Recent developments on rapid detection of main constituents in milk: a review

Using a random laser to measure the content of protein in skim milk

The luminescence of skim milk samples with distinct protein content doped with rhodamine B was investigated. The samples were excited by a nanosecond laser tuned at 532 nm, and the emission was characterized as a random laser. Its features were analyzed as a function of the protein aggregate content. The results showed a linear correlation between the random laser peak intensity and the protein content. This paper proposes a rapid detection photonic method to evaluate the protein content in skim milk based on the intensity of the random laser emission.

Analysis of milk with liquid chromatography–mass spectrometry: a review

As a widely consumed foodstuff, milk and dairy products are increasingly studied over the years. At the present time, milk profiling is used as a benchmark to assess the properties of milk. Modern biomolecular mass spectrometers have become invaluable to fully characterize the milk composition. This review reports the analysis of milk and its components using liquid chromatography coupled with mass spectrometry (LC–MS). LC–MS analysis as a whole will be discussed subdivided into the major constituents of milk, namely, lipids, proteins, sugars and the mineral fraction.

Lactitol and β-cyclodextrin alleviate the intensity of goaty flavor

BACKGROUND

Goat milk has balanced nutritional composition, is conducive to digestion and absorption, and does not easily lead to allergic reactions. However, the special goaty flavor in milk has seriously affected consumer acceptance. It is imperative to alleviate the goaty flavor in a safe and efficient way.

RESULTS

This study indicated that the supplementation of 6 g kg^-1 β-cyclodextrin or 8 g kg^-1 lactitol in goat milk significantly alleviated goaty flavor and improved sensory characteristics. Furthermore, the supplementation of β-cyclodextrin and lactitol had a synergistic effect in reducing the content of free fatty acids that cause goaty flavor. The content of caproic acid (C₆ H₁₂ O₂ ), octanoic acid (C₈ H₆ O₂ ), and decanoic acid (C₁₀ H₂₀ O₂ ) decreased by 42.46%, 39.45%, and 46.41%, respectively, after a combined group was supplemented with 6 g kg^-1 β-cyclodextrin and 7 g kg^-1 lactitol, which was significantly lower than in groups given β-cyclodextrin or lactitol individually.

CONCLUSION

This study provides a novel and effective approach to alleviate goaty flavor and promote the competitiveness of goat milk products. © 2022 Society of Chemical Industry.

Nucleic acid amplification-based strategy to detect foodborne pathogens in milk: a review

Milk contaminated with trace amounts of foodborne pathogens can considerably threaten food safety and public health. Therefore, rapid and accurate detection techniques for foodborne pathogens in milk are essential. Nucleic acid amplification (NAA)-based strategies are widely used to detect foodborne pathogens in milk. This review article covers the mechanisms of the NAA-based detection of foodborne pathogens in milk, including polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), recombinase polymerase amplification (RPA), rolling circle amplification (RCA), and enzyme-free amplification, among others. Key factors affecting detection efficiency and the advantages and disadvantages of the above techniques are analyzed. Potential on-site detection tools based on NAA are outlined. We found that NAA-based strategies were effective in detecting foodborne pathogens in milk. Among them, PCR was the most reliable. LAMP showed high specificity, whereas RPA and RCA were most suitable for on-site and in-situ detection, respectively, and enzyme-free amplification was more economical. However, factors such as sample separation, nucleic acid target conversion, and signal transduction affected efficiency of NAA-based strategies. The lack of simple and effective sample separation methods to reduce the effect of milk matrices on detection efficiency was noteworthy. Further research should focus on simplifying, integrating, and miniaturizing microfluidic on-site detection platforms.

Qualitative identification of mature milk adulteration in bovine colostrum using noise-reduced dielectric spectra and linear model

BACKGROUND

The rapid and accurate identification of colostrum, a strong non-homogeneous food, remains a challenge. In the present study, the dielectric spectra including the dielectric constant (ε') and loss factor (ε″) of 154 colostrum samples adulterated with 0-50% mature milk were measured from 20 to 4500 MHz.

RESULTS

The results showed that the noise-reducing spectral preprocessing, including Savitzky-Golay (S-G), second derivative (SD), and S-G + SD, was significantly better than scattering-eliminating, including standard normal variate (SNV), multiplicative scatter correction (MSC), and SNV + MSC. The combination of S-G and SD was the best. Principal component analysis results demonstrated that dielectric spectroscopy is less susceptible to the inhomogeneity of colostrum and can be used to identify doped colostrum. The identification performance of linear models was better than that of non-linear models. The established linear discriminant analysis model based on full spectra had the best accuracy rates of 99.14% and 97.37% in the calibration and validation sets, respectively. Confirmatory tests on samples from different sources confirmed the satisfactory robustness of the proposed model.

