There is an increasing need of developing methods for fast recognition and identification of new psychoactive substances (NPS). The chemical identification of these new substances produced with the intention of mimicking the effects of controlled drugs is a challenge for forensic and Customs laboratories. In this study, we aim to test the potential of Raman spectroscopy for the identification and classification of seized Customs samples into three NPS families. The performance of two excitation wavelength lasers (785 and 1064 nm) in a benchtop Raman instrument was compared in a set of seized samples that included cathinone, fentanyl, and synthetic cannabinoid derivatives or analogues. The 1064 nm wavelength laser had significant advantages for identifying NPS samples overcoming the intense fluorescence induced when using 785 nm lasers in some substances. Principal component analysis was employed to create a model that successfully discriminates the three NPS families. In order to provide Customs officers with a fast and nondestructive in‐field testing method, the same approach used with the benchtop Raman spectrometer was applied using three handheld Raman instruments. The developed identification and classification model allows the discrimination of fentanyl, cathinone, and synthetic cannabinoid analogues or derivatives providing an efficient tool for the rapid identification of three NPS families. The approach presented in this study can facilitate rapid decision‐making that could be of high relevance especially in the frame of the fentanyl crisis.

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Near-infrared microscopy (NIRM) has been proved to be a powerful tool for the detection of banned meat and bone meal (MBM) in feed. The identification of MBM traces and its ability to differentiate animal from vegetable feed ingredients is based on the evaluation of near-infrared spectra obtained from individual particles present in the sample. This evaluation is supported by appropriate decision rules for the absorbances at specific wavelengths. Here we show that the method and the corresponding decision rules can be successfully transferred from the laboratory which constructed the decision rules to two independent laboratories that were not involved in the calibration process of the method. The analytical results from blind feed samples containing MBM (positive samples) and feed samples without MBM (negative samples) revealed a very good agreement between the three laboratories, thus demonstrating the transferability of the method.

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