Sundaram Gunasekaran

Cheese rheology and texture.

Cheesemaking - An Overview Cheese Types Cheesemaking References Fundamental Rheological Methods Definition of Rheology Basic Concepts Fundamental Methods Uniaxial Compression Shear Rheometry Extensional Rheometry References Uniaxial Testing of Cheese Uniaxial Compression Measurements Structure and Composition Effects Stress-relaxation Measurements Torsion Measurements Tension Measurements Creep Measurements Bending Measurements Vane Measurements Shear Measurements Lubricated Squeezing Flow Measurements References Fracture Properties of Cheese Fracture Mechanics Brittle Fracture Griffith Criterion Determination of KI Fracture Tests on Cheese Cutting, Slicing, and Shredding Cutting with Wire and Blade Eye/slit Formation and Growth References Linear Viscoelasticity of Cheese Mathematical Relations in Linear Viscoelasticity Types of SAOS Measurements Time-Temperature Superposition Application of SAOS in Cheese Rheology Linear Viscoelastic Region of Cheeses Mozzarella: Time-Temperature Superposition Example Cox-Merz Rule References Nonlinear Viscoelasticity of Cheese Pipkin Diagram Sliding Plate Rheometer Large Amplitude Oscillatory Shear Flow Spectral Analysis Discrete Fourier Transform Determining Material Properties Amplitude Spectrum Stress-Shear Rate Loops Effect of Wall Slip Constitutive Model for Cheese Relaxation Modulus Obtained from SAOS Relaxation Modulus Conforming to LAOS References Cheese Texture Texture Development in Cheese Cheese Manufacturing Factors that Affect Texture Measurement of Texture Uniaxial Tests for Cheese Texture Measurement Compression Test Torsion Test and Vane Rheometry Texture Map Dynamic Tests Empirical Tests Crumbliness References Measuring Cheese Melt and Flow Properties Meltability Empirical Tests Objective Tests Steady Shear Viscometry Capillary Rheometry Squeeze-Flow Rheometry UW Meltmeter Viscoelasticity Index for Cheese Meltability Dynamic Shear Rheometry Helical Viscometry Cheese Melt Profile Measurement UW Melt Profiler Determination of Melt Profile Parameters Graphical Method Modeling Melt Profile Constant Temperature Test Conduction Heating References Measuring Cheese Stretchability Empirical Methods Instrumented Methods Vertical Elongation Horizontal Elongation Compression Tests Helical Viscometry Fiber-spinning Technique The Weissenberg Effect References Factors Affecting Functional Properties of Cheese Properties of Milk Cheesemaking Procedures Addition of Starter Culture and Coagulants Cheese Composition Post-Manufacturing Processes Aging/Ripening References

Application of Peleg model to study water absorption in chickpea during soaking

Application of the Peleg model was investigated for predicting water absorption by five winter- and five spring-planted chickpea genotypes during soaking between temperature (T ) of 20 and 100 C. The Peleg model can predict kinetics of the chickpea soaking till equilibrium using short-term data at the given conditions. Its specific form for infinite time may also be used to estimate equilibrium moisture content (Me )a tT P 40 C. Spring and winter chickpeas showed no significant difference ðP < 0:05Þ in the Peleg rate constant (K1) and Peleg capacity constant (K2) within and between the groups at all temperatures except for K1 at T < 40 C. The discrepancy for K1 was attributed to characteristic water permeabilities of spring and winter chickpeas which were prominent at T < 40 C. The Peleg constant K1 decreased from 17:1 � 10 � 3 to 0:95 � 10 � 3 h% � 1 for the spring chickpeas, and from 22:2 � 10 � 3 to 1:02 � 10 � 3 h% � 1 for the winter chickpeas with increasing temperature from 20 to 100 C. An Arrhenius plot for K1 exhibited a slope change around 55 C corresponding to approximate gelatinization temperature of the chickpea samples. The Peleg constant K2 for the samples linearly increased from 7:26 � 10 � 3 to 9:48 � 10 � 3 % � 1 with increasing temperature from 20 to 100

