Optimisation of time/temperature treatment, for heat treated soft wheat flour

Chlorination of wheat flour in the EU countries has been replaced in recent years, to some extent, by heat treated flour which is used to produce high ratio cakes. Heat treated flour allows high ratio recipes to be developed which generate products with longer shelf life, finer texture, moist crumb and sweeter taste. The mechanism by which heat treatment improves the flour is not fully understood, but it is known that during the heat treatment process, protein denaturation and partial gelatinisation of the starch granules occurs, as well as an increase in batter viscosity. Therefore, it is important to optimize the flour heat treatment process, in order to enhance baking quality. Laboratory preparation of heat treated base wheat flour (culinary, soft, low protein) was carried out in a fluidised bed drier using a range of temperatures and times. The gluten was extracted from the final product and its quality was tested, to obtain objective and comparative information on the extent of protein denaturation. The results indicated that heat treatment of flour decreases gluten extensibility and partial gelatinisation of the starch granules occurred. After heat treatment the gluten appeared to retain moisture. The optimum time/temperature for the heat treatment of base flour was 120-130°C for 30 min with moisture content of ˜12.5%.© 2012 Elsevier Ltd. All rights reserved.

Development of a recombinant Fab-fragment based electrochemical immunosensor for deoxynivalenol detection in food samples

A reliable and cost-effective electrochemical method for the detection of deoxynivalenol (DON) in cereals and cereal-based food samples based on the use of a novel anti-DON Fab fragment is presented. The analytical system employed, Enzyme-Linked-Immunomagnetic-Electrochemical (ELIME) assay, is based on the use of immunomagnetic beads (IMBs) coupled with eight magnetized screen-printed electrodes (8-mScPEs) as electrochemical transducers.

Food-web structure in low- and high-dimensional trophic niche spaces

A question central to modelling and, ultimately, managing food webs concerns the dimensionality of trophic niche space, that is, the number of independent traits relevant for determining consumer-resource links. Food-web topologies can often be interpreted by assuming resource traits to be specified by points along a line and each consumer's diet to be given by resources contained in an interval on this line. This phenomenon, called intervality, has been known for 30 years and is widely acknowledged to indicate that trophic niche space is close to one-dimensional. We show that the degrees of intervality observed in nature can be reproduced in arbitrary-dimensional trophic niche spaces, provided that the processes of evolutionary diversification and adaptation are taken into account. Contrary to expectations, intervality is least pronounced at intermediate dimensions and steadily improves towards lower- and higher-dimensional trophic niche spaces.

A framework for designing robust food supply chains

After years of emphasis on leanness and responsiveness businesses are now experiencing their vulnerability to supply chain disturbances. Although more literature is appearing on this subject, there is a need for an integrated framework to support the analysis and design of robust food supply chains. In this chapter we present such a framework. We define the concept of robustness and classify supply chain disturbances, sources of food supply chain vulnerability, and adequate redesign principles and strategies to achieve robust supply chain performances. To test and illustrate its applicability, the research framework is applied to a meat supply chain.

Development of a rapid low cost fluorescent biosensor for the detection of food contaminants

A prototype fluorescent based biosensor has been developed for the antibody based detection of food related contaminants. Its performance was characterised and showed a typical antibody binding signal of 200-2000 mV, a short term noise of 9.1 mV, and baseline slope of -0.016 mV/s over 4 h. Bulk signal detection repeatability (n=23) and reproducibility (n=3) were less than 2.4%CV. The biosensor detection unit was evaluated using two food related model systems proving its ability to monitor both binding using commercial products and inhibition through the development of an assay. This assay development potential was evaluated by observing the biosensor's performance whilst appraising several labelled antibody and glass slide configurations. The molecular interaction between biotin and an anti-biotin antibody was shown to be inhibited by 41% due to the presence of biotin in a sample. A food toxin (domoic acid) calibration curve was produced, with %CVs ranging from 2.7 to 7.8%, and a midpoint of approximately 17 ng/ml with further optimisation possible. The ultimate aim of this study was to demonstrate the working principles of this innovative biosensor as a potential portable tool with the opportunity of interchangeable assays. The biosensor design is applicable for the requirements of routine food contaminant analysis, with respect to performance, functionality and cost. (C) 2012 Elsevier B.V. All rights reserved.

