Supermarkets and agro-industrial foods : the strategic manufacturing of consumer trust

There is increasing evidence of a weakened platform of consumer trust in mass produced food products. The resistance shown by consumers to the agro-industrial paradigm is evident in an emergent phase of reflexive consumerism, public reactions to an overly-concentrated retail sector and the rise of alternative food networks such as farmers' markets and organic box schemes. Supermarkets are responding strategically by aiming to manufacture new trust relations with consumers. This paper identifies three key strategies of trust manufacturing: (i) reputational enhancement though the institution of “behind the scenes,” business-to-business private standards; (ii) direct quality claims via private standard certification badges on food products, and ; (iii) discursive claimsmaking through symbolic representations of “authenticity” and “tradition.” Drawing upon the food governance literature and a “visual sociology” of supermarkets and supermarket produce, we highlight how trust is both commoditized and increasingly embedded into the marketing of mass-produced foods.

Computation of Mathematical Models for Complex Industrial Processes

Designed for undergraduate and postgraduate students, academic researchers and industrial practitioners, this book provides comprehensive case studies on numerical computing of industrial processes and step-by-step procedures for conducting industrial computing. It assumes minimal knowledge in numerical computing and computer programming, making it easy to read, understand and follow. Topics discussed include fundamentals of industrial computing, finite difference methods, the Wavelet-Collocation Method, the Wavelet-Galerkin Method, High Resolution Methods, and comparative studies of various methods. These are discussed using examples of carefully selected models from real processes of industrial significance. The step-by-step procedures in all these case studies can be easily applied to other industrial processes without a need for major changes and thus provide readers with useful frameworks for the applications of engineering computing in fundamental research problems and practical development scenarios.

Metal oxide nanofibres membranes assembled by spin-coating method

Ceramic membranes are of particular interest in many industrial processes due to their ability to function under extreme conditions while maintaining their chemical and thermal stability. Major structural deficiencies under conventional fabrication approach are pin-holes and cracks, and the dramatic losses of flux when pore sizes are reduced to enhance selectivity. We overcome these structural deficiencies by constructing hierarchically structured separation layer on a porous substrate using larger titanate nanofibres and smaller boehmite nanofibres. This yields a radical change in membrane texture. The differences in the porous supports have no substantial influences on the texture of resulting membranes. The membranes with top layer of nanofibres coated on different porous supports by spin-coating method have similar size of the filtration pores, which is in a range of 10–100 nm. These membranes are able to effectively filter out species larger than 60 nm at flow rates orders of magnitude greater than conventional membranes. The retention can attain more than 95%, while maintaining a high flux rate about 900 L m-2 h. The calcination after spin-coating creates solid linkages between the fibres and between fibres and substrate, in addition to convert boehmite into -alumina nanofibres. This reveals a new direction in membrane fabrication.

Wavelet based approaches and high resolution methods for complex process models

Many industrial processes and systems can be modelled mathematically by a set of Partial Differential Equations (PDEs). Finding a solution to such a PDF model is essential for system design, simulation, and process control purpose. However, major difficulties appear when solving PDEs with singularity. Traditional numerical methods, such as finite difference, finite element, and polynomial based orthogonal collocation, not only have limitations to fully capture the process dynamics but also demand enormous computation power due to the large number of elements or mesh points for accommodation of sharp variations. To tackle this challenging problem, wavelet based approaches and high resolution methods have been recently developed with successful applications to a fixedbed adsorption column model. Our investigation has shown that recent advances in wavelet based approaches and high resolution methods have the potential to be adopted for solving more complicated dynamic system models. This chapter will highlight the successful applications of these new methods in solving complex models of simulated-moving-bed (SMB) chromatographic processes. A SMB process is a distributed parameter system and can be mathematically described by a set of partial/ordinary differential equations and algebraic equations. These equations are highly coupled; experience wave propagations with steep front, and require significant numerical effort to solve. To demonstrate the numerical computing power of the wavelet based approaches and high resolution methods, a single column chromatographic process modelled by a Transport-Dispersive-Equilibrium linear model is investigated first. Numerical solutions from the upwind-1 finite difference, wavelet-collocation, and high resolution methods are evaluated by quantitative comparisons with the analytical solution for a range of Peclet numbers. After that, the advantages of the wavelet based approaches and high resolution methods are further demonstrated through applications to a dynamic SMB model for an enantiomers separation process. This research has revealed that for a PDE system with a low Peclet number, all existing numerical methods work well, but the upwind finite difference method consumes the most time for the same degree of accuracy of the numerical solution. The high resolution method provides an accurate numerical solution for a PDE system with a medium Peclet number. The wavelet collocation method is capable of catching up steep changes in the solution, and thus can be used for solving PDE models with high singularity. For the complex SMB system models under consideration, both the wavelet based approaches and high resolution methods are good candidates in terms of computation demand and prediction accuracy on the steep front. The high resolution methods have shown better stability in achieving steady state in the specific case studied in this Chapter.