CONCLUSION

We found that the main unfavorable effect on the identification based on dielectric spectroscopy was noise interference, rather than scattering effect caused by inhomogeneity of colostrum. The satisfactory results undoubtedly cast light on rapid detection of strongly non-homogeneous foods based on dielectric spectroscopy. © 2022 Society of Chemical Industry.

Protein engineering for electrochemical biosensors

The development of electrochemical biosensors has gained tremendous attention. Protein engineering has been applied for enhancing properties of native redox enzymes, such as selectivity, sensitivity, and stability required for applicable biosensors. This review highlights recent advances of protein engineering to improve enzymatic catalysis of biosensors, facilitate electron transfer and enzyme immobilization, and construct allosteric protein biosensors. The pros and cons of different protein engineering strategies are briefly discussed, and perspectives are further provided.

The Promise and Challenges of Determining Recombinant Bovine Growth Hormone in Milk

Recombinant bovine growth hormone (rbGH) is produced in large quantities and widely used in a number of countries worldwide to stimulate milk production in dairy animals. The use of this compound in animal production is strictly regulated by food safety directives in force, in particular in the European Union (EU). Although analytical strategies for the detection of rbGH in blood have been successfully reported over the past 15 years, they do not fully answer the expectations of either competent authorities or industrials that would expect measuring its occurrence directly in the milk. As a matrix of excretion but also of consumption, milk appears indeed as the matrix of choice for detecting the use of rbGH in dairy animals. It also allows large volumes to be collected without presenting an invasive character for the animal. However, rbGH detection in milk presents several challenges, mainly related to the sensitivity required for its detection in a complex biological matrix. This review article presents the specific difficulties associated with milk and provides an overview of the analytical strategies reported in the literature and whether they concern indirect or direct approaches to the detection of rbGH administration to animals, with applications either for screening or confirmation purposes.

On-Site Measurement of Fat and Protein Contents in Milk Using Mobile NMR Technology

Robust and easy-to-use NMR sensor technology is proposed for accurate, on-site determination of fat and protein contents in milk. The two parameters are determined using fast consecutive ¹H and ³⁵Cl low-field NMR experiments on milk samples upon the 1:1 addition of a low-cost contrast solution. Reliable and accurate measurements are obtained without tedious calibrations and the need for extensive database information and may readily be conducted by non-experts in production site environments. This enables on-site application at farms or dairies, or use in laboratories harvesting significant reductions in costs and time per analysis as compared to wet-chemistry analysis. The performance is demonstrated for calibration samples, various supermarket milk products, and raw milk samples, of which some were analyzed directly in the milking room. To illustrate the wide application range, the supermarket milk products included both conventionally/organically produced, lactose-free milk, cow's, sheep's and goat's milk, homogenized and unhomogenized milk, and a broad nutrient range (0.1-9% fat, 1-6% protein). Excellent agreement between NMR measurements and reference values, without corrections or changes in calibration for various products and during extensive periods of experiment conduction (4 months) demonstrates the robustness of the procedure and instrumentation. For the raw milk samples, correlations between NMR and IR, NMR and wet-chemistry, as well as IR and wet-chemistry results, show that NMR, in terms of accuracy, compares favorably with the other methods.

Rapid detection and prediction of chloramphenicol in food employing label-free HAu/Ag NFs-SERS sensor coupled multivariate calibration

Considering growing food safety issues, hollow Au/Ag nano-flower (HAu/Ag NFs) nanosensor has been synthesized for label-free and ultrasensitive detection of chloramphenicol (CP) via integrating the surface-enhanced Raman scattering (SERS) and multivariate calibration. As the anisotropic plasmonic nanomaterials, HAu/Ag NFs had numerous nano-chink on their surface, which offered huge hotspots for analytes. CP generated a strong SERS signal while adsorbed on the surface of HAu/Ag NFs and noted excellent linearity with 1st derivative-competitive adaptive reweighted sampling-partial least squares (CARS-PLS) in the range of 0.0001-1000 µg/mL among the four applied multivariate calibrations. Additionally, CARS-PLS generated the lowest prediction error (RMSEP) of 0.089 and 0.123 µg/mL for milk and water samples, respectively, and any CARS-PLS model could be used for both samples according to T-test results (P > 0.05). The intra- and interday recovery for both samples were in the range of 92.62-96.74% with CV < 10%, suggested the proposed method has excellent accuracy and precision.

