In vivo confocal Raman spectroscopy: The window into the skin.

Development of in vivo confocal Raman spectroscopy (ICRS) methodology over the last 20 years has enabled previously unavailable capability to acquire molecular concentration gradients across the stratum corneum (SC), at the micron level and in a clinical setting. Professor Tony Rawlings has been a driving force in SC research for over 30 years, working with a wide range of teams across the world. Because a detailed knowledge of skin biochemistry was key to interpreting ICRS-acquired molecular concentration gradients, the authors formed a close working relationship with Professor Rawlings during the development of ICRS. This article, therefore, presents a summary of this process and how challenges raised by application of ICRS were tackled, towards the goal of validating the technique for clinical skin measurement.

Le développement de la méthodologie de spectroscopie confocale Raman in vivo (In vivo Confocal Raman Spectroscopy, ICRS) au cours des 20 dernières années a permis d'acquérir des gradients de concentration moléculaire dans l'ensemble du stratum corneum (SC), au niveau du micron et dans un contexte clinique, ce qui était impossible auparavant. Le professeur Tony Rawlings joue un rôle moteur dans la recherche sur le SC depuis plus de 30 ans et travaille avec de nombreuses équipes à travers le monde. Étant donné qu'une connaissance détaillée de la biochimie cutanée était essentielle à l'interprétation des gradients de concentration moléculaire acquis par l'ICRS, les auteurs ont établi une relation de travail étroite avec le professeur Rawlings pendant le développement de l'ICRS. Cet article présente donc un résumé de ce processus et de la manière dont les défis soulevés par l'application de l'ICRS ont été abordés dans le but de valider la technique de mesure clinique de la peau.

What defines dry skin? Correlating a range of skin hydration parameters with In Vivo Confocal Raman Spectroscopy.

OBJECTIVE: While there are a wide range of approaches for the assessment of skin hydration, it is not always clear how data from them relate to one another or to the skin itself. With the development of in vivo Confocal Raman Spectroscopy (ICRS), it has become possible to measure water concentration as a function of protein/depth within the stratum corneum (SC). This article reports a comparison between electrical skin hydration measures/visual/optical grading and water concentration profiles measured using ICRS, to better understand the relationship between these approaches. METHODS: SC hydration of lower-leg skin with varying degrees of dryness was assessed using visual grading (live and from digital images), Corneometer®, Visioscan and ICRS. In addition, a custom fingerprint sensor was used to image surface capacitance (as a surrogate of SC hydration), and SC barrier function was assessed using evaporimetry (to measure trans-epidermal water loss; TEWL). RESULTS: Significant correlations were observed between a number of different skin grading/measurement approaches and ICRS data. ICRS hydration profiles also revealed a region near the SC surface with a relatively flat water profile in dry skin subjects. CONCLUSIONS: The advent of quantitative in vivo analytical techniques such as ICRS, which can be used in a clinical setting, has enabled greater insight into more conventional approaches for assessing skin dryness. While traditional skin grading and biophysical methods for measuring skin hydration have varying degrees of correlation with one another, they also provide comparatively unique information about different regions within the SC. This should enable a more informed approach to product development in the future.

OBJECTIF: Bien qu'il existe un large éventail d'approches pour évaluer l'hydratation de la peau, la façon dont les données qui en résultent sont liées les unes aux autres ou à la peau elle­même n'est pas toujours claire. Avec le développement de la spectroscopie Raman confocale in vivo (ICRS), il est devenu possible de mesurer la concentration en eau en fonction du rapport protéine/profondeur au sein de la couche cornée (stratum corneum, SC). Cet article rapporte une comparaison entre les mesures électriques ou la classification visuelle/optique de l'hydratation de la peau et les profils de concentration en eau mesurés à l'aide de l'ICRS, afin de mieux comprendre la relation entre ces approches. MÉTHODES: L'hydratation du SC de la peau de la partie inférieure de la jambe avec différents degrés de sécheresse a été évaluée à l'aide d'une classification visuelle (en direct et à partir d'images numériques), du Corneometer®, du Visioscan et de l'ICRS. En outre, un capteur d'empreintes digitales personnalisé a été utilisé pour visualiser la capacité de surface (en tant que substitut de l'hydratation du SC) et la fonction de barrière du SC a été évaluée par évaporimétrie (pour mesurer la perte d'eau transépidermique ; trans­epidermal water loss, TEWL). RÉSULTATS: Des corrélations significatives ont été observées entre un certain nombre d'approches différentes de classification/mesure de la peau et les données ICRS. Les profils d'hydratation de l'ICRS ont également révélé une région près de la surface du SC ayant un profil d'eau relativement plat chez les sujets atteints de sécheresse cutanée. CONCLUSIONS: L'avènement de techniques d'analyse in vivo quantitatives telles que l'ICRS, qui peut être utilisée dans un contexte clinique, a permis de mieux comprendre les approches plus conventionnelles d'évaluation de la sécheresse cutanée. Bien que les méthodes traditionnelles de classification de la peau et les méthodes biophysiques de mesure de l'hydratation de la peau présentent des degrés de corrélation variables entre elles, elles fournissent également des informations comparativement uniques sur différentes régions au sein du SC. Cela devrait permettre une approche plus éclairée du développement de produits à l'avenir.

