Preliminary evaluation of endogenous milk fluorophores as tracer molecules for curd syneresis

Rapid Concentration and Detection of Bacteria in Milk Using a Microfluidic Surface Acoustic Wave Activated Nanosieve

Rapid detection of microbes is a key feature for monitoring food quality. Unfortunately, current detection systems rely on labor-intensive and time-consuming lab-based processes that are not suitable for point-of-interest applications and typically require several days before results are available. Here, we demonstrate a microfluidic system capable of rapidly concentrating, fluorescent staining, and detecting bacteria in unprocessed complex biological media such as milk. This concentration is done using a surface acoustic wave-driven microfluidic device which operates based on the Bjerknes force, a force generated on one particle by another in its close proximity. We exploit this effect by exciting a tightly packed bed of 50 μm polystyrene microparticles temporarily with surface acoustic waves within a microfluidic device to capture and release bacterial cells on demand. The bacterial cells are fluorescently stained during capture and then detected using fluorescence microscopy upon release. This device offers a high capturing efficiency (>80%) and a 34 Colony Forming Units (CFU)/mL limit of detection, which is 1 order of magnitude below that of plate counting at 30 CFU per standard 100 μL plate (or 300 CFU/mL). This can be attained in just 1 h of processing at 10 μL/min. With this system, we demonstrate that bacterial detection from extremely low concentration samples down to the order of ∼10 CFU/mL is possible without requiring any additional external pre- or postprocessing.

The impact of heat treatment of bovine milk on gastric emptying and nutrient appearance in peripheral circulation in healthy females: a randomized controlled trial comparing pasteurized and ultra-high temperature milk

BACKGROUND

Heat treatments of dairy, including pasteurization and ultra-high temperature (UHT) processing, alter milk macromolecular structures, and ultimately affect digestion. In vitro, animal, and human studies show faster nutrient release or circulating appearance after consuming UHT milk (UHT-M) compared with pasteurized milk (PAST-M), with a faster gastric emptying (GE) rate proposed as a possible mechanism.

OBJECTIVES

To investigate the impact of milk heat treatment on GE as a mechanism of faster nutrient appearance in blood. We hypothesized that GE and circulating nutrient delivery following consumption would be faster for UHT-M than PAST-M.

METHODS

In this double-blind randomized controlled cross-over trial, healthy female (n = 20; 27.3 ± 1.4 y, mean ± SD) habitual dairy consumers, consumed 500 mL of either homogenized bovine UHT-M or PAST-M (1340 compared with 1320 kJ). Gastric content volume (GCV) emptying half-time (T50) was assessed over 3 h by magnetic resonance imaging subjective digestive symptoms, plasma amino acid, lipid and B vitamin concentrations, and gastric myoelectrical activity were measured over 5 h.

RESULTS

Although GCV T50 did not differ (102 ± 7 min compared with 89 ± 8 min, mean ± SEM, UHT-M and PAST-M, respectively; P = 0.051), GCV time to emptying 25% of the volume was 31% longer following UHT-M compared with PAST-M (42 ± 2 compared with 32 ± 4 min, P = 0.004). Although GCV remained larger for a longer duration following UHT-M (treatment × time interaction, P = 0.002), plasma essential amino acid AUC was greater following UHT-M than PAST-M (55,324 ± 3809 compared with 36,598 ± 5673 μmol·min·L-1, P = 0.006). Heat treatment did not impact gastric myoelectrical activity, plasma appetite hormone markers or subjective appetite scores.

CONCLUSIONS

Contrary to expectations, GE was slower with UHT-M, yet, as anticipated, aminoacidemia was greater. The larger GCV following UHT-M suggests that gastric volume may poorly predict circulating nutrient appearance from complex food matrices. Dairy heat treatment may be an effective tool to modify nutrient release by impacting digestion kinetics.

CLINICAL TRIAL REGISTRY

www.anzctr.org.au (ACTRN12620000172909).

Intrinsic Fluorescence Markers for Food Characteristics, Shelf Life, and Safety Estimation: Advanced Analytical Approach

Food is a complex matrix of proteins, fats, minerals, vitamins, and other components. Various analytical methods are currently used for food testing. However, most of the used methods require sample preprocessing and expensive chemicals. New analytical methods are needed for quick and economic measurement of food quality and safety. Fluorescence spectroscopy is a simple and quick method to measure food quality, without sample preprocessing. This technique has been developed for food samples due to the application of a front-face measuring setup. Fluorescent compounds-fluorophores in the food samples are highly sensitive to their environment. Information about molecular structure and changes in food samples is obtained by the measurement of excitation-emission matrices of the endogenous fluorophores and by applying multivariate chemometric tools. Synchronous fluorescence spectroscopy is an advantageous screening mode used in food analysis. The fluorescent markers in food are amino acids tryptophan and tyrosine; the structural proteins collagen and elastin; the enzymes and co-enzymes NADH and FAD; vitamins; lipids; porphyrins; and mycotoxins in certain food types. The review provides information on the principles of the fluorescence measurements of food samples and the advantages of this method over the others. An analysis of the fluorescence spectroscopy applications in screening the various food types is provided.

