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The increasing amount of globally seized controlled substances in combination with the more diverse drugs-of-abuse market encompassing many new psychoactive substances (NPS) provides challenges for rapid and reliable on-site presumptive drug testing. Long-established colorimetric spot tests tend to fail due to the unavailability of reliable tests for novel drugs and to false-positive reactions on commonly encountered substances. In addition, handling of samples and chemicals is required. Spectroscopic techniques do not have these disadvantages as spectra are compound-specific and non-invasive tests are possible. Near-infrared (NIR) spectroscopy is a promising technique for on-scene forensic drug detection. Numerous portable devices were introduced in the market in recent years. However, most handheld spectrometers operate in different and relatively confined wavelength ranges compared to the full 780 – 2500 nm NIR wavelength range. In addition, their spectral resolution is limited compared to benchtop instruments. This dataset presents the NIR spectra of 430 forensic samples, including regularly encountered illicit-drugs, NPS, commonly used adulterants, bulking-agents and excipients, and seized casework materials (powders and tablets). Data is available from 5 different NIR spectrometers; including a benchmark high-resolution, full range 350–2500 nm laboratory grade instrument and 4 portable spectrometers operating in the ranges of 1300–2600 nm, 1550–1950 nm, 950–1650 nm and 740–1070 nm. Via this dataset, spectra of illicit-drugs become available to institutes that typically do not have access to controlled substances. This data can be used to develop chemometric detection and classification models for illicit-drugs and provide insight in diagnostic spectral features that need to be recorded for reliable detection models. Additionally, the high-resolution, full range VIS-NIR spectra of the benchmark ASD instrument can be used for in-silica predictions of spectra in a certain wavelength range to provide insight in the optimal resolution and wavelength range of a prospective portable device.

Background Current developments in portable photonic devices for fast authentication of extra virgin olive oil (EVOO) or EVOO with non-EVOO additions steer towards hyphenation of different optic technologies. The multiple spectra or so-called “fingerprints” of samples are then analyzed with multivariate statistics. For EVOO authentication, one-class classification (OCC) to identify “out-of-class” EVOO samples in combination with data-fusion is applicable. Objective Prospecting the application of a prototype photonic device (“PhasmaFood”) which hyphenates visible, fluorescence, and near-infrared spectroscopy in combination with OCC modelling to classify EVOOs and discriminate them from other edible oils and adulterated EVOOs. Method EVOOs were adulterated by mixing in 10–50% (v/v) of refined and virgin olive oils, olive-pomace olive oils, and other common edible oils. Samples were analyzed by the hyphenated sensor. OCC, data-fusion, and decision thresholds were applied and optimized for two different scenarios. Results By high-level data-fusion of the classification results from the three spectral databases and several multivariate model vectors, a 100% correct classification of all pure edible oils using OCC in the first scenario was found. Reducing samples being falsely classified as EVOOs in a second scenario, 97% of EVOOs adulterated with non-EVOO olive oils were correctly identified and ones with other edible oils correctly classified at score of 91%. Conclusions Photonic sensor hyphenation in combination with high-level data fusion, OCC, and tuned decision thresholds delivers significantly better screening results for EVOO compared to individual sensor results. Highlights Hyphenated photonics and its data handling solutions applied to extra virgin olive oil authenticity testing was found to be promising.