Inline Raman Spectroscopy Provides Versatile Molecular Monitoring for Platelet Extracellular Vesicle Purification with Anion-Exchange Chromatography.

Extracellular vesicles (EVs) are relatively recently discovered biological nanoparticles that mediate intercellular communication. The development of new methods for the isolation and characterization of EVs is crucial to support further studies on these small and structurally heterogenous vesicles. New scalable production methods are also needed to meet the needs of future therapeutic applications. A reliable inline detection method for the EV manufacturing process is needed to ensure reproducibility and to identify any possible variations in real time. Here, we demonstrate the use of an inline Raman detector in conjunction with anion exchange chromatography for the isolation of EVs from human platelets. Anion-exchange chromatography can be easily coupled with multiple inline detectors and provides an alternative to size-based methods for separating EVs from similar-sized impurities, such as lipoprotein particles. Raman spectroscopy enabled us to identify functional groups in EV samples and trace EVs and impurities in different stages of the process. Our results show a notable separation of impurities from the EVs during anion-exchange chromatography and demonstrate the power of inline Raman spectroscopy. Compared to conventional EV analysis methods, the inline Raman approach does not require hands-on work and can provide detailed, real-time information about the sample and the purification process.

Advanced Vibrational Spectroscopy and Bacteriophages Team Up: Dynamic Synergy for Medical and Environmental Applications.

Bacteriophages are emerging as a promising alternative in combating antibiotic-resistant bacteria amidst the escalating global antimicrobial resistance crisis. Recently, there has been a notable resurgence of interest in phages, prompting extensive research into their therapeutic potential. Beyond conventional microbiology and virology techniques, such as genomics and proteomics, novel phenotypic and chemical characterization methods are being explored. Among these, there is a growing interest in vibrational spectroscopy, especially in advanced modalities such as surface-enhanced Raman spectroscopy (SERS), tip-enhanced Raman spectroscopy (TERS), and atomic force microscopy-infrared spectroscopy (AFM-IR), which offer improved sensitivity and spatial resolution. This review explores the spectrum of uses of vibrational spectroscopy for bacteriophages, including its role in diagnostics, biosensing, phage detection, assistance in phage-based therapy, and advancing basic research.

SERS Platform for Integrated Enrichment, Isolation, and Identification of Multiple Respiratory Viruses in a Single Assay Using 3D Stereoscopic SERS Tags and Flocked Swabs.

Influenza (flu) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exhibit similar clinical symptoms, complicating the diagnosis and clinical management of these critical respiratory infections. Thus, there is an urgent need for rapid on-site detection technologies that can simultaneously detect SARS-CoV-2 and influenza A viruses. Here, we have developed the first platform that combines in situ sampling with immune swabs and multichannel surface-enhanced Raman spectroscopy (SERS) for simultaneous screening of these two respiratory viruses in a single assay. A seed-mediated growth method was used to assemble a number of silver spheres on the surface of Fe3O4@SiO2 spheres, which not only creates extensive Raman hotspots but also provides numerous sites for Raman signaling molecules, enhancing the sensing sensitivity. Integrating two specific Raman signaling molecules into the nanospheres allows for the parallel detection of both viruses, improving the efficiency of SERS signal read-out. Rapid quantitative screening of both SARS-CoV-2 and H1N1 is achievable within 15 min, with detection limits of 7.76, and 8.13 pg·mL-1 for their respective target proteins. The platform demonstrated excellent performance in testing and analyzing 98 clinical samples (SARS-CoV-2:50; influenza A:48), achieving sensitivities of 88.00, and 95.83% for SARS-CoV-2 and influenza A, respectively. Pearson's correlation analysis revealed a significant correlation with the clinical CT values (P < 0.0001), underscoring the great potential of this platform for the early, rapid, and simultaneous diagnostic discrimination of multiple pathogens.