Research project for managing skid resistance is on the road

In December 2006, the Engineering and Technology Group of Queensland’s Department of Main Roads entered into a three-year skid resistance management research project with QUT Faculty of Built Environment and Engineering researchers and the QUT-based CRC for Integrated Engineering Asset Management (CIEAM). CIEAM undertakes a broad range of asset management research in the areas of defence, utilities, transportation and industrial processes. “The research project is an important activity of Main Roads’ Skid Resistance Management Plan published in June 2006.” said Main Roads project leader Mr Justin Weligamage. “The intended project output is a decision-support model for use by Road Asset Managers throughout a road network. The research objective is to enable road asset managers to better manage the surfacing condition of the road asset with specific focus on skid resistance,” said QUT project leader Professor Arun Kumar. The research project will review existing skid resistance investigatory levels, develop a risk-based method to establish skid resistance investigatory levels and improve the decision support methodology in order to minimise crashes. The new risk-based approach will be used to identify locations on the Queensland state-controlled road network that may have inadequate skid resistance. Once a high risk site is identified, the appropriate remedial action will be decided on. This approach will allow road asset managers to target optimal remedial actions, reducing the incidence and severity of crashes where inadequate skid resistance is a contributing cause.

Mechanical behaviours of pumpkin peel under compression test

Mechanical damages such as bruising, collision and impact during food processing stages diminish quality and quantity of productions as well as efficiency of operations. Studying mechanical characteristics of food materials will help to enhance current industrial practices. Mechanical properties of fruits and vegetables describe how these materials behave under loading in real industrial operations. Optimizing and designing more efficient equipments require accurate and precise information of tissue behaviours. FE modelling of food industrial processes is an effective method of studying interrelation of variables during mechanical operation. In this study, empirical investigation has been done on mechanical properties of pumpkin peel. The test was a part of FE modelling and simulation of mechanical peeling stage of tough skinned vegetables. The compression test has been conducted on Jap variety of pumpkin. Additionally, stress strain curve, bio-yield and toughness of pumpkin skin have been calculated. The required energy for reaching bio-yield point was 493.75, 507.71 and 451.71 N.mm for 1.25, 10 and 20 mm/min loading speed respectively. Average value of force in bio-yield point for pumpkin peel was 310 N.

Study of tissue damage during mechanical peeling of tough skinned vegetables

Peeling is an essential phase of post harvesting and processing industry; however the undesirable losses and waste rate that occur during peeling stage are always the main concern of food processing sector. There are three methods of peeling fruits and vegetables including mechanical, chemical and thermal, depending on the class and type of fruit. By comparison, the mechanical method is the most preferred; this method keeps edible portions of produce fresh and creates less damage. Obviously reducing material losses and increasing the quality of the process has a direct effect on the whole efficiency of food processing industry which needs more study on technological aspects of this industrial segment. In order to enhance the effectiveness of food industrial practices it is essential to have a clear understanding of material properties and behaviour of tissues under industrial processes. This paper presents the scheme of research that seeks to examine tissue damage of tough skinned vegetables under mechanical peeling process by developing a novel FE model of the process using explicit dynamic finite element analysis approach. In the proposed study a nonlinear model which will be capable of simulating the peeling process specifically, will be developed. It is expected that unavailable information such as cutting force, maximum shearing force, shear strength, tensile strength and rupture stress will be quantified using the new FEA model. The outcomes will be used to optimize and improve the current mechanical peeling methods of this class of vegetables and thereby enhance the overall effectiveness of processing operations. Presented paper aims to review available literature and previous works have been done in this area of research and identify current gap in modelling and simulation of food processes.