Background: Since the incidence of food adulteration is rising, finding a rapid, accurate, precise, low-cost, user-friendly, high-throughput, ruggedized, and ideally portable method is valuable to combat food fraud. Near-infrared spectroscopy (NIRS), in combination with a chemometrics-based approach, allows potentially rapid, frequent, and in situ measurements in supply chains. Methods: This study focused on the feasibility of a benchtop Fourier-transformation-NIRS apparatus (FT-NIRS, 1000 - 2500 nm) and a portable short wave NIRS device (SW-NIRS, 740 - 1070 nm) for the discrimination of genuine and citric acid-adulterated lime juice samples in a cost-effective manner following chemometrics study. Results: Principal component analysis (PCA) of the spectral data resulted in a noticeable distinction between genuine and adulterated samples. Wavelengths between 1100 - 1400 nm and ‎‎1550 - 1900 nm were found to be more important for the discrimination of samples for the benchtop FT-NIRS data, while variables between 950 - 1050 nm contributed significantly to the discrimination of samples based on the portable SW-NIRS data. Following partial least squares discriminant analysis (PLS-DA) as a discriminant model, standard normal variate (SNV) or multiplicative scatter correction (MSC) transformation of benchtop FT-NIRS data and SNV in combination with the second derivative transformation of portable SW-NIRS data on the training set delivered equal accuracy (94%) in the prediction of the test set. In the soft independent modeling of class analogy (SIMCA) as a class-modeling approach, the overall performances of generated models on the auto-scaled data were 98% and 94.5% for benchtop FT-NIRS and portable SW-NIRS, respectively. Conclusions: As a proof of concept, NIRS technology coupled with appropriate ‎multivariate classification models enables fast detection of citric acid-adulterated ‎lime juices. In addition, the promising results of portable SW-NIRS combined with SIMCA indicated its use as a screening tool for on-site analysis of lime juices at various stages of the food supply chain.

Both the increasing volume and diversity of drugs-of-abuse encountered by investigation services necessitates the need for fast on-scene detectors to detect and identify a broad range of substances. Near-Infrared (NIR) spectroscopy is suitable for presumptive drugs testing by miniaturized sensors implemented in portable devices. Currently, a myriad of different portable NIR spectrometers is available that utilize different wavelength ranges. This study presents a comparison of NIR spectra of frequently occuring drugs analyzed by five different devices. A 350 – 2500 nm range laboratory grade VIS-NIR spectrometer was used to gain insight in spectral ranges diagnostic for substances relevant in forensic science. Obtained spectra were compared to the output of portable spectrometers operating in the 740 – 1070 nm, 950 – 1650 nm, 1550 – 1950 nm and 1300 – 2600 nm range. The results yielded novel insights in the usability of individual spectrometers by visual inspection of NIR spectra as well as comparative statistics with reference substances. For MDMA detection, an instrument capable of detecting a highly abundant and specific peak at 2020 nm is beneficial whereas colored samples are more difficult to detect by lower wavelength range sensors. Relatively pure, lightly colored samples may be correctly characterized by all sensors. These findings may aid NIR spectrometer selection in forensic practice as well as future studies on instrument selectivity or cross-platform calibration transfer.

Many industries see a shifting focus towards performing on-site analysis using handheld spectroscopic devices. A determining factor for decision-making on the commissioning of these devices is available information on the potential performance of the device for specific applications. By now, myriad handheld solutions with very different specifications and pricing are available on the market. Although specifications are generally available for new devices, this does not directly quantify or predict how available devices will perform for targeted cases. We present a novel chemometric method to estimate the prediction performance of handheld NIR hardware and apply it to estimate the performance of two commercially available handheld NIR technologies in predicting protein content (ranging 120–180 g kg−1) in pig feed from existing data of a benchtop device. Adjusting benchtop data to the wavelength range and resolution of the handheld device lead to over-optimistic estimates of the handheld performances. Our method additionally utilizes information on the error structure of the handheld devices for the estimation. It yielded performance estimates differing less than 1 g kg−1 from the experimentally determined handheld performances and similar model parameters. Our method was effective for linear and nonlinear calibration algorithms, also when estimating performance after averaging multiple scans. Replicate spectra of twenty samples recorded using the handheld were required for replication error estimation to obtain an accurate performance estimation. The error structure could be reported by manufacturers in the future for this approach to be universally employed for predictive quantitative technology assessment. Overall, our method provides estimates of the performance of a handheld device for a specific task with minimal testing required and can thus be used as a device or application screening tool before committing to develop calibrations.