Ultrasensitive Surface-Enhanced Raman Scattering Platform for Protein Detection via Active Delivery to Nanogaps as a Hotspot.

Surface-enhanced Raman scattering (SERS) is an attractive technique in molecular detection with high sensitivity and label-free characteristics. However, its use in protein detection is limited by the large volume of proteins, hindering its approach to the narrow spaces of hotspots. In this study, we fabricated a Au nanoTriangle plate Array on Gel (AuTAG) as an SERS substrate by attaching a Au nanoTriangle plate (AuNT) arrangement on a thermoresponsive hydrogel surface. The AuTAG acts as an actively tunable plasmonic device, on which the interparticle distance is altered by controlling temperature via changes in hydrogel volume. Further, we designed a Gel Filter Trapping (GFT) method as an active protein delivery strategy based on the characteristics of hydrogels, which can absorb water and separate biopolymers through their three-dimensional (3D) polymer networks. On the AuTAGs, fabricated with AuNTs modified with charged surface ligands to prevent the nonspecific adsorption of analytes to particles, the GFT method helped the delivery of proteins to hotspot areas on the AuNT arrangement. This combination of a AuTAG substrate and the GFT method enables ultrahigh sensitivity for protein detection by SERS up to a single-molecule level as well as a wide quantification concentration range of 6 orders due to their geometric advantages.

Probing Biological Nitrogen Fixation in Legumes Using Raman Spectroscopy.

Biological nitrogen fixation (BNF) by symbiotic bacteria plays a vital role in sustainable agriculture. However, current quantification methods are often expensive and impractical. This study explores the potential of Raman spectroscopy, a non-invasive technique, for rapid assessment of BNF activity in soybeans. Raman spectra were obtained from soybean plants grown with and without rhizobia bacteria to identify spectral signatures associated with BNF. δN15 isotope ratio mass spectrometry (IRMS) was used to determine actual BNF percentages. Partial least squares regression (PLSR) was employed to develop a model for BNF quantification based on Raman spectra. The model explained 80% of the variation in BNF activity. To enhance the model's specificity for BNF detection regardless of nitrogen availability, a subsequent elastic net (Enet) regularisation strategy was implemented. This approach provided insights into key wavenumbers and biochemicals associated with BNF in soybeans.

Controllable Construction of Aptamer-Modified Fe3O4@SiO2-Au Core-Shell-Satellite Nanocomposites with Surface-Enhanced Raman Scattering and Photothermal Properties and Their Effective Capture, Detection, and Elimination of Staphylococcus aureus.

The early monitoring and inactivation of bacteria are of crucial importance in preventing the further spread of foodborne pathogens. Staphylococcus aureus (S. aureus), a prototypical foodborne pathogen, is widely present in the natural environment and has the capability to trigger a range of diseases at low concentrations. In this work, we designed Fe3O4@SiO2-Au core-shell-satellite nanocomposites (NCs) modified with aptamer for efficient capture, high-sensitivity surface-enhanced Raman scattering (SERS) detection, and photothermal therapy (PTT) against S. aureus. Fe3O4@SiO2-Au NCs with tunable Au nanocrystal nanogaps were prepared. By combining the finite-difference time-domain (FDTD) method and experimental results, we studied the electric field distribution of Fe3O4@SiO2-Au under different Au nanogaps and ultimately obtained the optimal SERS substrate FSA-60. The modification of aptamer on the surfaces of FSA-60 could be used for the specific capture and selective detection of S. aureus, achieving a detection limit of as low as 50 cfu/mL. Furthermore, Apt-FSA-60 possessed excellent photothermal properties, demonstrating the strong photothermal killing ability against S. aureus. Therefore, Apt-FSA-60 is a promising high-sensitivity SERS substrate and efficient photothermal agent and is expected to be widely applied and promoted in future disease prevention and treatment.