Study of mechanical deformations on tough skinned vegetables during mechanical peeling process

Peeling is an essential phase of post harvesting and processing industry; however undesirable processing losses are unavoidable and always have been the main concern of food processing sector. There are three methods of peeling fruits and vegetables including mechanical, chemical and thermal, depending on the class and type of fruit. By comparison, the mechanical methods are the most preferred; mechanical peeling methods do not create any harmful effects on the tissue and they keep edible portions of produce fresh. The main disadvantage of mechanical peeling is the rate of material loss and deformations. Obviously reducing material losses and increasing the quality of the process has a direct effect on the whole efficiency of food processing industry, this needs more study on technological aspects of these operations. In order to enhance the effectiveness of food industrial practices it is essential to have a clear understanding of material properties and behaviour of tissues under industrial processes. This paper presents the scheme of research that seeks to examine tissue damage of tough skinned vegetables under mechanical peeling process by developing a novel FE model of the process using explicit dynamic finite element analysis approach. A computer model of mechanical peeling process will be developed in this study to stimulate the energy consumption and stress strain interactions of cutter and tissue. The available Finite Element softwares and methods will be applied to establish the model. Improving the knowledge of interactions and involves variables in food operation particularly in peeling process is the main objectives of the proposed study. Understanding of these interrelationships will help researchers and designer of food processing equipments to develop new and more efficient technologies. Presented work intends to review available literature and previous works has been done in this area of research and identify current gap in modelling and simulation of food processes.

Sweet sorghum : opportunities for a new, renewable fuel and food industry in Australia

Sweet sorghum is receiving significant global interest as an agro-industrial crop because of its capacity to co-produce energy, food, and feed products in integrated biorefineries. This report assesses the opportunities to develop a sweet sorghum industry in Australia, reports on research demonstrating the production of energy, food, and feed products, and assesses the potential economic and sustainability benefits of sweet sorghum biorefineries in the Australian context.

A gene encoding a new cold-active lipase from an Antarctic isolate of Penicillium expansum

Cold-active lipases are of significant interest as biocatalysts in industrial processes. We have identified a lipase that displayed activity towards long carbon-chain-p-nitrophenyl substrates (C12–C18) at 25 °C from the culture supernatant of an Antarctic Penicillium expansum strain assigned P. expansum SM3. Zymography revealed a protein band of around 30 kDa with activity towards olive oil. DNA fragments of a lipase gene designated as lipPE were isolated from the genomic DNA of P. expansum SM3 by genomic walking PCR. Subsequently, the complete genomic lipPE gene was amplified using gene-specific primers designed from the 5′- and 3′-regions. Reverse transcription PCR was used to amplify the lipPE cDNA. The deduced amino acid sequence consisted of 285 residues that included a predicted signal peptide. Three peptides identified by LC/MS/MS analysis of the proteins in the culture supernatant of P. expansum were also present in the deduced amino acid sequence of the lipPE gene suggesting that this gene encoded the lipase identified by initial zymogram activity analysis. Full analysis of the nucleotide and the deduced amino acid sequences indicated that the lipPE gene encodes a novel P. expansum lipase. The lipPE gene was expressed in E. coli for further characterization of the enzyme with a view of assessing its suitability for industrial applications.

