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

A Systematic Review of Spectroscopic Techniques for Detecting Milk Adulteration

Milk adulteration is a crucial worldwide concern that endangers food safety and public health, as it involves the deliberate tampering with milk by adding foreign substances or removing essential nutrients, often to boost profits or hinder microbial growth. Traditional detection methods frequently lack the sensitivity and speed required to identify adulterants within milk's complex matrix. This systematic review critically examines the application of spectroscopic techniques for detecting milk adulteration, focusing on Nuclear Magnetic Resonance (NMR), Infrared (IR) Spectroscopy, Raman Spectroscopy, Ultraviolet-Visible (UV-Vis) Spectroscopy, Mass Spectrometry, Laser-Based Techniques, Dielectric Spectroscopy, and X-Ray Spectroscopy. Each technique's principles, advantages, limitations, and specific applications in identifying adulterants, such as water, urea, melamine, added sugars, fats, preservatives, and heavy metals are discussed. The review highlights how these methods offer rapid, non-destructive, and sensitive analysis, enhancing the ability to detect adulterants at molecular levels. Despite advancements, challenges persist, including the complexity and natural variability of milk composition, high costs of advanced equipment, need for specialized expertise, and lack of standardized protocols. Future directions emphasize developing portable and cost-effective spectroscopic devices, integrating artificial intelligence and machine learning for advanced data analysis, and fostering international collaboration to establish standardized methodologies and comprehensive spectral databases. By addressing these challenges, spectroscopic techniques can be more widely implemented, ultimately safeguarding public health, ensuring the integrity of dairy products, and maintaining consumer trust in the global food supply chain.

Identification and quantification of goat milk adulteration using mid-infrared spectroscopy and chemometrics

The fraudulent adulteration of goat milk with cheaper and more available milk of other species such as cow milk is occurrence. The aims of the present study were to investigate the effect of goat milk adulteration with cow milk on the mid-infrared (MIR) spectrum and further evaluate the potential of MIR spectroscopy to identify and quantify the goat milk adulterated. Goat milk was adulterated with cow milk at 5 different levels including 10%, 20%, 30%, 40%, and 50%. Statistical analysis showed that the adulteration had significant effect on the majority of the spectral wavenumbers. Then, the spectrum was preprocessed with standard normal variate (SNV), multiplicative scattering correction (MSC), Savitzky-Golay smoothing (SG), SG plus SNV, and SG plus MSC, and partial least squares discriminant analysis (PLS-DA) and partial least squares regression (PLSR) were used to establish classification and regression models, respectively. PLS-DA models obtained good results with all the sensitivity and specificity over 0.96 in the cross-validation set. Regression models using raw spectrum obtained the best result, with coefficient of determination (R2), root mean square error (RMSE), and the ratio of performance to deviation (RPD) of cross-validation set were 0.98, 2.01, and 8.49, respectively. The results preliminarily indicate that the MIR spectroscopy is an effective technique to detect the goat milk adulteration with cow milk. In future, milk samples from different origins and different breeds of goats and cows should be collected, and more sophisticated adulteration at low levels should be further studied to explore the potential and effectiveness of milk mid-infrared spectroscopy and chemometrics.

Simultaneous Detection of Eight Dairy-Derived Components Using Double-Tube Multiplex qPCR Based TaqMan Probe

The authentication of milk and dairy products has great significance for food fraud. The present investigation entailed the development of a novel method that amalgamates the double-tube approach with multiplex real-time polymerase chain reaction (PCR) technology, incorporating TaqMan probes, to facilitate the high-throughput screening and detection of animal-derived constituents within milk and dairy products. Eight dairy-derived animal-specific primers and probes were designed for the mitochondrial cytochrome b (Cytb) gene of eight dairy products, including cow, buffalo, yak, goat, sheep, horse, donkey, and camel. Through the developed double-tube detection assays, the above eight targets could be simultaneously identified with a detection limit of 0.00128-0.0064 ng/μL. The multiplex qPCR assay was effectively validated using simulated adulterated samples with different mixing ratios and demonstrated a detection limit of 0.1%. Upon analysis of 54 commercially available dairy products, a mislabeling rate of 33% was revealed. This method affords an efficacious means of detecting dairy product ingredients, thereby offering robust technical backing for market oversight and regulatory enforcement of milk and dairy products.

