Industrial scale microwave processing of tomato juice using a novel continuous microwave system

This study evaluated the effect of an industrial scale continuous flow microwave volumetric heating system in comparison to conventional commercial scale pasteurisation for the processing of tomato juice in terms of physicochemical properties, microbial characteristics and antioxidant capacity. The effect against oxidative stress in Caco-2 cells, after in vitro digestion was also investigated. Physicochemical and colour characteristics of juices were very similar between technologies and during storage. Both conventional and microwave pasteurisation inactivated microorganisms and kept them in low levels throughout storage. ABTS⁺ values, but not ORAC, were higher for the microwave pasteurised juice at day 0 however no significant differences between juices were observed during storage. Juice processed with the microwave system showed an increased cytoprotective effect against H₂O₂ induced oxidation in Caco-2 cells. Organoleptic analysis revealed that the two tomato juices were very similar. The continuous microwave volumetric heating system appears to be a viable alternative to conventional pasteurisation.

Infrared and Raman screening of seized novel psychoactive substances: A large scale study of >200 samples

The potential of IR absorption and Raman spectroscopy for rapid identification of novel psychoactive substances (NPS) has been tested using a set of 221 unsorted seized samples suspected of containing NPS. Both IR and Raman spectra showed large variation between the different sub-classifications of NPS and smaller, but still distinguishable, differences between closely related compounds within the same class. In initial tests, screening the samples using spectral searching against a limited reference library allowed only 41% of the samples to be fully identified. The limiting factor in the identification was the large number of active compounds in the seized samples for which no reference vibrational data were available in the libraries rather than poor spectral quality. Therefore, when 33 of these compounds were independently identified by NMR and mass spectrometry and their spectra used to extend the libraries, the percentage of samples identified by IR and Raman screening alone increased to 76%, with only 7% of samples having no identifiable constituents. This study, which is the largest of its type ever carried out, therefore demonstrates that this approach of detecting non-matching samples and then identifying them using standard analytical methods has considerable potential in NPS screening since it allows rapid identification of the constituents of the majority of street quality samples. Only one complete feedback cycle was carried out in this study but there is clearly the potential to carry out continuous identification/updating when this system is used in operational settings.

Novel precipitated zirconia-based DGT technique for high-resolution imaging of oxyanions in waters and sediments

Water-sediment exchange is a fundamental component of oxyanion cycling in the environment. Yet, many of the (im)mobilization processes overlay complex spatial and temporal redox regimes that occur within millimeters of the interface. Only a few methods exist that can reliably capture these porewater fluxes, with the most popular being high-resolution diffusive gradients in thin films (HR-DGT). However, functionality of HR-DGT is restricted by the availability of suitable analyte binding agents within the sampler, which must be simple to cast and homogeneously distributed in the binding layer, exhibit adequate sorption capacities, be resistive to chemical change, and possess a very fine particle size (≤10 μm). A novel binding layer was synthesized to meet these requirements by in situ precipitation of zirconia into a precast hydrogel. The particle diameter ≤0.2 μm of zirconia in this precipitated gel was uniform and at least 50-times smaller than the conventional molding approach. Further, this gel had superior binding and stability characteristics compared with the commonly used ferrihydrite HR-DGT technique and could be easily fabricated as an ultrathin gel (60 μm) for simultaneous oxygen imaging in conjunction with planar-optodes. Chemical imaging of anion and oxygen fluxes using the new sampler were evaluated on Lake Taihu sediments.

Sediment metal bioavailability in Lake Taihu, China: evaluation of sequential extraction, DGT, and PBET techniques

The European “Community Bureau of Reference” (BCR) sequential extraction procedure, diffusive gradient in thin-films technique (DGT), and physiologically based extraction test were applied to assess metal bioavailability in sediments of Lake Taihu (n = 13). Findings from the three methods showed that Cd was a significant problem in the western lake whereas Cu, Zn, and Ni pollution was most severe in the northern lake. Results from the sequential extraction revealed that more than 50 % of the Cu and Zn were highly mobile and defined within the extractable fraction (AS1 + FM2 + OS3) in the majority of the sediments, in contrast extractable fractions of Ni and Cd were lower than 50 % in most of the sampling sites. Average Cu, Zn, Ni, and Cd bioaccessibilities were <50 % in the gastric phase. Zn and Cd bioaccessibility in the intestinal phase was ∼50 % lower than the gastric phase while bioaccessibilities of Cu and Ni were 47–57 % greater than the gastric phase. Linear regression analysis between DGT and BCR measurements indicated that the extractable fractions (AS1 + FM2 + OS3) in the reducing environment were the main source of DGT uptake, suggesting that DGT is a good in situ evaluation tool for metal bioavailability in sediments.

Design, production and characterisation of granular adsorbent material for arsenic removal from contaminated wastewater

The objective of this research was to design granulated iron oxide for the adsorption of heavy metals from wastewater. Polyvinyl acetate (PVAc) was chosen as a suitable binder; as it is water insoluble. Initial experiments on selection of suitable solvent of the polymer were carried out using three solvents namely; methanol, acetone and toluene. Based on the initial tests on product yield and mechanical strength, acetone was selected as the solvent for the polyvinyl acetate binder. Design of experiment was then used to investigate the influence of granulation process variables; impeller speed, binder concentration and liquid to solid ratio on the properties of the granular materials. The response variables in the study were granules mean size, stability in water and granule strength. The results showed that the combination of high impeller speed and high binder concentration favour the formation of strong and stable granules. Results also showed that leaching of the binder into the simulated was water was negligible. Trial adsorption experiments carried out using the strongest and most stable iron oxide granules produced in this work showed removal efficiency of around 70% of synthetic arsenic solutions with initial concentration of 1000 ppb.

Generating Data Augmented Spectroscopic Data For Performance Enhancement

The application of chemometrics in food science has revolutionized the field by allowing the creation of models able to automate a broad range of applications such as food authenticity and food fraud detection. In order to create effective and general models able to address the complexity of real life problems, a vast amount of varied training samples are required. Training dataset has to cover all possible types of sample and instrument variability. However, acquiring a varied amount of samples is a time consuming and costly process, in which collecting samples representative of the real world variation is not always possible, specially in some application fields. To address this problem, a novel framework for the application of data augmentation techniques to spectroscopic data has been designed and implemented. This is a carefully designed pipeline of four complementary and independent blocks which can be finely tuned depending on the desired variance for enhancing model's robustness: a) blending spectra, b) changing baseline, c) shifting along x axis, and d) adding random noise.
This novel data augmentation solution has been tested in order to obtain highly efficient generalised classification model based on spectroscopic data. Fourier transform mid-infrared (FT-IR) spectroscopic data of eleven pure vegetable oils (106 admixtures) for the rapid identification of vegetable oil species in mixtures of oils have been used as a case study to demonstrate the influence of this pioneering approach in chemometrics, obtaining a 10% improvement in classification which is crucial in some applications of food adulteration.