On‐scene drug detection is an increasingly significant challenge due to the fast‐changing drug market as well as the risk of exposure to potent drug substances. Conventional colorimetric cocaine tests involve handling of the unknown material and are prone to false‐positive reactions on common pharmaceuticals used as cutting agents. This study demonstrates the novel application of 740–1070 nm small‐wavelength‐range near‐infrared (NIR) spectroscopy to confidently detect cocaine in case samples. Multistage machine learning algorithms are used to exploit the limited spectral features and predict not only the presence of cocaine but also the concentration and sample composition. A model based on more than 10,000 spectra from case samples yielded 97% true‐positive and 98% true‐negative results. The practical applicability is shown in more than 100 case samples not included in the model design. One of the most exciting aspects of this on‐scene approach is that the model can almost instantly adapt to changes in the illicit‐drug market by updating metadata with results from subsequent confirmatory laboratory analyses. These results demonstrate that advanced machine learning strategies applied on limited‐range NIR spectra from economic handheld sensors can be a valuable procedure for rapid on‐site detection of illicit substances by investigating officers. In addition to forensics, this interesting approach could be beneficial for screening and classification applications in the pharmaceutical, food‐safety, and environmental domains., The novel application of 740‐1070 nm small wavelength range NIR spectroscopy to confidently detect cocaine in case samples is demonstrated. Multi‐stage machine learning algorithms are applied to exploit the limited spectral features and predict not only the presence of cocaine but also predict a concentration and sample composition. A model based on >10,000 spectra from case samples yielded 97% true positive and 98% true negative results. The practical applicability is shown on over 100 case samples not included in model design.

Handheld Raman spectroscopy is an emerging technique for rapid on‐site detection of drugs of abuse. Most devices are developed for on‐scene operation with a user interface that only shows whether cocaine has been detected. Extensive validation studies are unavailable, and so are typically the insight in raw spectral data and the identification criteria. This work evaluates the performance of a commercial handheld Raman spectrometer for cocaine detection based on (i) its performance on 0–100 wt% binary cocaine mixtures, (ii) retrospective comparison of 3,168 case samples from 2015 to 2020 analyzed by both gas chromatography–mass spectrometry (GC–MS) and Raman, (iii) assessment of spectral selectivity, and (iv) comparison of the instrument's on‐screen results with combined partial least square regression (PLS‐R) and discriminant analysis (PLS‐DA) models. The limit of detection was dependent on sample composition and varied between 10 wt% and 40 wt% cocaine. Because the average cocaine content in street samples is well above this limit, a 97.5% true positive rate was observed in case samples. No cocaine false positives were reported, although 12.5% of the negative samples were initially reported as inconclusive by the built‐in software. The spectral assessment showed high selectivity for Raman peaks at 1,712 (cocaine base) and 1,716 cm−1 (cocaine HCl). Combined PLS‐R and PLS‐DA models using these features confirmed and further improved instrument performance. This study scientifically assessed the performance of a commercial Raman spectrometer, providing useful insight on its applicability for both presumptive detection and legally valid evidence of cocaine presence for law enforcement., The performance of a handled Raman spectrometer for cocaine detection is evaluated by validation samples, spectral assessment, and retrospective comparison. Raman and GC–MS results of 3,168 cases samples from 2015 to 2020 were compared. Limits of detection were dependent of sample composition and varied between 10 and 40 wt% cocaine. A 97.5% true positive rate was observed in case samples. Instrument performance was assessed and further improved by a combined partial least square regression (PLS‐R) and discriminant analysis (PLS‐DA) model.