Oligosaccharide profiles as potential biomarkers for detecting adulteration of caprine dairy products with bovine dairy products

Adulteration of caprine dairy products raises concerns among consumers. This study aimed to identify the differences in oligosaccharide profiles of caprine dairy products, including raw milk, colostrum powder, and lactose powder, and their corresponding bovine dairy products, and provide new insights for detecting adulteration of bovine dairy products in caprine dairy products. Twenty-seven oligosaccharides were detected in caprine and bovine dairy products. The principal component analysis plot of the oligosaccharide profiles clearly differentiated among the six types of dairy products. Specific oligosaccharides that were most distinctive for caprine and bovine dairy products were identified. Lacto-N-triose (LNTri) could be used as a potential biomarker for distinguishing caprine milk from bovine milk, caprine colostrum powder from bovine colostrum powder, and caprine lactose powder from bovine lactose powder. The results demonstrated that oligosaccharides could be used as biomarkers for detecting bovine dairy products in caprine dairy products, especially caprine lactose powder.

Synchronous Front-Face Fluorescence Spectra: A Review of Milk Fluorophores

Milk is subjected to different industrial processes, provoking significant physicochemical modifications that impact milk's functional properties. As a rapid and in-line method, front-face fluorescence can be used to characterize milk instead of conventional analytical tests. However, when applying fluorescence spectroscopy for any application, it is not always necessary to determine which compound is responsible for each fluorescent response. In complex matrixes such as milk where several variables are interdependent, the unique identification of compounds can be challenging. Thus, few efforts have been made on the chemical characterization of milk' fluorescent spectrum and the current information is dispersed. This review aims to organize research findings by dividing the milk spectra into areas and concatenating each area with at least one fluorophore. Designations are discussed by providing specific information on the fluorescent properties of each compound. In addition, a summary table of all fluorophores and references cited in this work by area is provided. This review provides a solid foundation for further research and could serve as a central reference.

Synchronous fluorescence detection of nitrite in meat products based on dual-emitting dye@MOF and its portable hydrogel test kit

A novel ratiometric fluorescent nanoprobe (Rh6G@UIO-66-NH2) was fabricated for efficient nitrite (NO2-) detection in the present study. When NO2- was introduced, it interacted with the amino groups on the surface of Rh6G@UIO-66-NH2, forming diazonium salts that led to the quenching of blue fluorescence. With this strategy, a good linear relationship between NO2- concentration and the fluorescent intensity ratio of the nanoprobe in the range of 1-100 μM was established, with a detection limit of 0.021 μM. This dual-readout nanosensor was applied to analyze the concentration of NO2- in real meat samples, achieving satisfactory recovery rates of 94.72-104.52%, highlighting the practical potential of this method. Furthermore, a portable Gel/Rh6G@UIO-66-NH2 hydrogel test kit was constructed for on-spot dual-mode detection of NO2-. This kit allows for convenient colorimetric analysis and fluorometric detection when used in conjunction with a smartphone. All the photos taken with the portable kit was converted into digital information using ImageJ software. It provides colorimetric and fluorescent visual detection of NO2- over a range of 0.1-1.5 mM, achieving a direct quantitative tool for NO2- identification. This methodology presents a promising strategy for NO2- detection and expands the application prospects for on-spot monitoring of food safety assessment.

High resolution melting is a useful tool to detect animal species sources of various milk types

Accurate identification of animal species sources in milk have become quite important due to adulteration of high-priced milk types in the dairy industry. To date, milk identification methods have mainly depended on biochemical properties or physical properties detected by spectroscopic methods. The current study aimed to develop an easy to use and sensitive DNA-based High resolution melting (HRM) assay to identify animal species and detect cross-adulteration of water buffalo, bovine, goat, sheep, camel and donkey milks. HRM compatible designed primer set, targeted mitochondrial region, successfully amplified the specific targeted region for six animal species DNA and showed a high degree of specificity based on nucleotide variations. Capillary electrophoresis analysis validated the specific amplicons and determined the amplicon lengths as 114 bp for bovine, goat, sheep, and camel, 115 bp for water buffalo, and 121 bp for donkey. HRM analysis showed a clear discrimination for water buffalo-bovine, camel-bovine and donkey-bovine adulteration down to 0.5%, and goat-sheep adulteration down to 1% in the milk admixtures. The efficacy of the method was also confirmed by its standard curve with a very high correlation coefficient In conclusion, the designed HRM assay allows for the rapid, sensitive and cost-effective authentication of milk and dairy products.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-023-05705-3.