Nasopharyngeal carcinoma cell screening based on nuclear targeting Surface-Enhanced Raman Scattering (SERS) detection.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a malignant epithelial carcinoma arising from the nasopharyngeal mucosal lining. Diagnosis of NPC at early stage can improve the outcome of patients and facilitate reduction in cancer mortality. The most significant change between cancer cells and normal cells is the variation of cell nucleus. Therefore, accurately detecting the biochemical changes in nucleus between cancer cells and normal cells has great potential to explore diagnostic molecular markers for NPC. Highly sensitive surface-enhanced Raman scattering (SERS) could reflect the biochemical changes in the process of cell cancerization at the molecular level. However, rapid nuclear targeting SERS detection remains a challenge. RESULTS: A novel and accurate nuclear-targeting SERS detection method based on electroporation was proposed. With the assistance of electric pulses, nuclear-targeting nanoprobes were rapidly introduced into different NPC cells (including CNE1, CNE2, C666 cell lines) and normal nasopharyngeal epithelial cells (NP69 cell line), respectively. Under the action of nuclear localization signaling peptides (NLS), the nanoprobes entering cells were located to the nucleus, providing high-quality nuclear SERS signals. Hematoxylin and eosin (H&E) staining and in situ cell SERS imaging confirmed the excellent nuclear targeting performance of the nanoprobes developed in this study. The comparison of SERS signals indicated that there were subtle differences in the biochemical components between NPC cells and normal nasopharyngeal cells. Furthermore, SERS spectra combined with principal component analysis (PCA) and linear discriminant analysis (LDA) were employed to diagnose and distinguish NPC cell samples, and high sensitivity, specificity, and accuracy were obtained in the screening of NPC cells from normal nasopharyngeal epithelial cells. SIGNIFICANCE: To the best of our knowledge, this is the first study that employing nuclear-targeting SERS testing to screen nasopharyngeal carcinoma cells. Based on the electroporation technology, nanoprobes can be rapidly introduced into living cells for intracellular biochemical detection. Nuclear-targeting SERS detection can analyze the biochemical changes in the nucleus of cancer cells at the molecular level, which has great potential for early cancer screening and cytotoxicity analysis of anticancer drugs.

Bead-based spontaneous Raman codes for multiplex immunoassay.

In the immunoassay process, for fulfilling the need to identify multiple analytes in a small amount of complex sample matrix, it is desirable to develop highly efficient and specific multiplex suspension array technology. Raman coding strategy offers an attractive solution to code the suspension arrays by simply combing narrow spectral bands with stable signal intensities through solid-phase synthesis on the resin beads. Based on this strategy, we report the bead-based spontaneous Raman codes for multiplex immunoassay. The study resulted in superior selectivity of the Raman-encoded beads for binding with single and multiple analytes, respectively. With the use of mixed types of Raman-encoded immunoassay beads, multiple targets in small amounts of samples were identified rapidly and accurately. By confirming the feasibility of bead-based spontaneous Raman codes for multiplex immunoassay, we anticipate this novel technology to be widely applied in the near future.

Vibrational imaging of metabolites for improved microbial cell strains.

Significance: Biomanufacturing utilizes modified microbial systems to sustainably produce commercially important biomolecules for use in agricultural, energy, food, material, and pharmaceutical industries. However, technological challenges related to non-destructive and high-throughput metabolite screening need to be addressed to fully unlock the potential of synthetic biology and sustainable biomanufacturing. Aim: This perspective outlines current analytical screening tools used in industrial cell strain development programs and introduces label-free vibrational spectro-microscopy as an alternative contrast mechanism. Approach: We provide an overview of the analytical instrumentation currently used in the "test" portion of the design, build, test, and learn cycle of synthetic biology. We then highlight recent progress in Raman scattering and infrared absorption imaging techniques, which have enabled improved molecular specificity and sensitivity. Results: Recent developments in high-resolution chemical imaging methods allow for greater throughput without compromising the image contrast. We provide a roadmap of future work needed to support integration with microfluidics for rapid screening at the single-cell level. Conclusions: Quantifying the net expression of metabolites allows for the identification of cells with metabolic pathways that result in increased biomolecule production, which is essential for improving the yield and reducing the cost of industrial biomanufacturing. Technological advancements in vibrational microscopy instrumentation will greatly benefit biofoundries as a complementary approach for non-destructive cell screening.

