Effects of Mixing Duration and Raw Materials on the Physicochemical, Microstructural and Sensorial Properties of Sausages Prepared From Red Tilapia (Oreochromis sp.)

Tilapia can be commercialised to produce sausages. However, the use of minced tilapia or tilapia surimi as the raw material and different mixing durations of the ingredients using the bowl cutter during the sausage production could affect the quality of the products. This study determined the effects of different mixing durations (10, 15 or 20 min) on the physicochemical, microstructural and sensorial properties of sausages made from minced tilapia and tilapia surimi. The washing of the minced tilapia during the surimi production significantly increased the tilapia surimi moisture content and pH, while reducing the protein, fat and ash contents. Subsequently, the addition of other ingredients to produce the sausages influenced the moisture, fat, ash and carbohydrate contents of both types of sausages. The type of raw material and mixing duration showed significant interactions in terms of linear expansion, water holding capacity and colour properties of the sausages. Individually, the tilapia surimi sausage had a better linear expansion, cohesiveness, colour and sensory acceptability than the minced tilapia sausage. The mixing times of 15 and 20 min produced better results for the physicochemical and sensory properties of both types of sausages. However, the gel strengths of both types of sausages were better when mixed for 15 min and the microstructure images supported this. Based on the results obtained, this study concluded that tilapia surimi as the raw material with 15 min of mixing duration is recommended to produce a better-quality sausage.

Complexity Analysis of a Sampling-Based Interior Point Method for Convex Optimization

We develop a short-step interior point method to optimize a linear function over a convex body assuming that one only knows a membership oracle for this body. The approach is based a sketch of a universal interior point method using the so-called entropic barrier. It is well known that the gradient and Hessian of the entropic barrier can be approximated by sampling from Boltzmann-Gibbs distributions and the entropic barrier was shown to be self-concordant. The analysis of our algorithm uses properties of the entropic barrier, mixing times for hit-and-run random walks, approximation quality guarantees for the mean and covariance of a log-concave distribution, and results on inexact Newton-type methods.

Study of the Effect of a Plug with Torsion Channels on the Mixing Time in a Continuous Casting Ladle Water Model

The use of porous plugs in injecting gas through the bottom of a ladle forms vertical plumes in a very similar way to a truncated cone. The gas plume when exiting the plug has a smaller diameter compared to that formed in the upper zone of the ladle because inertial forces predominate over buoyancy forces in this zone. In addition, the magnitude of the plume velocity is concentrated in an upward direction, which increases the likelihood of low velocity zones forming near the bottom of the ladle, especially in lower corners. In this work, a plug with spiral-shaped channels with different torsion angles is proposed, with the objective that the gas, when passing through them, has a tangential velocity gain or that the velocity magnitude is distributed in the three axes and does not just focus on the upward direction, helping to decrease low velocity zones near the bottom of the ladle for better mixing times. For the experimentation, we worked in a continuous casting ladle water model with two configuration injections, which in previous works were reported as the most efficient in mixing the steel in this ladle. The results obtained using the PIV technique (particle image velocimetry) and conductimetry technique indicate that the plugs with the torsion channels at angles of 60° and 120° improve the mixing times for the two injection configurations.

Establishment of a simple method to evaluate mixing times in a plastic bag photobioreactor using image processing based on freeware tools

Objective Accurate determination of the mixing time in bioreactors is essential for the optimization of the productivity of bioprocesses. The aim of this work was to develop a simple optical method to determine the mixing time in a photobioreactor. The image processing method should be based on freeware tools, should not require programming skills, and thus could be used in education within high schools and in early stages of undergraduate programs. Results An optical method has been established to analyze images from recorded videos of mixing experiments. The steps are: 1. Extraction of a sequence of images from the video file; 2. Cropping of the pictures; 3. Background removal; and 4. Image analysis and mixing time evaluation based on quantification of pixel-to-pixel heterogeneity within a given area of interest. The novel method was generally able to track the dependency between aeration rate and mixing time within the investigated photobioreactor. In direct comparison, a pearson correlation coefficient of rho = 0.99 was obtained. Gas flow rates between 10 L h−1, and 300 L h−1 resulted from mixing times of between 48 and 14 s, respectively. This technique is applicable without programming skills and can be used in education with inexperienced user groups.

