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We demonstrate a sensing scheme for liquid analytes that integrates multiple optical fiber sensors in a near-infrared spectrometer. With a simple optofluidic method, a broadband radiation is encoded in a time-domain interferogram and distributed to different sensing units that interrogate the sample simultaneously; the spectral readout of each unit is extracted from its output signal by a Fourier transform routine. The proposed method allows performing a multiparametric analysis of liquid samples in a compact setup where the radiation source, measurement units, and spectral readout are all integrated in a robust telecom optical fiber. An experimental validation is provided by combining a plasmonic nanostructured fiber probe and a transmission cuvette in the setup and demonstrating the simultaneous measurement of the absorption spectrum and the refractive index of water-methanol solutions.

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Unsaturated fatty acids are renowned for their beneficial effects on the cardiovascular system. The high content of unsaturated fatty acids is a benefit of vegetable fats and an important nutraceutical indicator. The ability to quickly check fat composition of an edible oil could be advantageous for both consumers and retailers. A Bluetooth-connected pocket spectrometer operating in NIR band was used for analyzing olive oils of different qualities. Reference data for fatty acid composition were obtained from a certified analytical laboratory. Chemometrics was used for processing data, and predictive models were created for determining saturated and unsaturated fatty acid content. The NIR spectrum also demonstrated good capability in classifying extra virgin and non-extra virgin olive oils. The pocket spectrometer used in this study has a relatively low cost, which makes it affordable for a wide class of users. Therefore, it may open the opportunity for quick and non-destructive testing of edible oil, which can be of interest for consumer, retailers, and for small/medium-size producers, which lack easy access to conventional analytics.

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A portable Raman device with a 532 nm excitation laser and a portable infrared spectrometer with ATR (Attenuated Total Reflection) mode were used to analyse the spectral features associated with the identification and compositional variation of Ca-Mg-Fe-Mn natural carbonate minerals with a calcite structure (calcite, ankerite, dolomite, siderite, rhodochrosite, and magnesite). A systematic study of the variations of the peak positions with various compositional ratios was carried out. Most of the band positions were shifted to lower wavenumbers with increasing ionic radius or atomic mass of the divalent cations but the band of the translational lattice (T) mode in Raman and the symmetric bending (ν4) band in the mid-infrared were the most sensitive. Therefore, the elemental variation of the Ca-Mg-Fe-Mn ratio in this carbonate series can be estimated from Raman and infrared band positions from spectra acquired with portable spectrometers.

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The development of portable near-infrared spectroscopy (NIRS) combined with smartphone cloud-based chemometrics has increased the power of these devices to provide real-time in-situ crop nutrient analysis. This capability provides the opportunity to address nutrient deficiencies early to optimise yield. The agriculture sector currently relies on results delivered via laboratory analysis. This involves the collection and preparation of leaf or soil samples during the growing season that are time-consuming and costly. This delays farmers from addressing deficiencies by several weeks which impacts yield potential; hence, requires a faster solution. This study evaluated the feasibility of using NIRS in estimating different macro- and micronutrients in cotton leaf tissues, assessing the accuracy of a portable handheld NIR spectrometer (wavelength range of 1,350-2,500 nm). This study first evaluated the ability of NIRS to predict leaf nutrient levels using dried and ground cotton leaf samples. The results showed the high accuracy of NIRS in predicting essential macronutrients (0.76 ≤ R 2 ≤ 0.98 for N, P, K, Ca, Mg and S) and most micronutrients (0.64 ≤ R 2 ≤ 0.81 for Fe, Mn, Cu, Mo, B, Cl and Na). The results showed that the handheld NIR spectrometer is a practical option to accurately measure leaf nutrient concentrations. This research then assessed the possibility of applying NIRS on fresh leaves for potential in-field applications. NIRS was more accurate in estimating cotton leaf nutrients when applied on dried and ground leaf samples. However, the application of NIRS on fresh leaves was still quite accurate. Using fresh leaves, the prediction accuracy was reduced by 19% for macronutrients and 11% for micronutrients, compared to dried and ground samples. This study provides further evidence on the efficacy of using NIRS for field estimations of cotton nutrients in combination with a nutrient decision support tool, with an accuracy of 87.3% for macronutrients and 86.6% for micronutrients. This application would allow farmers to manage nutrients proactively to avoid yield penalties or environmental impacts.

