy demanded by the electric machine of the vehicle was supplied by the PEMFC stack.     

Extracting Low-Frequency Spatio-Temporal Patterns in Ambient Power System Data Using Blind Source Separation

Wide-area techniques provide a powerful tool to extract spatio-temporal patterns from high-dimensional datasets and can be used for event detection and visualization, data fusion, stability assessment, and coherency analysis. In this paper, a novel blind source separation-based approach for extracting low-frequency spatio-temporal patterns from measured ambient power system data is proposed and a spatio-temporal visualization index is also suggested. This methodology combines a nonlinear hierarchical neural network with a Blind Source Separation (BSS) technique. The neural network allows reducing noise and removing the nonlinear relations among data (preserve dynamic features of interest), while the BSS technique permits extracting spatial and temporal patterns. In addition, the proposed approach takes advantage of the latest techniques in nonlinear estimation of non-stationary time series. Finally, application examples of the proposed framework on real test cases recorded from an actual power system by Phasor Measurement Units (PMUs) are presented. The obtained results show that the temporal patterns can be used for extracting and identifying the low-frequency oscillation modes and the spatial patterns can be used for identifying modes with the most contribution in original data. Compared to other BSS approaches, the proposed method has shown to be better for the analysis of real ambient data.