Dynamic oscillatory shear testing of foods - selected applications

Abstract An ideal solid material will respond to an applied load by deforming finitely and recovering that deformation upon removal of the load. Such a response is called “elastic”. Ideal elastic materials obey Hookes law, which describes a direct proportionality between the stress (σ) and strain (γ) via a proportionality constant called modulus (G), i.e., σ=Gγ. An ideal fluid will deform and continue to deform as long as the load is applied. The material will not recover from its deformation when the load is removed. This response is called “viscous”. The flow of simple viscous materials is described by Newtons law, which constitutes a direct proportionality between the shear stress and the shear rate ( γ ), i.e., σ=η γ . The proportionality constant η is called the shear viscosity. From energy considerations, elastic behavior represents complete recovery of energy expended during deformation, whereas viscous flow represents complete loss of energy as all the energy supplied during deformation is dissipated as heat. Ideal elastic and ideal viscous behaviors present two extreme responses of materials to external stresses. As the terms imply, these are only applicable for “ideal” materials. Real materials, however, exhibit a wide array of responses between viscous and elastic. Most materials exhibit some viscous and some elastic behavior simultaneously and are called “viscoelastic”. Almost all foods, both liquid and solid, belong to this group. The viscoelastic properties of materials are determined by transient or dynamic methods. The transient methods include stress relaxation (application of constant and instantaneous strain and measuring decaying stress with respect to time) and creep (application of constant and instantaneous stress and measuring increasing strain with time). Though such methods are fairly easy to perform, there are several limitations. Major among them is that the material response cannot be determined as a function of frequency.

A highly sensitive non-enzymatic glucose sensor based on a simple two-step electrodeposition of cupric oxide (CuO) nanoparticles onto multi-walled carbon nanotube arrays

A novel, stable and highly sensitive non-enzymatic glucose (Glc) sensor was developed using vertically well-aligned multi-walled carbon nanotubes array (MWCNTs) incorporated with cupric oxide (CuO) nanoparticles. The MWCNTs array was prepared by catalytic chemical vapor deposition on a tantalum (Ta) substrate, while a simple and rapid two-step electrodeposition technique was used to prepare the CuO-MWCNTs nanocomposite. First, Cu nanoparticles were deposited onto MWCNTs at constant potential and then they were oxidized into CuO by potential cycling. The electrocatalytic activity of CuO-MWCNTs array was investigated for Glc under alkaline conditions using cyclic voltammetry and chronoamperometry. The sensor exhibited a linear response up to 3 mM of Glc and sensitivity of 2190 microA mM(-1) cm(-2), which is two to three orders of magnitude higher than that of most non-enzymatic Glc sensors reported in the literature. The sensor response time is less than 2s and detection limit is 800 nM (at signal/noise=3). When tested with human blood serum samples, the sensor exhibited high electrocatalytic activity, stability, fast response and good selectivity against common interfering species, suggesting its potential to be developed as a non-enzymatic Glc sensor.

Computer vision technology for food quality assurance

Computer vision systems are being used increasingly in the food industry for quality assurance purposes. Essentially, such systems replace human inspectors for the evaluation of a variety of quality attributes of raw and prepared foods. Over the past few years, the explosive growth in both computer hardware and software has led to many significant advances in computer vision technology. Computer vision applications range from routine inspection to complex vision-guided robotic controls. Computer vision technology provides a high level of flexibility and repeatability at relatively low cost. It also permits fairly high plant throughput without compromising accuracy. Currently, computer vision systems are being developed as an integral part of food processing plants for on-line, real-time quality evaluation and quality control.

An amperometric non-enzymatic glucose sensor by electrodepositing copper nanocubes onto vertically well-aligned multi-walled carbon nanotube arrays

A non-enzymatic glucose (Glc) sensor was developed by potentiostatically electrodepositing metallic Cu nanocubes from a precursor solution onto vertically well-aligned multi-walled carbon nanotube arrays (MWCNTs). The electrochemical characteristics of the sensor were studied by electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). The sensor shows significantly higher electrocatalytic activity to the oxidation of Glc in 0.1M NaOH alkaline solution after modification of Cu nanocubes than before. The sensor response is rapid (<1s) and highly sensitive (1096 μA mM(-1) cm(-2)) with a wide linear range (up to 7.5 mM) and low detection limit (1.0 μM at signal/noise ratio (S/N)=3); it also exhibits high stability and specificity to Glc and performs very well in detecting of Glc concentration in human blood serum.