Smartphone Application for Determining the Segregation Index of Lightweight Aggregate Concrete

Due to the low density of the aggregates and the longer mixing times, lightweight aggregate concrete (LWAC) is susceptible to segregation of the aggregates. Several studies have proposed different methods to estimate the segregation of concrete because segregation affects strength and durability in structures. Image analysis techniques have become very popular for quickly analysing different materials and, together with the widespread use of mobile applications, can make it much easier for engineers to obtain parameters that identify concrete segregation. The aim of this work was the development of a mobile application to photograph the section of a concrete specimen and indicate the segregation values. A simple, fast, and effective application was implemented, and the results were validated with other previously published results, which can facilitate the task of engineers and researchers to determine the segregation of concrete.

Establishment of a simple method to evaluate mixing times in a plastic bag photobioreactor using image processing based on freeware tools

Objective The aim of this work was to develop a simple optical method to determine the mixing time in a photobioreactor. The image processing method should be based on freeware tools and should not require programming skills. Results An optical method has been established to analyze images from recorded videos of mixing experiments. The basic steps are: 1. Extraction of a sequence of images from the video file; 2. Cropping of the pictures; 3. Background removal; and 4. Image analysis and mixing time evaluation based on quantification of pixel-to-pixel heterogeneity (standard deviation over pixel intensities) within a given area of interest. The novel method was generally able to track the dependency between aeration rate and mixing time within the investigated photobioreactor. In a direct comparison, a Pearson correlation coefficient of rho = 0.9957 was obtained. Gas flow rates between 10 L h−1, and 300 L h−1 resulted from mixing times of between 48 sec and 14 sec, respectively. This simple technique is applicable even without programming skills and can be used in education within high schools and in early stages of undergraduate programs.

Automated Compartment Model Development Based on Data from Flow-Following Sensor Devices

Due to the heterogeneous nature of large-scale fermentation processes they cannot be modelled as ideally mixed reactors, and therefore flow models are necessary to accurately represent the processes. Computational fluid dynamics (CFD) is used more and more to derive flow fields for the modelling of bioprocesses, but the computational demands associated with simulation of multiphase systems with biokinetics still limits their wide applicability. Hence, a demand for simpler flow models persists. In this study, an approach to develop data-based flow models in the form of compartment models is presented, which utilizes axial-flow rates obtained from flow-following sensor devices in combination with a proposed procedure for automatic zoning of volume. The approach requires little experimental effort and eliminates the necessity for computational determination of inter-compartmental flow rates and manual zoning. The concept has been demonstrated in a 580 L stirred vessel, of which models have been developed for two types of impellers with varying agitation intensities. The sensor device measurements were corroborated by CFD simulations, and the performance of the developed compartment models was evaluated by comparing predicted mixing times with experimentally determined mixing times. The data-based compartment models predicted the mixing times for all examined conditions with relative errors in the range of 3–27%. The deviations were ascribed to limitations in the flow-following behavior of the sensor devices, whose sizes were relatively large compared to the examined system. The approach provides a versatile and automated flow modelling platform which can be applied to large-scale bioreactors.

The Use of Computational Fluid Dynamics in the Analysis of Gas-Liquid-Liquid Reactors

Gas–liquid–liquid reactors are typically found in bioprocess setups such as those used in alkane biocatalysis and biological gas stripping. The departure of such reactors from traditional gas–liquid setups is by the introduction of a secondary (dispersed) liquid phase. The introduction of the latter results in complicated hydrodynamics as observed through measurements of velocity fields, turbulence levels and mixing times. Similarly, changes in mass transfer occur as observed through measurements of gas hold up, bubble diameters and the volumetric mass transfer coefficients. The design and analysis of such reactors thus requires the adoption of an approach that can comprehensively account for the various observed changes. This chapter proposes Computational Fluid Dynamics as an approach fit for this purpose. Key considerations, successes and challenges of this approach are highlighted and discussed based on a review of previously published case studies.