Mid-Infrared (MIR) Spectroscopy for the quantitative detection of cow’s milk in buffalo milk

In Italy, buffalo mozzarella is a largely sold and consumed dairy product. The fraudulent adulteration of buffalo milk with cheaper and more available milk of other species is very frequent. In the present study, Fourier transform infrared spectroscopy (FTIR), in combination with multivariate analysis by partial least square (PLS) regression, was applied to quantitatively detect the adulteration of buffalo milk with cow milk by using a fully automatic equipment dedicated to the routine analysis of the milk composition. To enhance the heterogeneity, cow and buffalo bulk milk was collected for a period of over three years from different dairy farms. A total of 119 samples were used for the analysis to generate 17 different concentrations of buffalo-cow milk mixtures. This procedure was used to enhance variability and to properly randomize the trials. The obtained calibration model showed an R² ≥ 0.99 (R²cal. = 0.99861; root mean square error of cross-validation [RMSEC] = 2.04; R²val. = 0.99803; root mean square error of prediction [RMSEP] = 2.84; root mean square error of cross-validation [RMSECV] = 2.44) suggesting that this method could be successfully applied in the routine analysis of buffalo milk composition, providing rapid screening for possible adulteration with cow’s milk at no additional cost.

Fluorescence-based characterisation of selected edible insect species: Excitation emission matrix (EEM) and parallel factor (PARAFAC) analysis

Fluorescence spectroscopy coupled with chemometric tools is a powerful analytical method, largely used for rapid food quality and safety evaluations. However, its potential has not yet been explored in the novel food sector. In the present study, excitation emission matrices (EEMs) of 15 insect powders produced by milling insects belonging to 5 Orthoptera species (Acheta domesticus, Gryllus assimilis, Gryllus bimaculatus, Locusta migratoria, Schistocerca gregaria) from 3 different origins were investigated. Parallel factor (PARAFAC) analysis performed on the overall averaged dataset was validated for five components, highlighting the presence of five different fluorescence peaks. The presence of these peaks was confirmed on each species, suggesting that fluorescence compounds of edible insects are the same in several species. PARAFAC analysis performed on the overall averaged dataset after alternatively adding the EEM recorded from one standard compound allowed to speculate that edible insects fluorescence raises from mixtures of: tryptophan + tyrosine (PARAFAC component-1), tryptophan + tyrosine + tocopherol (PARAFAC component-2), collagen + pyridoxine + pterins (PARAFAC component-3). This study suggests that fluorescence spectroscopy may represent a powerful method for investigating composition and quality of insect-based foods.

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Fluorescence landscape of edible insects comprises of 5 different peaks.

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Similar fluorescence compounds are present among several Orthoptera species.

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Fluorescence peaks of edible insects result from several chemical molecules.

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Fluorescence intensity of edible insects depends on their species and origin.

Rapid detection of sulfamethazine and ofloxacin residues in duck meat using synchronous fluorescence spectroscopy coupled with chemometric methods

Rapid detection of antibiotic residues in duck meat is of great significance for strengthening food safety and quality supervision of duck meat and fighting against inferior products in the duck meat market. The objective of the current paper was to evaluate the potential of synchronous fluorescence spectroscopy (SFS) coupled with chemometric methods for the rapid detection of sulfamethazine (SM2) and ofloxacin (OFL) residues in duck meat.The SFS spectral data from duck meat containing different concentrations of SM2 and OFL were preprocessed by baseline offset. The detection conditions, including the adding amounts of β-mercaptoethanol solution and o-phthalaldehyde solution, as well as the reaction time, were optimized by a single factor experiment for obtaining a better detection effect, and their optimal values were 400 μL , 25 μL , and 40 min, respectively. By comparing 2 chemometric models based on peak-height algorithm and peak-area algorithm, the prediction model based on peak-height algorithm was a better quantitative model with correlation coefficient for the prediction set (Rp) of 0.9031 and 0.9981, the root mean error for the prediction set (RMSEP) of 7.9509 and 0.5267 mg/kg, recovery of 81.7 to 155.1% and 96.4 to 111.2%, and relative standard deviation (RSD) of 4.1 to 6.7% and 2.9 to 6.8% to predict SM2 and OFL residues in duck meat, respectively. Overall, the results of this investigation showed that SFS technique was an effective and rapid tool for the detection of SM2 and OFL residues in duck meat.

