Coriander oil is a vegetable oil extracted from coriander seed that has about 70% of petroselinic acid, apart from anti-inflammatory and anti-aging properties, thus gaining the status of new food ...ingredient. Due to its properties and added value, it can become the target of adulteration as occurs with other edible vegetable oils of high market value. Therefore, the objective of this work was to identify the authenticity of coriander oil and adulteration with other commercial vegetable oils such as palm olein, canola oil and soybean oil. Principal component analysis (PCA) differentiated the matrices of pure oils using 3 principal components, which explained 87% of the variance. Linear discriminant analysis (LDA) and k-nearest neighbors algorithm (k-NN) were used to classify pure oil samples and adulterated coriander oils. Partial Least Squares (PLS) regression models presented coefficient of determination (R2) of 0.98, 0.99 and 0.99, for coriander oil adulterated with palm olein soybean oil and canola oil, respectively. RPD was between 7.1 and 10, which indicates robust models that can be used for quality control during the processing of coriander oil.
•Portable NIR spectrometer was used to detect coriander oil adulteration.•Supervised classification methods can identify adulterated coriander oil.•PLSR can predict concentration of different adulterants in coriander oil.
•A rapid method for non-targeted detection of paprika adulteration was investigated.•We combined NIR spectra with multivariate calibration by PLS-DA and PLSR.•NIR spectra of authentic and adulterated ...samples were collected.•NIR is a potential tool to assess the authenticity of paprika powder.
Paprika powder is a widely consumed spice, making it an attractive target for adulteration, which is not easily detected. In this study, a portable near-infrared (NIR) spectrometer was used for fast detection of paprika adulteration. Nine paprika samples from five suppliers were adulterated with potato starch, acacia gum and annatto at different concentrations (0–36% by weight of potato starch and acacia gum, and 0–18% by weight of annatto). The NIR spectrum of each mixture (n = 315) was used as predictors to determine adulteration by partial least squares-discriminant analysis (PLS-DA) and partial least squares regression (PLSR). First, PLS-DA was applied to discriminate between adulterated and non-adulterated samples, as well as the type of adulterant. This method proved to be efficient, with specificity greater than 90 % and error rate lower than 2 %, for all models constructed. PLSR was used to predict the concentration of adulterants in paprika samples. In addition, PLSR models with reduced number of wavelengths (predictors) were built by selecting the variables with larger weights on the regression coefficients. Coefficient of prediction (R2p) and root mean square errors of prediction (RMSEP) obtained were 0.95 and 2.12; 0.97 and 1.68; 0.87 and 1.74, for potato starch, acacia gum and annatto, respectively. In conclusion, results showed that NIR spectroscopy is a useful screening technique for identification and quantification of adulteration in paprika.
•An optical colorimetric sensor for promethazine detection was fabricated using sol-gel process.•The fabricated optical sensor was used with a portable spectrometer.•The portable system detected ...promethazine in lean cocktail and pharmaceutical samples.•The system produced results consistent with spectrophotometric reference results.
A low-cost, easy-to-use and portable optical colorimetric sensor determined promethazine using the oxidation of promethazine by a potassium persulfate reagent entrapped within a sol-gel polymer network. The colored reaction product was detected with a portable spectrometer. The surface morphology of the optical colorimetric sensor was characterized by scanning electron microscopy and Fourier transform infrared spectroscopy. Under optimized conditions, the calibration curve of promethazine was a concentration range from 50 to 500 mg L−1 with a coefficient of determination (r2 = 0.9948). The limit of detection (LOD) and limit of quantification (LOQ) were 16.5 and 48.9 mg L−1, respectively. The intra-day precisions of the proposed method for measurement of promethazine at the concentrations of 80, 250 and 350 mg L−1 were 0.8, 4.3 and 2.4%RSD, respectively while the inter-day precisions were 1.9, 2.9 and 0.2%RSD, respectively. Accuracy of promethazine analysis ranged from 87 to 105%. The proposed device was stable for at least 90 days. The method was applied for the determination of promethazine in lean cocktail samples and pharmaceutical promethazine. The amounts of promethazine determined by the proposed method and amounts determined by spectrophotometry were not significantly different at 95% confidence level. The developed method is portable, inexpensive, easy and safe to use, consumes low amounts of sample and reagent and enables qualitative and quantitative analysis of the target analyte.
