A finite element model of spinodal decomposition in a power-law fluid in the extruder cooling die has been developed to investigate the effects of different parameters on fibre formation and alignment. The model makes use of the Cahn-Hilliard equations with a thermodynamic potential and numerical approximations to simulate local compositions in the separated state. The constitutive model is calibrated towards extrusion-relevant strain rates and temperatures by using a combination of rheometry techniques. The simulations show that the effect of decreased wall cooling has a limited effect on fibre development. Instead, decreasing the die width or increasing the die length can be used somewhat interchangeably to achieve fibre formation at the die exit. Viscosity also seemed to influence fibre formation in the outer viscous regions of the die by yielding comparably finer lamellar structures. The local composition of fibres also varied across the die, which may indicate differences in fibre consistency. 

lant proteins such as soy, pea and wheat gluten are known to form a fibrous structures resembling chicken meat when extruded at elevated temperature with subsequent active cooling. The current hypothesis on the mechanisms responsible for the fibre formation contribute to understanding but are not sufficient to describe the full picture and cannot be used to predict fibre formation ability of protein melts thus hampering the use of more sustainable protein ... interactions between protein chains or polymer crystallites. The aim of the present study to use rheological data of protein melts combined with simulation to elucidate the fibre formation mechanisms and this paper will show an example.

There is growing interest in consumer health related to food, behaviourand lifestyle determinants. At the same time, digitalisation of societies creates newsets of data on consumers. A major driving force in the paradigm shift towards adigital consumer society is the continuous ICT developments that enable a future datasharing economy, where consumers are donating their data, thus making it availablefor food business analysts, marketing researchers and scientists. Business intelligence& analytics (BI&A) has gone through an evolution process and huge amounts ofconsumer data is now collected and analysed. The methodologies for data collectionand analysis are based on the different smart IC technologies that have transformedthe way goods are purchased, extending beyond just transactions. Similarly, from ascientific perspective, it is reasonable to assume that similar ICT solutions may play animportant role in the understanding of public health issues.The study was carried out as part of the RICHFIELDS project aimed at designing afuture European research infrastructure (RI) for innovative research on healthy foodchoices, preparation and consumption of EU-citizens and their respective relationshipswith socio- economic factors. The project, funded by the H2020 program is seeking todevelop state-of- the–art RI that combines knowledge of consumer behaviour and foodintake in one data platform.

This paper presents a new approach combining experimental methodology and modelling, developed to evaluate the effective diffusivity of water in skim milk during drying over a full range of water contents and temperatures. This parameter is important to support modelling of spray-drying processes and designing of equipment. The effective diffusion coefficient is evaluated using a combination of nuclear magnetic resonance (NMR) and parameter estimation. NMR is used to determine the temperature dependence and parameter estimation is used to estimate the water concentration dependence of the effective diffusivity of water in skim milk (0.90 on total weight basis) during drying by comparing the experimental data obtained using a suspended-drop method, which allows the recording of weight and temperature changes during drying, with the results of a distributed heat and mass transport model. The results indicate that the free-volume theory best predicts the dependence of the effective diffusion coefficient of water in skim milk. A mathematical correlation of effective diffusivity over a full range of water contents and temperatures (from 50 to 90°C) was obtained and experimentally successfully validated for concentrated skim milk (0.70 on total weight basis).

This paper presents a new approach combining experimental methodology and modelling, developed to evaluate the effective diffusivity of water in skim milk during drying over a full range of water contents and temperatures. This parameter is important to support modelling of spray-drying processes and designing of equipment. The effective diffusion coefficient is evaluated using a combination of nuclear magnetic resonance (NMR) and parameter estimation. NMR is used to determine the temperature dependence and parameter estimation is used to estimate the water concentration dependence of the effective diffusivity of water in skim milk (0.90 on total weight basis) during drying by comparing the experimental data obtained using a suspended-drop method, which allows the recording of weight and temperature changes during drying, with the results of a distributed heat and mass transport model. The results indicate that the free-volume theory best predicts the dependence of the effective diffusion coefficient of water in skim milk. A mathematical correlation of effective diffusivity over a full range of water contents and temperatures (from 50 to 90 °C) was obtained and experimentally successfully validated for concentrated skim milk (0.70 on total weight basis).