Molecular separation-assisted label-free SERS combined with machine learning for nasopharyngeal cancer screening and radiotherapy resistance prediction.

Nasopharyngeal cancer (NPC) is a malignant tumor with high prevalence in Southeast Asia and highly invasive and metastatic characteristics. Radiotherapy is the primary strategy for NPC treatment, however there is still lack of effect method for predicting the radioresistance that is the main reason for treatment failure. Herein, the molecular profiles of patient plasma from NPC with radiotherapy sensitivity and resistance groups as well as healthy group, respectively, were explored by label-free surface enhanced Raman spectroscopy (SERS) based on surface plasmon resonance for the first time. Especially, the components with different molecular weight sizes were analyzed via the separation process, helping to avoid the possible missing of diagnostic information due to the competitive adsorption. Following that, robust machine learning algorithm based on principal component analysis and linear discriminant analysis (PCA-LDA) was employed to extract the feature of blood-SERS data and establish an effective predictive model with the accuracy of 96.7% for identifying the radiotherapy resistance subjects from sensitivity ones, and 100% for identifying the NPC subjects from healthy ones. This work demonstrates the potential of molecular separation-assisted label-free SERS combined with machine learning for NPC screening and treatment strategy guidance in clinical scenario.

Plasmonic trimers designed as SERS-active chemical traps for subtyping of lung tumors.

Plasmonic materials can generate strong electromagnetic fields to boost the Raman scattering of surrounding molecules, known as surface-enhanced Raman scattering. However, these electromagnetic fields are heterogeneous, with only molecules located at the 'hotspots', which account for ≈ 1% of the surface area, experiencing efficient enhancement. Herein, we propose patterned plasmonic trimers, consisting of a pair of plasmonic dimers at the bilateral sides and a trap particle positioned in between, to address this challenge. The trimer configuration selectively directs probe molecules to the central traps where 'hotspots' are located through chemical affinity, ensuring a precise spatial overlap between the probes and the location of maximum field enhancement. We investigate the Raman enhancement of the Au@Al2O3-Au-Au@Al2O3 trimers, achieving a detection limit of 10-14 M of 4-methylbenzenethiol, 4-mercaptopyridine, and 4-aminothiophenol. Moreover, single-molecule SERS sensitivity is demonstrated by a bi-analyte method. Benefiting from this sensitivity, our approach is employed for the early detection of lung tumors using fresh tissues. Our findings suggest that this approach is sensitive to adenocarcinoma but not to squamous carcinoma or benign cases, offering insights into the differentiation between lung tumor subtypes.

Improved Classification Performance of Bacteria in Interference Using Raman and Fourier-Transform Infrared Spectroscopy Combined with Machine Learning.

The rapid and sensitive detection of pathogenic and suspicious bioaerosols are essential for public health protection. The impact of pollen on the identification of bacterial species by Raman and Fourier-Transform Infrared (FTIR) spectra cannot be overlooked. The spectral features of the fourteen class samples were preprocessed and extracted by machine learning algorithms to serve as input data for training purposes. The two types of spectral data were classified using classification models. The partial least squares discriminant analysis (PLS-DA) model achieved classification accuracies of 78.57% and 92.85%, respectively. The Raman spectral data were accurately classified by the support vector machine (SVM) algorithm, with a 100% accuracy rate. The two spectra and their fusion data were correctly classified with 100% accuracy by the random forest (RF) algorithm. The spectral processed algorithms investigated provide an efficient method for eliminating the impact of pollen interference.

Graphene Oxide Nanosheets for Bone Tissue Regeneration.