Biodiesel production from non-edible beauty leaf (Calophyllum Inophyllum) oil : process optimization using response surface methodology (RSM)

In recent years, the beauty leaf plant (Calophyllum Inophyllum) is being considered as a potential 2nd generation biodiesel source due to high seed oil content, high fruit production rate, simple cultivation and ability to grow in a wide range of climate conditions. However, however, due to the high free fatty acid (FFA) content in this oil, the potential of this biodiesel feedstock is still unrealized, and little research has been undertaken on it. In this study, transesterification of beauty leaf oil to produce biodiesel has been investigated. A two-step biodiesel conversion method consisting of acid catalysed pre-esterification and alkali catalysed transesterification has been utilized. The three main factors that drive the biodiesel (fatty acid methyl ester (FAME)) conversion from vegetable oil (triglycerides) were studied using response surface methodology (RSM) based on a Box-Behnken experimental design. The factors considered in this study were catalyst concentration, methanol to oil molar ratio and reaction temperature. Linear and full quadratic regression models were developed to predict FFA and FAME concentration and to optimize the reaction conditions. The significance of these factors and their interaction in both stages was determined using analysis of variance (ANOVA). The reaction conditions for the largest reduction in FFA concentration for acid catalysed pre-esterification was 30:1 methanol to oil molar ratio, 10% (w/w) sulfuric acid catalyst loading and 75 °C reaction temperature. In the alkali catalysed transesterification process 7.5:1 methanol to oil molar ratio, 1% (w/w) sodium methoxide catalyst loading and 55 °C reaction temperature were found to result in the highest FAME conversion. The good agreement between model outputs and experimental results demonstrated that this methodology may be useful for industrial process optimization for biodiesel production from beauty leaf oil and possibly other industrial processes as well.

Pumping systems: Design and energy efficiency

Pumping systems are widely used in many applications, including municipal water/wastewater services, domestic, commercial and agricultural services, and industrial processes. They are a very significant energy user and consume nearly 20% of the world’s electrical energy demand. Therefore, improving the energy efficiency of pumping systems can provide great benefits in terms of energy, environment, and cost reduction. In this entry, an overview of pump classification with pros and cons of each type of pump is presented. The procedures used to design pumping systems are also outlined. This is then followed by a discussion on the opportunities for improving the energy efficiency of pumping systems during every stage of design, selection, operation, and maintenance.

Influence of organic amendments on greenhouse gas emissions and N use efficiency in sub-tropical cropping systems

This thesis investigated the impact of organic sources of nutrients on greenhouse gas emissions (carbon dioxide, nitrous oxide and methane), nitrogen use efficiency and biomass production in subtropical cropping soils. The study was conducted in two main soil types in subtropical ecosystems, sandy loam soil and clay soil, with a variety of organic materials from agro-industrial residues and crop residues. It is important for recycling of agro-industrial residues and agricultural residues and the mitigation of greenhouse gas emissions and nitrogen use efficiency.

Efficient route update and maintenance processes for multipath routing in large-scale industrial wireless sensor networks

Reliable communications is one of the major concerns in wireless sensor networks (WSNs). Multipath routing is an effective way to improve communication reliability in WSNs. However, most of existing multipath routing protocols for sensor networks are reactive and require dynamic route discovery. If there are many sensor nodes from a source to a destination, the route discovery process will create a long end-to-end transmission delay, which causes difficulties in some time-critical applications. To overcome this difficulty, the efficient route update and maintenance processes are proposed in this paper. It aims to limit the amount of routing overhead with two-tier routing architecture and introduce the combination of piggyback and trigger update to replace the periodic update process, which is the main source of unnecessary routing overhead. Simulations are carried out to demonstrate the effectiveness of the proposed processes in improvement of total amount of routing overhead over existing popular routing protocols.

A comprehensive dual-scale wood torrefaction model : application to the analysis of thermal run-away in industrial heat treatment processes

A dual-scale model of the torrefaction of wood was developed and used to study industrial configurations. At the local scale, the computational code solves the coupled heat and mass transfer and the thermal degradation mechanisms of the wood components. At the global scale, the two-way coupling between the boards and the stack channels is treated as an integral component of the process. This model is used to investigate the effect of the stack configuration on the heat treatment of the boards. The simulations highlight that the exothermic reactions occurring in each single board can be accumulated along the stack. This phenomenon may result in a dramatic eterogeneity of the process and poses a serious risk of thermal runaway, which is often observed in industrial plants. The model is used to explain how thermal runaway can be lowered by increasing the airflow velocity, the sticker thickness or by gas flow reversal.