raman spectroscopy (5)


Fish species identification is normally undertaken using DNA barcoding methods. However, it is often useful to have an on-site rapid non-destructive method to verify fish species. In this study, 2 Raman spectrometers (a portable Raman spectrometer and a benchtop confocal Raman spectrometer) were used and compared for their performance to identify 11 species of fish (4 species of Salmonidae and 7 species of non-Salmonidae).  Supervised chemometric/machine learning classification models were constructed based on a hierarchical classification principle to develop this 11-class identification. Both Raman spectrometers were able to differentiate Salmonidae from non-Salmonidae fish with close to 100% accuracy. To further identify the fish to species level, the portable Raman spectrometer provided better accuracy (i.e., 93% and 93% accuracy for the Salmonidae group and non-Salmonidae identification, respectively) compared to the benchtop Raman spectrometer (i.e., 90% and 84% accuracy for the Salmonidae group and non-Salmonidae identification, respectively). The overall non-destructive analytical time was only 5 minutes.

Read the full open access paper here

Read more…


This review investigates the feasibility of different non-destructive techniques used for authenticating meat products, which could provide real-time monitoring in the near future. The spectroscopic techniques reviewed are NIR (near infrared), MIR (mid-infrared), FTIR (Fourier transform infrared), and Raman. The imaging techniques discussed are colour imaging, hyperspectral imaging and Xray imaging with computed technology. The advantages of these techniques is that they can be applied in-situ, and they give rapid results, but calibration procedures are laborious. In addition, the results are influenced by scanning times, sample to detector distance and environmental factors such as ambient temperature, humidity, illumination conditions, and sample temperature, the latter can differ in meat processing facilities. However, it is hoped that the application of these techniques will be easier with the improvement in instrumental technology, the availability of high-speed computers with appropriate storage capacity, and the development of appropriate chemometric procedures.

Read the full paper here

Read more…


In the US, hemp plants (Cannabis sativa) that produce delta-9-tetrahydrocannabinolic acid (THCA) in amounts higher than 0.3% are classed as cannabis, and lower amounts than 0.3%, as hemp. THCA is the precursor of the psychoactive delta-9 tetrahydrocannabinol (THC) that forms from its oxidation. At present, confirmatory testing whether a sample is cannibis or hemp has to be carried out in a certified laboratory by HPLC, which is time consuming and labour intensive. US researchers have developed a rapid portable, confirmatory, non-invasive and non-destructive approach for cannabis diagnostics that could be performed by a police officer using a hand-held Raman spectrometer.

Samples were taken from both hemp plants and 3 varieties of cannabis plants, and the latter were frozen at  −10 to −15 °C and thawed, which is the standard procedure in cannabis farming that is used to preserve cannabinol content of plants during their post-harvest processing. The Raman spectra were analysed using orthogonal partial least squares discriminant analysis (OPLS-DA) to determine the spectral regions giving the best separation between the two classes especially for THCA. The chemometric model showed 100% accuracy in determining whether a sample was hemp or cannabis, and further modelling gave a prediction rate of 96-100% in identifying the three cannabis varieties.

Read the full open-access paper

Read more…

4469437532?profile=RESIZE_400xRaman spectroscopy represents an increasingingly useful technique for food authentication being a fast, reliable non-targeted method, requiring a minimum sample preparation step. However, in the case of honey, there are limitations to its application caused by sugar crystallisation effects and fluorescence in dark coloured honeys. Romanian researchers have developed a simple sample preparation of honey by a 1:1 w/v dilution in distilled water, which overcomes the limitations and gives reliable and reproductible spectra. 

Read the abstract here

Read more…

In this paper, Raman spectra were acquired through the glass wall of the bottle using a 785 nm laser as excitation source. Principal component analysis (PCA) of the spectra allowed determination of the cask type in which the whisky was aged. Partial least-squares regression facilitated the determination of the age, the alcohol content, the filtering process, and whether or not a whisky contains artificial colourants. 

Read the full abstract at: Single Malt Authentication

Read more…