Lipid-soluble vitamins from dairy products: Extraction, purification, and analytical techniques

Milk and dairy products are considered as essential sources of lipid-soluble vitamins (LSVs) for human nutrition. Due to the lower concentrations, complexity, and instability of LSVs during extraction, their quantification remains challenging. This review focus on advances in the extraction and quantification of LSVs from different dairy products. Saponification, and liquid-liquid (LLE), solid-phase (SPE), and supercritical fluid (SFE) extraction methods, as well as dispersive liquid-liquid microextraction, are the most common techniques. Liquid chromatography-mass spectrophotometry (LC-MS) has unique advantages for LSVs determination and quantification due to its high sensitivity and specificity.

Mycobacterium avium subsp. paratuberculosis Proteome Changes Profoundly in Milk

Mycobacterium avium subspecies paratuberculosis (MAP) are detectable viable in milk and other dairy products. The molecular mechanisms allowing the adaptation of MAP in these products are still poorly understood. To obtain information about respective adaptation of MAP in milk, we differentially analyzed the proteomes of MAP cultivated for 48 h in either milk at 37 °C or 4 °C or Middlebrook 7H9 broth as a control. From a total of 2197 MAP proteins identified, 242 proteins were at least fivefold higher in abundance in milk. MAP responded to the nutritional shortage in milk with upregulation of 32% of proteins with function in metabolism and 17% in fatty acid metabolism/synthesis. Additionally, MAP upregulated clusters of 19% proteins with roles in stress responses and immune evasion, 19% in transcription/translation, and 13% in bacterial cell wall synthesis. Dut, MmpL4_1, and RecA were only detected in MAP incubated in milk, pointing to very important roles of these proteins for MAP coping with a stressful environment. Dut is essential and plays an exclusive role for growth, MmpL4_1 for virulence through secretion of specific lipids, and RecA for SOS response of mycobacteria. Further, 35 candidates with stable expression in all conditions were detected, which could serve as targets for detection. Data are available via ProteomeXchange with identifier PXD027444.

A 1D binary photonic crystal sensor for detecting fat concentrations in commercial milk

Our goal in this study is to design an efficient sensor to detect the fat volume in commercial milk. We used a one-dimensional binary photonic crystal to design the sensor and the Transfer Matrix Method to study theoretically its optical response as the refractive index of milk samples changes due to the change in fat concentration. We found that the proposed sensor is efficient in sensing the fat concentration in milk. The optimum defect layer thickness is found to be 1.20 μm and the sensitivity of the sensor improved as the angle of incidence of radiation increased up to 60°. Besides, we proposed an empirical formula that can be used to estimate the fat concentration in milk. The efficiency of our sensor is based on the quick response of the sensor to the changes in the fat concentration in milk. The output signal of the sensor would be processed in a signal processing unit that will give an accurate estimation of the fat concentration in milk. The sensor is easy to fabricate, cost-effective, and user-friendly.

Milk as a Complex Multiphase Polydisperse System: Approaches for the Quantitative and Qualitative Analysis

Milk is a product that requires quality control at all stages of production: from the dairy farm, processing at the dairy plant to finished products. Milk is a complex multiphase polydisperse system, whose components not only determine the quality and price of raw milk, but also reflect the physiological state of the herd. Today’s production volumes and rates require simple, fast, cost-effective, and accurate analytical methods, and most manufacturers want to move away from methods that use reagents that increase analysis time and move to rapid analysis methods. The review presents methods for the rapid determination of the main components of milk, examines their advantages and disadvantages. Optical spectroscopy is a fast, non-destructive, precise, and reliable tool for determination of the main constituents and common adulterants in milk. While mid-infrared spectroscopy is a well-established off-line laboratory technique for the routine quality control of milk, near-infrared technologies provide relatively low-cost and robust solutions suitable for on-site and in-line applications on milking farms and dairy production facilities. Other techniques, discussed in this review, including Raman spectroscopy, atomic spectroscopy, molecular fluorescence spectroscopy, are also used for milk analysis but much less extensively. Acoustic methods are also suitable for non-destructive on-line analysis of milk. Acoustic characterization can provide information on fat content, particle size distribution of fat and proteins, changes in the biophysical properties of milk over time, the content of specific proteins and pollutants. The basic principles of ultrasonic techniques, including transmission, pulse-echo, interferometer, and microbalance approaches, are briefly described and milk parameters measured with their help, including frequency ranges and measurement accuracy, are given.