Microplastics (MPs) are considered an emerging issue as environmental pollutants and a potential health threat. This review will focus on recently published data on concentrations in food, possible effects, and monitoring methods. Some data are available on concentrations in seafood (fish, bivalves, and shrimps), water, sugar, salt, and honey, but are lacking for other foods. Bottled water is a considerable source with numbers varying between 2600 and 6300 MPs per liter. Particle size distributions have revealed an abundance of particles smaller than 25 µm, which are considered to have the highest probability to pass the intestinal border and to enter the systemic circulation of mammals. Some studies with mice and zebrafish with short- or medium-term exposure (up to 42 days) have revealed diverse results with respect to both the type and extent of effects. Most notable modifications have been observed in gut microbiota, lipid metabolism, and oxidative stress. The principal elements of MP monitoring in food are sample preparation, detection, and identification. Identified data gaps include a lack of occurrence data in plant- and animal-derived food, a need for more data on possible effects of different types of microplastics, a lack of in silico models, a lack of harmonized monitoring methods, and a further development of quality assurance.

Commission Regulation (EC) 543/2008 limits moisture and protein contents in poultry meat. However, this regulation leaves room for interpretation regarding sample homogenisation, potentially affecting comparability of laboratory results. Therefore, a proficiency test and sample homogenisation study were organised amongst 19 European National Reference Laboratories (NRL). In the proficiency test, three different pre-homogenised chicken samples (fillets, drumsticks and carcasses) were analysed. Only one NRL produced unsatisfactory results. In the homogenisation study, NRLs were supplied with uniform fillet, drumstick and carcass materials. Homogenisation was performed according to the NRLs in-house methods. Five NRLs did not return satisfactory results. As these NRLs produced satisfactory results in the proficiency test, their increase in z-scores was related to their homogenisation practices. Overall, scattering of individual results was higher for drumsticks compared to fillets and carcasses. Homogenisation practices for poultry meat introduced significant differences in moisture and protein results and standardisation is therefore advisable.

The application of phycobiliproteins, e.g. blue C-phycocyanin, as natural water-soluble food colourants is emerging. The chromophore of these proteins comprises a number of tetrapyrroles (or phycocyanobilins), which have an extensive conjugated system, vulnerable to autoxidation. To assess the autoxidation products, a simplified model system was used in which the free tetrapyrrole biliverdin, instead of phycobiliprotein, was subjected to light-accelerated autoxidation. Degradation products of biliverdin were subsequently annotated by reversed-phase ultra-high performance liquid chromatography with a photo diode array and positive mode in-line electrospray ionization mass spectrometry. To facilitate the analysis of degradation products, autoxidation of the three methine bridges in biliverdin was mimicked in silico. It was found that both the peripheral and central methine bridges of biliverdin were susceptible to light-accelerated autoxidation. Scission products tentatively annotated with MS(2) and MS(3) were propionic acid-containing pyrroles. From this, it can be speculated that tetrapyrroles attached to phycobiliproteins are susceptible to autoxidative degradation.

Food products enriched with fatty acid-esterified xanthophylls may result in deviating dietary apo-carotenoids. Therefore, free astaxanthin and its mono- and dipalmitate esters were subjected to two degradation processes in a methanolic model system: light-accelerated autoxidation and hypochlorous acid/hypochlorite (HOCl/OCl(-)) bleaching. Reversed phase ultrahigh-performance liquid chromatography photodiode array with in-line electrospray ionization mass spectrometry (RP-UHPLC-PDA-ESI-MS) was used for assessment of degradation products. Apo-astaxanthinals and -astaxanthinones containing 3 (apo-9) to 10 (apo-8') conjugated double bonds were found upon autoxidation for all three types of astaxanthin (except free apo-8'-astaxanthinal). Fragmentation of [M + H](+) and [M + Na](+) parent masses of apo-astaxanthins from dipalmitate astaxanthin indicated palmitate esterification. Astaxanthin monopalmitate degradation resulted in a mixture of free and palmitate apo-astaxanthins. HOCl/OCl(-) rapidly converted the astaxanthins into a mixture of epoxy-apo-9- and epoxy-apo-13-astaxanthinones. The palmitate ester bond was hardly affected by autoxidation, whereas for HOCl/OCl(-) the ester bond of the apo-astaxanthin palmitoyl esters was degraded.