Engineering of Vis-NIR Metamaterials towards Revolutionary Ultrasensitive and Versatile Plasmonic Biosensors

By enabling subwavelength light localization and strong electromagnetic field enhancement, plasmonic biosensors have opened up a new realm of possibilities for a broad range of chemical and biological sensing applications owing to their label-free and real-time attributes. Although significant progress has been made, many fundamental and practical challenges still remain to be addressed. For instance, the plasmonic biosensors are nonselective sensing platforms; they are not well-suited to provide information regarding conformation or chemical fingerprint of unknown biomolecules. Furthermore, tunability of the plasmonic resonance in visible frequency regime is still limited; this will prevent their efficient and reproducible exploitation in single-molecule sensitivity. Here, we show that by engineering geometry of plasmonic metamaterials,1 consisting of periodic arrays of artificial split-ring resonators (SRRs), the plasmonic resonance of metamaterials could be tuned to visible-near infrared regimes (Vis-NIR) such that it allows parallel acquisition of optical transmission and highly surface-enhanced Raman (SERS) spectra from large functionalized SRR arrays. The Au SRRs were designed in form of alphabet letters (U, V, S, H, Y) with various line width (from 80 to 30 nm). By tailoring their size and shape, plasmonic resonance wavelength of the SRRs could be actively tuned so that it gives the strongest SERS effect under given excitation energy and polarization for biological and organic molecules. On the other hand, the plasmonic tunability was also achieved for a given SRR pattern by tuning the laser wavelength to obtain the highest electromagnetic field enhancement. The geometry- and laser-tunable channels typically provide an electromagnetic field enhancement as high as 20 times. This will provide the basis of versatile and multichannel devices for identification of different conformational states of Guanine-rich DNA, detection of a cancer biomarker nucleolin, and femtomolar sensitivity detection of food and drink additives. These results show that the tunable Vis-IR metamaterials are very versatile biosensing platforms and suggest considerable promise in genomic research, disease diagnosis, and food safety analysis.

Implementation of a cogeneration plant for a food processing facility. A case study

The present work presents an investigation regarding the feasibility analysis of a cogeneration plant for a food processing facility with the aim to decrease the cost of energy supply. The monthly electricity and heat consumption profiles are analyzed, in order to understand the consumption profiles, as well as the costs of the current furniture of electricity and gas. Then, a detailed thermodynamic model of the cogeneration cycle is implemented and the investment costs are linked to the thermodynamic variables by means of cost functions. The optimal electricity power of the co-generator is determined with reference to various investment indexes. The analysis highlights that the optimal dimension varies according to the chosen indicator, therefore it is not possible to establish it univocally, but it depends on the financial/economic strategy of the company through the considered investment index.

Point-and-shoot: rapid quantitative detection methods for on-site food fraud analysis – moving out of the laboratory and into the food supply chain

Major food adulteration and contamination events occur with alarming regularity and are known to be episodic, with the question being not if but when another large-scale food safety/integrity incident will occur. Indeed, the challenges of maintaining food security are now internationally recognised. The ever increasing scale and complexity of food supply networks can lead to them becoming significantly more vulnerable to fraud and contamination, and potentially dysfunctional. This can make the task of deciding which analytical methods are more suitable to collect and analyse (bio)chemical data within complex food supply chains, at targeted points of vulnerability, that much more challenging. It is evident that those working within and associated with the food industry are seeking rapid, user-friendly methods to detect food fraud and contamination, and rapid/high-throughput screening methods for the analysis of food in general. In addition to being robust and reproducible, these methods should be portable and ideally handheld and/or remote sensor devices, that can be taken to or be positioned on/at-line at points of vulnerability along complex food supply networks and require a minimum amount of background training to acquire information rich data rapidly (ergo point-and-shoot). Here we briefly discuss a range of spectrometry and spectroscopy based approaches, many of which are commercially available, as well as other methods currently under development. We discuss a future perspective of how this range of detection methods in the growing sensor portfolio, along with developments in computational and information sciences such as predictive computing and the Internet of Things, will together form systems- and technology-based approaches that significantly reduce the areas of vulnerability to food crime within food supply chains. As food fraud is a problem of systems and therefore requires systems level solutions and thinking.