Front-Face Fluorimeter for the Determination of Cutting Time of Cheese Curd

The yield of product (cheese) during the cheese-making process depends on the cutting time of the cheese curd. However, the determination of optimal cutting time on an industrial scale is difficult as current standard methods are destructive or analyse only small volumes and not the entire milk to be curdled into cheese. This paper presents a novel front-face fluorimeter (FFF) that is designed to be immersed into a milk batch to enable the determination of the cutting time of cheese curd without the destruction of the sample. The FFF sensor signal corresponds to physical changes in milk during cheese formation and has high predictive power (r > 0.85) and good accuracy (RSE = 30%, considering daily variation between milk samples). The performance of the presented fluorimeter was on par with standard rheological and Berridge methods.

Control and Monitoring of Milk Renneting Using FT-NIR Spectroscopy as a Process Analytical Technology Tool

Failures in milk coagulation during cheese manufacturing can lead to decreased yield, anomalous behaviour of cheese during storage, significant impact on cheese quality and process wastes. This study proposes a Process Analytical Technology approach based on FT-NIR spectroscopy for milk renneting control during cheese manufacturing. Multivariate Curve Resolution optimized by Alternating Least Squares (MCR-ALS) was used for data analysis and development of Multivariate Statistical Process Control (MSPC) charts. Fifteen renneting batches were set up varying temperature (30, 35, 40 °C), milk pH (6.3, 6.5, 6.7), and fat content (0.1, 2.55, 5 g/100 mL). Three failure batches were also considered. The MCR-ALS models well described the coagulation processes (explained variance ≥99.93%; lack of fit <0.63%; standard deviation of the residuals <0.0067). The three identified MCR-ALS profiles described the main renneting phases. Different shapes and timing of concentration profiles were related to changes in temperature, milk pH, and fat content. The innovative implementation of MSPC charts based on T² and Q statistics allowed the detection of coagulation failures from the initial phases of the process.

Front-face fluorescence spectroscopy combined with chemometrics to detect high proteinaceous matter in milk and whey ultrafiltration permeate

Proteinaceous matter can leak into the permeate stream during ultrafiltration (UF) of milk and whey and lead to financial losses. Although manufacturers can measure protein content in the finished permeate powders, there is currently no rapid monitoring tool during UF to identify protein leak. This study applied front-face fluorescence spectroscopy (FFFS) and chemometrics to identify the fluorophore of interest associated with the protein leak, develop predictive models to quantify true protein content, and classify the types of protein leak in permeate streams. Crude protein (CP), nonprotein nitrogen (NPN), true protein (TP), tryptone-equivalent peptide (TEP), α-lactalbumin (α-LA), and β-lactoglobulin (β-LG) contents were measured for 37 lots of whey permeate and 29 lots of milk permeate from commercial manufacturers. Whey permeate contained more TEP than did milk permeate, whereas milk permeate contained more α-LA and β-LG than did whey permeate. The types of protein leak were thus identified for predictive model development. Based on excitation-emission matrix (EEM) of high- and low-TP permeates, tryptophan excitation spectra were collected for predictive model development, measuring TP content in permeate. With external validation, a useful model for quality control purposes was developed, with a root mean square error of prediction of 0.22% (dry basis) and a residual prediction deviation of 2.8. Moreover, classification models were developed using partial least square discriminant analysis. These classification methods can detect high TP level, high TEP level, and presence of α-LA or β-LG with 83.3%, 84.8%, and 98.5% cross-validated accuracy, respectively. This method showed that FFFS and chemometrics can rapidly detect protein leaks and identify the types of protein leak in UF permeate. Implementation of this method in UF processing plants can reduce financial loss from protein leaks and maintain high-quality permeate production.

Identification of cow, buffalo, goat and ewe milk species in fermented dairy products using synchronous fluorescence spectroscopy

In the dairy industry, substitution of high priced milk species with low priced ones is a common practice, and determination of milk species is critical. In this study, synchronous fluorescence spectroscopy (SFS) method was developed for identification of milk species in fermented dairy products (yoghurt and cheese). Three partial least square-discriminant analysis models were developed in order to identify pure-mixed samples, milk species and binary mixture type, and partial least square (PLS) model was utilized to quantify the mixing ratio in binary mixtures. PLS models used for yoghurt and cheese samples showed that detection limits of adulteration were below 3.3%. Apart from the buffalo-cow yoghurt and goat-cow cheese, precision of the measurements was found to be below 6.2. It can be said that SFS technique is applicable on yoghurt and cheese samples as it's a less destructive and a less costly method compared to DNA and protein based conventional methods.