National Reference Laboratories (NRLs) are part of the system responsible for the control and enforcement of EU food and feed law. RIKILT Wageningen University & Research has been designated as the NRL for twelve subjects. The tasks of a NRL depend on its research field. This report gives an overview of the activities performed by all of RIKILT's NRLs in 2016.

Fresh/chilled chicken breasts retail at a higher price than their frozen/thawed counterparts. Verification of the fresh/thawed status of chicken meat is determined by measuring β-hydroxyacyl-Coenzyme A-hydrogenase (HADH) activity present in meat intra-cellular liquids spectrophotometrically. However, considerable numbers of reference samples are required for the current arithmetic method, adding to laboratory costs. Therefore, two alternative mathematical approaches which do not require such reference samples were developed and evaluated: curve fitting and multivariate classification. The approaches were developed using 55 fresh/thawed fillet samples. The performance of the methods was examined by an independent validation set which consisted of 16 samples. Finally, the approach was tested in practice in a market study. With the exception of two minor false classifications, both newly proposed methods performed equally well as the classical method. All three methods were able to identify two apparent fraudulent cases in the market study. Therefore, the experiments showed that the costs of HADH measurements can be reduced by adapting alternative mathematics.

Organic wheat retails at higher market prices than the conventionally grown counterparts. In view of fair competition and sustainable consumer confidence, the organic nature of organic wheat needs to be assured. Amongst other controls this requires analytical tests based on discriminating traits. In this paper, phenolic acids were examined by liquid chromatography analysis as biomarkers for discriminating between the two groups by means of a controlled grown full factorial design Danish wheat sample set. By combining baseline and retention-time correction pre-treatments and principal component analysis, discrimination between organic and conventional produce was found to be expressed in the first principal component (93%), whilst the second principal component accounted for the production year (4%). Upon examination of the loadings plot, a single chromatographic peak was found to account for a large part in the discrimination between the two wheat production systems. This was further underpinned by statistically significant differences found in concentrations between the organic and conventional production systems of this phenolic acid (ANOVA, P0.05). The phenolic acid was tentatively identified as protocatechuic acid by negative mode mass spectrometry. The results obtained implied that protocatechuic acid may serve as a single marker for discrimination between organic and conventional produced wheat.

The effect of three different nutrient depletions (nitrogen, sulphur and magnesium) on the growth and pigment accumulation of the haptophyte Isochrysis aff. galbana (clone T-ISO) has been studied. Pigments were quantified based on RP-UHPLC-PDA-MSn analysis. All nutrient depletions led to reduced maximal biomass concentrations. Besides, all nutrient-depleted cultures accumulated 3-hydroxyechinenone. To our knowledge, this is the first time that 3-hydroxyechinenone has been found in I. aff. galbana T-ISO. Most 3-hydroxyechinenone, as well as the most echinenone and diatoxanthin, were found in the nitrogen-limited culture in which a more severe limitation resulted in higher cellular contents. Similar to accumulation of diatoxanthin, accumulation of 3-hydroxyechinenone and echinenone may be part of a global (stress) response mechanism to oversaturating light conditions.

Fatty acid esterification, common in naturally occurring astaxanthin, has been suggested to influence both colour stability and degradation of all-trans-astaxanthin. Therefore, astaxanthin stability was studied as influenced by monoesterification and diesterification with palmitate. Increased esterification decelerated degradation of all-trans-astaxanthin (RP-UHPLC-PDA), whereas, it had no influence on colour loss over time (spectrophotometry). This difference might be explained by the observation that palmitate esterification influenced the cis-trans equilibrium. Free astaxanthin produced larger amounts of 9-cis isomer whereas monopalmitate esterification resulted in increased 13-cis isomerization. The molar ratios of 9-cis:13-cis after 60 min were 1:1.7 (free), 1:4.8 (monopalmitate) and 1:2.6 (dipalmitate). The formation of 9-cis astaxanthin, with its higher molar extinction coefficient than that of all-trans-astaxanthin, might compensate for colour loss induced by conjugated double bond cleavage. As such, it was concluded that spectrophotometry is not an accurate measure of the degradation of the all-trans-astaxanthin molecule.