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.

Kashk with caper (Capparis spinosa L.) extract: quality during storage

Introduction. Dairy products are an important part of the diet. Kashk is a traditional Iranian dairy product rich in protein. However, kashk has a high water content and is a good medium for the growth of microorganisms. The aim of this study was to investigate the effect of the ethanolic extract of caper fruit (Capparis spinosa L.) on reducing the microbial burden of kashk. Study objects and methods. The study objects were three kashk samples. The control sample was kashk without caper extract. Two experimental samples included kashk with 0.211 and kashk with 0.350 mg/mL of ethanolic caper extract. All the samples were tested for pH, sensory and antioxidant properties, colorimetric parameters, and microbial population. The experiments were performed on days 0, 7, 14, 21 and 28 of storage. Results and discussion. The results showed all the samples had pH within the standard values during the entire shelf life (3.96 to 4.53). The samples with 0.350 mg/mL of the caper extract had the lowest EC50 (12.05 μg/mL), i.e. the highest antioxidant activity. The increased concentration of the extract and storage time resulted in a decrease in L* and increase in b*, while did not impact a*. Staphylococcus aureus population increased more rapidly than Clostridium botulinum during the storage time, and the overall sensory acceptability of the kashk samples on days 0 and 7 received the highest score. Conclusion. The kashk samples containing 0.350 mg/mL of caper extract had an improved antimicrobial, antioxidant and antifungal properties and can be produced and consumed as a new functional product.

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance. Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud. It is the aim of the present manuscript to review the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions will also be discussed.

Discrimination of bovine milk from non-dairy milk by lipids fingerprinting using routine matrix-assisted laser desorption ionization mass spectrometry

An important sustainable development goal for any country is to ensure food security by producing a sufficient and safe food supply. This is the case for bovine milk where addition of non-dairy milks such as vegetables (e.g., soya or coconut) has become a common source of adulteration and fraud. Conventionally, gas chromatography techniques are used to detect key lipids (e.g., triacylglycerols) has an effective read-out of assessing milks origins and to detect foreign milks in bovine milks. However, such approach requires several sample preparation steps and a dedicated laboratory environment, precluding a high throughput process. To cope with this need, here, we aimed to develop a novel and simple method without organic solvent extractions for the detection of bovine and non-dairy milks based on lipids fingerprint by routine MALDI-TOF mass spectrometry (MS). The optimized method relies on the simple dilution of milks in water followed by MALDI-TOF MS analyses in the positive linear ion mode and using a matrix consisting of a 9:1 mixture of 2,5-dihydroxybenzoic acid and 2-hydroxy-5-methoxybenzoic acid (super-DHB) solubilized at 10 mg/mL in 70% ethanol. This sensitive, inexpensive, and rapid method has potential for use in food authenticity applications.

Robust Classification of Tea Based on Multi-Channel LED-Induced Fluorescence and a Convolutional Neural Network

A multi-channel light emitting diode (LED)-induced fluorescence system combined with a convolutional neural network (CNN) analytical method was proposed to classify the varieties of tea leaves. The fluorescence system was developed employing seven LEDs with spectra ranging from ultra-violet (UV) to blue as excitation light sources. The LEDs were lit up sequentially to induce a respective fluorescence spectrum, and their ability to excite fluorescence from components in tea leaves were investigated. All the spectral data were merged together to form a two-dimensional matrix and processed by a CNN model, which is famous for its strong ability in pattern recognition. Principal component analysis combined with k-nearest-neighbor classification was also employed as a baseline for comparison. Six grades of green tea, two types of black tea and one kind of white tea were verified. The result proved a significant improvement in accuracy and showed that the proposed system and methodology provides a fast, compact and robust approach for tea classification.