Bone tissue engineering is a promising alternative to repair wounds caused by cellular or physical accidents that humans face daily. In this sense, the search for new graphene oxide (GO) nanofillers related to their degree of oxidation is born as an alternative bioactive component in forming new scaffolds. In the present study, three different GOs were synthesized with varying degrees of oxidation and studied chemically and tissue-wise. The oxidation degree was determined through infrared (FTIR), X-ray diffraction (XRD), X-ray photoelectron (XPS), and Raman spectroscopy (RS). The morphology of the samples was analyzed using scanning electron microscopy (SEM). The oxygen content was deeply described using the deconvolution of RS and XPS techniques. The latter represents the oxidation degree for each of the samples and the formation of new bonds promoted by the graphitization of the material. In the RS, two characteristic bands were observed according to the degree of oxidation and the degree of graphitization of the material represented in bands D and G with different relative intensities, suggesting that the samples have different crystallite sizes. This size was described using the Tuinstra-Koenig model, ranging between 18.7 and 25.1 nm. Finally, the bone neoformation observed in the cranial defects of critical size indicates that the F1 and F2 samples, besides being compatible and resorbable, acted as a bridge for bone healing through regeneration. This promoted healing by restoring bone and tissue structure without triggering a strong immune response.

Surface-Enhanced Raman Spectroscopy (SERS)-Based Sensors for Deoxyribonucleic Acid (DNA) Detection.

Surface-enhanced Raman spectroscopy (SERS) has emerged as a powerful technique for the detection and analysis of biomolecules due to its high sensitivity and selectivity. In recent years, SERS-based sensors have received significant attention for the detection of deoxyribonucleic acid (DNA) molecules, offering promising applications in fields such as medical diagnostics, forensic analysis, and environmental monitoring. This paper provides a concise overview of the principles, advancements, and potential of SERS-based sensors for DNA detection. First, the fundamental principles of SERS are introduced, highlighting its ability to enhance the Raman scattering signal by several orders of magnitude through the interaction between target molecules with metallic nanostructures. Then, the fabrication technologies of SERS substrates tailored for DNA detection are reviewed. The performances of SERS substrates previously reported for DNA detection are compared and analyzed in terms of the limit of detection (LOD) and enhancement factor (EF) in detail, with respect to the technical parameters of Raman spectroscopy (e.g., laser wavelength and power). Additionally, strategies for functionalizing the sensor surfaces with DNA-specific capture probes or aptamers are outlined. The collected data can be of help in selecting and optimizing the most suitable fabrication technology considering nucleotide sensing applications with Raman spectroscopy.

Raman-Activated, Interactive Sorting of Isotope-Labeled Bacteria.

Due to its high spatial resolution, Raman microspectroscopy allows for the analysis of single microbial cells. Since Raman spectroscopy analyzes the whole cell content, this method is phenotypic and can therefore be used to evaluate cellular changes. In particular, labeling with stable isotopes (SIPs) enables the versatile use and observation of different metabolic states in microbes. Nevertheless, static measurements can only analyze the present situation and do not allow for further downstream evaluations. Therefore, a combination of Raman analysis and cell sorting is necessary to provide the possibility for further research on selected bacteria in a sample. Here, a new microfluidic approach for Raman-activated continuous-flow sorting of bacteria using an optical setup for image-based particle sorting with synchronous acquisition and analysis of Raman spectra for making the sorting decision is demonstrated, showing that active cells can be successfully sorted by means of this microfluidic chip.

Nanoimprinted Plasmonic Crystals for Cost-Effective SERS Identification of Methylated DNAs.

The development of a cost-effective and rapid assay technique for the identification of DNA methylation is one of the most crucial issues in the field of biomedical diagnosis because DNA methylation plays key roles in human health. The plasmonic crystal-based surface-enhanced Raman spectroscopy (SERS) technique is promising for the realization of such an assay method owing to its capability of generating uniformly enhanced electric fields to achieve high reproducibility and accuracy in SERS assays. However, the time and technical costs of fabricating plasmonic crystals are high, owing to the need for nanofabrication equipment. In this study, we developed nanoimprinted plasmonic crystals for cost-effective and rapid DNA methylation assays. Our plasmonic crystals identified methylated DNA with the 40-base pair adenomatous polyposis coli (APC) gene sequence, which is correlated with cell growth and cancer cells.

Comment on "Raman spectroscopy combined with multivariate statistical algorithms for the simultaneous screening of cervical and breast cancers".

This article discusses current research on the detection of cervical and breast cancer using in vitro Raman spectral analysis of human serum by Cao et al. (2024) which was published in the Lasers in Medical Science journal. Despite the high accuracy of the suggested approach (93%), the demonstrated findings could be treated unclear due to possible overestimation of the classification models.

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.