Natural carotenoids such as astaxanthin, β,β-carotene and lutein are pigments with a high market value. We studied the effects of nitrogen depletion on the carotenoid metabolism of Chlorella zofingiensis (Chlorophyta) and the subsequent treatment with diphenylamine (DPA), an inhibitor of the biosynthesis of secondary ketocarotenoids. Pigments were identified and quantified based on reversed phase ultra-high performance liquid chromatography photodiode array tandem mass spectrometry (RP-UHPLC-PDA-MSn). Nitrogen depletion (without DPA) resulted in a degradation of chlorophylls and primary carotenoids and an accumulation of astaxanthin, ketolutein, canthaxanthin, adonixanthin and β,β-carotene. The DPA treatment decreased the overall production of β,β-carotene derivatives (sum of astaxanthin, canthaxanthin, echinenone and adonixanthin); however, the production of ketolutein and degradation of primary carotenoids were not modified. This suggests that the regulatory mechanisms controlling the flux towards ketolutein and primary carotenoids were not affected by the decreased levels of β,β-carotene derivatives. In addition, DPA increased production of the individual carotenoids, adonixanthin and echinenone. Insight into the regulation of microalgal carotenoid biosynthesis as demonstrated in this paper is essential when a large-scale carotenoid production process is to be optimised or a recombinant C. zofingiensis strain is to be designed with the intention of excessively producing primary or secondary carotenoids.

Berries and leaves from six varieties of Carpathians’ sea buckthorn (Hippophae rhamnoides L., ssp. Carpatica) were analysed for their carotenoid composition (free and esterified) using a combination of HPLC-PAD, GC–MS and UHPLC–PAD–ESI-MS techniques. GC–MS techniques revealed the fatty acid profile specific for each berry variety, while targeted UHPLC–MS analysis identified the fatty acids involved in carotenoids esterification: palmitic (C16:0), myristic (C14:0) and stearic (C18:0). Total carotenoid content varied between 53 and 97 mg/100 g dry weight in berries, and between 3.5 and 4.2 mg/100 g DW in leaves. The carotenoid di-esters represented the main fraction among berry varieties having zeaxanthin di-palmitate as major compound, while leaves contained only free carotenoids like lutein, ß-carotene, violaxanthin and neoxanthin. Principal component analysis identified the suitable carotenoid biomarkers characteristic for the Carpathians’ sea buckthorn from Romania with contribution to their taxonomic classification and authenticity recognition.

The aim of this study was to investigate the aroma and sensory profiles of various types of peaches (Prunus persica L. Batsch.). Forty-three commercial cultivars comprising peaches, flat peaches, nectarines, and canning peaches (pavías) were grown over two consecutive harvest years. Fruits were assessed for chemical aroma and sensory profiles. Chemical aroma profile was obtained by proton transfer reaction-mass spectrometry (PTR-MS) and spectral masses were tentatively identified with PTR-Time of Flight-MS (PTR-Tof-MS). Sensory analysis was performed at commercial maturity considering seven aroma/flavor attributes. The four types of peaches showed both distinct chemical aroma and sensory profiles. Flat peaches and canning peaches showed most distinct patterns according to discriminant analysis. The sensory data were related to the volatile compounds by partial least square regression. γ-Hexalactone, γ-octalactone, hotrienol, acetic acid and ethyl acetate correlated positively, and benzeneacetaldehyde, trimethylbenzene and acetaldehyde negatively to the intensities of aroma and ripe fruit sensory scores., This research was financed by the Spanish Ministry of Economy and Competitiveness, INIA – Project: RTA2011-00123-00-00, and by the Agency for the Research Centres of Catalonia (I-CERCA). Tiago Bianchi acknowledges the Ph.D. grant from the Spanish National Institute for Agricultural and Food Research and Technology (INIA).