Application of in-line Raman spectroscopy to monitor crystallization and melting processes in milk fat.

Anhydrous milk fat (AMF) and its fractions are used as ingredients in a wide range of food applications. Obtaining the appropriate solid fat content (SFC) is essential to achieve the desired product texture. At present, in-line monitoring techniques to control milk fat crystallization and melting are largely unavailable. The thermal behaviour of milk fat (AMF and four of its fractions) was monitored in a temperature-controlled vessel using an in-line Raman analyser and compared with thermograms generated using differential scanning calorimetry (DSC). The major stages of milk fat crystallization and melting were identified using the in-line Raman analyser. Thermal data from DSC showed excellent linear correlations with Raman spectral data (R2 value of 0.97 for the onset of milk fat crystallisation). Partial least squares regression (PLSR) models were developed using Raman spectra to predict SFC with coefficient of determination (R2Cs) from 0.929 to 0.992 and root mean standard error of calibration (RMSECs) ranging from 3.20 to 10.36%. Results demonstrated Raman spectroscopy has significant potential as a way of monitoring milk fat crystallization and melting processes.

Spectroscopic technologies and data fusion: Applications for the dairy industry.

Increasing consumer awareness, scale of manufacture, and demand to ensure safety, quality and sustainability have accelerated the need for rapid, reliable, and accurate analytical techniques for food products. Spectroscopy, coupled with Artificial Intelligence-enabled sensors and chemometric techniques, has led to the fusion of data sources for dairy analytical applications. This article provides an overview of the current spectroscopic technologies used in the dairy industry, with an introduction to data fusion and the associated methodologies used in spectroscopy-based data fusion. The relevance of data fusion in the dairy industry is considered, focusing on its potential to improve predictions for processing traits by chemometric techniques, such as principal component analysis (PCA), partial least squares regression (PLS), and other machine learning algorithms.

Recent Advances in Portable and Handheld NIR Spectrometers and Applications in Milk, Cheese and Dairy Powders.

Quality and safety monitoring in the dairy industry is required to ensure products meet a high-standard based on legislation and customer requirements. The need for non-destructive, low-cost and user-friendly process analytical technologies, targeted at operators (as the end-users) for routine product inspections is increasing. In recent years, the development and advances in sensing technologies have led to miniaturisation of near infrared (NIR) spectrometers to a new era. The new generation of miniaturised NIR analysers are designed as compact, small and lightweight devices with a low cost, providing a strong capability for on-site or on-farm product measurements. Applying portable and handheld NIR spectrometers in the dairy sector is increasing; however, little information is currently available on these applications and instrument performance. As a result, this review focuses on recent developments of handheld and portable NIR devices and its latest applications in the field of dairy, including chemical composition, on-site quality detection, and safety assurance (i.e., adulteration) in milk, cheese and dairy powders. Comparison of model performance between handheld and bench-top NIR spectrometers is also given. Lastly, challenges of current handheld/portable devices and future trends on implementing these devices in the dairy sector is discussed.

Monitoring Viscosity and Total Solids Content of Milk Protein Concentrate Using an Inline Acoustic Flowmeter at Laboratory Scale.

Control of milk concentrate viscosity and total solids (TS) content prior to spray drying can improve dairy ingredient manufacture. However, the availability of hygienic and appropriately pressure rated process viscometers for inline monitoring of viscosity is limited. An acoustic flowmeter (FLOWave) is an inline process analytical technology (PAT) tool that measures changes in acoustic signals in response to changes in liquid properties (i.e., acoustic transmission (AT), acoustic impedance (AI), temperature and volume flowrate). In this study, an acoustic flowmeter is evaluated as an inline PAT tool for monitoring viscosity of milk protein concentrate (MPC85), protein and TS content of (MPC85), and standardised MPC (sMPC). Laboratory scale experiments were carried out at 45 °C for five different concentrations (4-21%) of MPC85 and sMPC. Results showed that AT decreased with an increase in MPC85 viscosity (e.g., AT was 98.79 ± 0.04% and 86.65 ± 0.17% for 4% and 21% TS content, respectively). Non-linear regression was carried out to develop a relationship between AT and offline viscosity (R2 (coefficient of determination) value = 0.97 and standard error of prediction = 1.86 mPa·s). AI was observed to increase at higher protein and TS content which was dependent on protein to total solid ratio (P_TSR). Multiple linear regression was carried out to develop the relationship between AI, protein content, TS content and P_TSR. Results demonstrated that AI could be used to monitor the protein and TS content of milk protein concentrate (R2 > 0.96). Overall this study demonstrated the potential of an inline acoustic flowmeter for monitoring process viscosity, protein and TS during dairy concentrate processing.

State of the art in gluten-free research.

Celiac disease (CD) is widespread and is often under diagnosed. It can affect a variety of genetically susceptible people from the young to the old. Presently, the only treatment for celiac patients is lifelong avoidance of any food, drink, sauce, or dressing containing gluten. Scientists and technologists continue in their quest to improve the quality of gluten-free products. Their main goal is to create a product of a similar standard to the gluten-containing products, currently on the market. However, the quality of these products still tends to be poor. Bread products have a low volume, pale crust, crumbly texture, bland flavor and a high rate of staling. Other gluten-free products contain minimal nutrition and substandard product characteristics, for example, pasta having an inferior texture, sauces which separate more easily. The main focus of this review is to discuss the most recent advances in gluten-free research which have arisen between the years 2011 and 2013. In particular, the manuscript focuses on ingredients and processing methods which have been documented to develop or improve the processing characteristics and nutritional properties of gluten-free products.

The rheology, microstructure and sensory characteristics of a gluten-free bread formulation enhanced with orange pomace.

The present manuscript studied a previously optimised gluten-free bread formulation containing 5.5% orange pomace (OP) in relation to the batter characteristics (i.e. pre-baking), microstructure (of the flours, batter and bread) and sensory characteristics of the bread. Rheology, RVA and mixolab results illustrated that orange pomace improved the robustness of the gluten-free batter and decreased the occurrence of starch gelatinisation. This was confirmed from the confocal laser scanning microscopy (CLSM) images, which showed potato starch granules to be more expanded in the control batter when compared to the sample containing orange pomace. Starch granules were also observed to be more enlarged and swollen in the CLSM bread images, suggesting a higher level of gelatinisation occurred in the control sample. Sensory analysis was carried out on the optimised and control bread; panellists scored the flavour, crumb appearance and overall acceptability of the OP-containing breads comparable to the control.