Influence of Incident Wavelength and Detector Material Selection on Fluorescence in the Application of Raman Spectroscopy to a Fungal Fermentation Process

Artifacts and Anomalies in Raman Spectroscopy: A Review on Origins and Correction Procedures

Raman spectroscopy, renowned for its unique ability to provide a molecular fingerprint, is an invaluable tool in industry and academic research. However, various constraints often hinder the measurement process, leading to artifacts and anomalies that can significantly affect spectral measurements. This review begins by thoroughly discussing the origins and impacts of these artifacts and anomalies stemming from instrumental, sampling, and sample-related factors. Following this, we present a comprehensive list and categorization of the existing correction procedures, including computational, experimental, and deep learning (DL) approaches. The review concludes by identifying the limitations of current procedures and discussing recent advancements and breakthroughs. This discussion highlights the potential of these advancements and provides a clear direction for future research to enhance correction procedures in Raman spectral analysis.

Direct Measurement of Chocolate Components Using Dispersive Raman Spectroscopy at 1000 nm Excitation

Chocolate is a popular food around the world. Making chocolate-based confectionaries involve multiple processing steps including cocoa bean fermentation, cocoa bean roasting, grinding, and then a controlled crystallization, where the processing conditions yields the desirable polymorph V to give chocolate its characteristic snap and texture. Raman spectroscopy is well known as a technique that can provide a non-contact, non-destructive analysis of chemical composition and molecular structure. Yet, excitation in the visible and near-infrared (532-785 nm) has not been possible for dark or milk chocolate because of the samples' overwhelming fluorescence. New technologies enabling Raman spectroscopy closer to shortwave infrared wavelengths, closer to 1000 nm, are likely to reduce fluorescence of chocolate and other highly fluorescent samples. Based on the successes of 1064 nm excitation to understand chocolate blooming, we hypothesized that 1000 nm excitation would also reduce fluorescence and enable Raman spectroscopy in dark and milk chocolates. We used dispersive Raman spectroscopy at 1000 nm to measure white, milk, and dark chocolate and cocoa nibs. The use of 1000 nm excitation effectively reduced fluorescence, enabling qualitative and quantitative Raman spectroscopy directly on chocolate samples. These feasibility studies indicate that 1000 nm Raman spectroscopy can be used to measure chocolate in a laboratory or process environment.

Microplastic Pollution: Chemical Characterization and Impact on Wildlife

Microplastics are small pieces of plastic that are less than 5 mm in size and can be found in most environments, including the oceans, rivers, and air. These small plastic particles can have negative impacts on wildlife and the environment. In this review of the literature, we analyze the presence of microplastics in various species of wildlife, including fish, birds, and mammals. We describe a variety of analytical techniques, such as microscopy and spectrometry, which identify and quantify the microplastics in the samples. In addition, techniques of sample preparation are discussed. Summary results show that microplastics are present in all the wildlife species studied, with the highest concentrations often found in fish and birds. The literature suggests that microplastics are widely distributed in the environment and have the potential to affect a wide range of species. Further research is required to fully understand the impacts of microplastics on wildlife and the environment.

High-Throughput Raman Spectroscopy Combined with Innovate Data Analysis Workflow to Enhance Biopharmaceutical Process Development

Raman spectroscopy has the potential to revolutionise many aspects of biopharmaceutical process development. The widespread adoption of this promising technology has been hindered by the high cost associated with individual probes and the challenge of measuring low sample volumes. To address these issues, this paper investigates the potential of an emerging new high-throughput (HT) Raman spectroscopy microscope combined with a novel data analysis workflow to replace off-line analytics for upstream and downstream operations. On the upstream front, the case study involved the at-line monitoring of an HT micro-bioreactor system cultivating two mammalian cell cultures expressing two different therapeutic proteins. The spectra generated were analysed using a partial least squares (PLS) model. This enabled the successful prediction of the glucose, lactate, antibody, and viable cell density concentrations directly from the Raman spectra without reliance on multiple off-line analytical devices and using only a single low-volume sample (50–300 μL). However, upon the subsequent investigation of these models, only the glucose and lactate models appeared to be robust based upon their model coefficients containing the expected Raman vibrational signatures. On the downstream front, the HT Raman device was incorporated into the development of a cation exchange chromatography step for an Fc-fusion protein to compare different elution conditions. PLS models were derived from the spectra and were found to predict accurately monomer purity and concentration. The low molecular weight (LMW) and high molecular weight (HMW) species concentrations were found to be too low to be predicted accurately by the Raman device. However, the method enabled the classification of samples based on protein concentration and monomer purity, allowing a prioritisation and reduction in samples analysed using A280 UV absorbance and high-performance liquid chromatography (HPLC). The flexibility and highly configurable nature of this HT Raman spectroscopy microscope makes it an ideal tool for bioprocess research and development, and is a cost-effective solution based on its ability to support a large range of unit operations in both upstream and downstream process operations.