Electrochemical synthesis of reduced graphene sheet-AuPd alloy nanoparticle composites for enzymatic biosensing

A simple, fast, green and controllable approach was developed for electrochemical synthesis of a novel nanocomposite of electrochemically reduced graphene oxide (ERGO) and gold-palladium (1:1) bimetallic nanoparticles (AuPdNPs), without the aid of any reducing reagent. The electrochemical reduction efficiently removed oxygen-containing groups in ERGO, which was then modified with homogeneously dispersed AuPdNPs in a good size distribution. ERGO-AuPdNPs nanocomposite showed excellent biocompatibility, enhanced electron transfer kinetics and large electroactive surface area, and were highly sensitive and stable towards oxygen reduction. A biosensor was constructed by immobilizing glucose oxidase as a model enzyme on the nanocomposites for glucose detection through oxygen consumption during the enzymatic reaction. The biosensor had a detection limit of 6.9μM, a linear range up to 3.5mM and a sensitivity of 266.6μAmM(-1)cm(-2). It exhibited acceptable reproducibility and good accuracy with negligible interferences from common oxidizable interfering species. These characteristics make ERGO-AuPdNPs nanocomposite highly suitable for oxidase-based biosensing.

PULSED MICROWAVE-VACUUM DRYING OF FOOD MATERIALS

ABSTRACT Microwave drying of food materials has been investigated over several years as a potential means for reducing the total drying time. However, some quality loss almost always accompanied when foods were dried completely using microwaves due to nonuniform temperature and moisture distribution. Some strategies used to improve dried product quality include combination of microwave and conventional hot air drying. pulsed or intermittent drying, and microwave-vacuum drying. Combination of pulsing and vacuum drying is a useful technique to maximize energy use efficiency and product quality especially for temperature sensitive products such as fruits. Some results of pulsed, microwave-vacuum drying of cranberries are presented. Pulsed drying is more energy efficient than continuous drying. In pulsed drying, the longer the pulsing ratio (i.e. longer power-off time in relation to power-on time) was more energy efficient. The quality of pulse-dried product was also generally better than that of continuous-d...

Nickel nanoparticle–chitosan-reduced graphene oxide-modified screen-printed electrodes for enzyme-free glucose sensing in portable microfluidic devices

A facile one-step strategy is reported to synthesize nanocomposites of chitosan-reduced graphene oxide-nickel nanoparticles (CS-RGO-NiNPs) onto a screen-printed electrode (SPE). The synthesis is initiated by electrostatic and hydrophobic interactions and formation of self-assembled nanocomposite precursors of negatively charged graphene oxide (GO) and positively charged CS and nickel cations (Ni(2+)). The intrinsic mechanism of co-depositions from the nanocomposite precursor solution under cathodic potentials is based on simultaneous depositions of CS at high localized pH and in situ reduced hydrophobic RGO from GO as well as cathodically reduced metal precursors into nanoparticles. There is no need for any pre- or post-reduction of GO due to the in situ electrochemical reduction and the removal of oxygenated functionalities, which lead to an increase in hydrophobicity of RGO and successive deposition on the electrode surface. The as-prepared CS-RGO-NiNPs-modified SPE sensor exhibited outstanding performance for enzymeless glucose (Glc) sensing in alkaline media with high sensitivity (318.4µAmM(-1)cm(-2)), wide linear range (up to 9mM), low detection limit (4.1µM), acceptable selectivity against common interferents in physiological fluids, and excellent stability. A microfluidic device was fabricated incorporating the SPE sensor for real-time Glc detection in human urine samples; the results obtained were comparable to those obtained using a high-performance liquid chromatography (HPLC) coupled with an electrochemical detector. The excellent sensing performance, operational characteristics, ease of fabrication, and low cost bode well for this electrochemical microfluidic device to be developed as a point-of-care healthcare monitoring unit.

Preparation and Characterization of Whey Protein Film Incorporated with TiO2 Nanoparticles

Biodegradable titanium dioxide (TiO(2))/whey protein isolate (WPI) blend films were made by casting denatured WPI film solutions incorporated with TiO(2) nanoparticles. X-ray diffraction, UV-vis spectra, and fluorescence spectra of the films showed the successful incorporation of TiO(2) nanoparticles into the WPI matrix and indicated the interactions between TiO(2) and WPI. Mechanical tests revealed the antiplasticizing effect of TiO(2) nanoparticles on the WPI/TiO(2) film. Small amounts (<1 wt%) of added TiO(2) nanoparticles significantly increase the tensile properties of WPI film, but also decrease the moisture barrier properties. The addition of higher amounts (>1 wt%) of TiO(2) improves moisture barrier properties but lowers the tensile properties of the film. Microstructural evaluation confirmed the aggregation and distribution of TiO(2) nanoparticles within the WPI matrix and validated the results of functional properties of the WPI/TiO(2) film.