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Efficient selection of potato varieties with enhanced nutritional quality requires simple, accurate and cost effective assays to obtain tuber chemical composition information. In this study, 75 Andean native potato samples from 7 Solanum species with different colors were characterized and quantified for their anthocyanin, phenolics and sugar content using traditional reference methods. IR (infrared) spectra of potato extracts were collected using a portable infrared system and partial least squares regression (PLSR) calibration models were developed. These models were validated using both full cross-validation and an independent sample set giving strong linear correlation coefficients of prediction (rPred)>0.91 and standard error of prediction (SEP) of 24mg/100g phenolics, 7mg/100g monomeric anthocyanins, 0.1g/100g reducing sugars and 0.12g/100g sucrose. Overall, portable infrared system with PLSR showed great potential to facilitate potato breeding and certain aspects of crop management, material selection for potato processing and related research by providing alternative prediction models.

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Quick and presumptive identification of seized drug samples without destroying evidence is necessary for law enforcement officials to control the trafficking and abuse of drugs. This work reports an automated screening method to detect the presence of cocaine in seized samples using portable Fourier transform infrared (FT-IR) spectrometers. The method is based on the identification of well-defined characteristic vibrational frequencies related to the functional group of the cocaine molecule and is fully automated through the use of an expert system. Traditionally, analysts look for key functional group bands in the infrared spectra and characterization of the molecules present is dependent on user interpretation. This implies the need for user expertise, especially in samples that likely are mixtures. As such, this approach is biased and also not suitable for non-experts. The method proposed in this work uses the well-established "center of gravity" peak picking mathematical algorithm and combines it with the conditional reporting feature in MicroLab software to provide an automated method that can be successfully employed by users with varied experience levels. The method reports the confidence level of cocaine present only when a certain number of cocaine related peaks are identified by the automated method. Unlike library search and chemometric methods that are dependent on the library database or the training set samples used to build the calibration model, the proposed method is relatively independent of adulterants and diluents present in the seized mixture. This automated method in combination with a portable FT-IR spectrometer provides law enforcement officials, criminal investigators, or forensic experts a quick field-based prescreening capability for the presence of cocaine in seized drug samples.

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This work presents a methodology that combines spectroscopic speciation, performed through portable Raman spectroscopy, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and energy dispersive X-ray fluorescence spectrometry (ED-XRF) working in situ, and thermodynamic speciation to diagnose the environmental impacts, induced by past and current events, on two wall painting panels (Nos. 9103 and 9255) extracted more than 150 years ago from the walls of a Pompeian house (Marcus Lucretius House, Regio IX, Insula 3, House 5/24) and deposited in the Naples National Archaeological Museum (MANN). The results show a severe chemical attack of the acid gases that can be explained only by the action of H2S during and just after the eruption of the Vesuvius volcano, that expelled a high concentration of sulfur gases. This fact can be considered as the most important process impacting the wall painting panels deposited in the museum, while the rain-wash processes and the colonization of microorganisms have not been observed in contrast to the impacts shown by the wall paintings left outside in the archaeological site of Pompeii. Moreover, the systematic presence of lead traces and strontium in both wall paintings suggests their presence as impurities of the calcite mortars (intonacco) or calcite binder of these particular fresco Pompeian murals.

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The most common methods for acrylamide analysis in foods require the use of LC-MS/MS and GC-MS. Although these methods have great analytical performance, they need intensive sample preparation, highly specialised instrumentation, and are time consuming. In this study, portable and handheld infrared spectrometers were evaluated as rapid methods for screening acrylamide in potato chips and their performances were compared to those of benchtop infrared systems. The acrylamide content of 64 commercial potato chips (169-2453 µg/kg) was determined by LC-MS/MS. Spectral data were collected using mid-infrared (MIR) and near-infrared (NIR) spectrometers. Partial least squares regression (PLSR) calibration models were developed to predict acrylamide levels. Overall, good linear correlation was found between the predicted acrylamide levels and actual measured acrylamide concentrations by LC-MS/MS (rPred > 0.90 and SEP < 100 µg/kg). Our results indicate that portable and handheld spectrometers can be used as simple and rapid alternatives for acrylamide analysis in potato chips.

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