Substantial research has been carried out on rapid, nondestructive, and inexpensive techniques for predicting cheese composition using spectroscopy in the visible and near-infrared radiation range. ...Moreover, in recent years, new portable and handheld spectrometers have been used to predict chemical composition from spectra captured directly on the cheese surface in dairies, storage facilities, and food plants, removing the need to collect, transport, and process cheese samples. For this review, we selected 71 papers (mainly dealing with prediction of the chemical composition of cheese) and summarized their results, focusing our attention on the major sources of variation in prediction accuracy related to cheese variability, spectrometer and spectra characteristics, and chemometrics techniques. The average coefficient of determination obtained from the validation samples ranged from 86 to 90% for predicting the moisture, fat, and protein contents of cheese, but was lower for predicting NaCl content and cheese pH (79 and 56%, respectively). There was wide variability with respect to all traits in the results of the various studies (standard deviation: 9–30%). This review draws attention to the need for more robust equations for predicting cheese composition in different situations; the calibration data set should consist of representative cheese samples to avoid bias due to an overly specific field of application and ensure the results are not biased for a particular category of cheese. Different spectrometers have different accuracies, which do not seem to depend on the spectrum extension. Furthermore, specific areas of the spectrum—the visible, infrared-A, or infrared-B range—may yield similar results to broad-range spectra; this is because several signals related to cheese composition are distributed along the spectrum. Small, portable instruments have been shown to be viable alternatives to large bench-top instruments. Last, chemometrics (spectra pre-treatment and prediction models) play an important role, especially with regard to difficult-to-predict traits. A proper, fully independent, validation strategy is essential to avoid overoptimistic results.
Cocoa shell is a by-product from cocoa industry which contains bioactive compounds of high and attractive value for food, pharmaceutical and cosmetics industry. However, cocoa shell can be ...contaminated by undesirable materials that, even in small amounts, would not change the color, aroma, and taste characteristics of the final product. Identification and prediction of this impurity are performed using expensive methods that require chemicals and produce residues. Thus, this work aims to investigate the performances of benchtop (867–2535 nm) and portable (900–1700 nm) near-infrared (NIR) spectrometer for fast prediction of cocoa shell powder impurities. Mixtures (n = 432) of cocoa shell powders with leaves, pods, stem fragments and nibs at several proportions (0–20 % w/w), were analyzed. Multivariate calibration models were developed using partial least-squares regression (PLSR) with raw spectra and various preprocessing approaches applied to the spectra. The most informative spectral variables were selected by variable importance in projection (VIP) method. Results obtained for the benchtop (R2P> 0.99 and RMSEP<0.71) and low-cost portable (R2P> 0.92 and RMSEP<1.70) devices are promising, and portable spectrometer could be used to certify cocoa shell purity.
Display omitted
•A rapid method for prediction of impurities in cocoa shell was investigated.•Low-cost handheld NIR spectrometer satisfactorily predicted impurities in cocoa shell.•Partial least square (PLS) regression demonstrated high accuracy and precision for prediction models.•VIP is a suitable method for variable selection in this application.•PLSR achieved R2 = 0.99 for benchtop and R2 = 0.92 for handheld devices.
Nuclear terrorism has the characteristics of strong concealment, great harm, wide range and complex composition. Once it happens, it will cause serious casualties, property losses and social panic. ...How to prevent nuclear terrorism has become one of the focuses of nuclear security work in various countries. In view of the slow speed of nuclide identification in the process of nuclear security, such as important traffic gates and international major events, through the overall optimization design of the system, the research of nuclear electronics and intelligent nuclide identification algorithm, this paper develops the advanced nuclear electronics module through the overall optimization design of the system, and innovatively designs the competitive weighted algorithm for intelligent nuclide identification. We have successfully developed a miniaturized, low-power portable CdZnTe(CZT) spectrometer. When the test index is 0.5 μSv/h higher than the background, the identification time of single nuclide 137Cs is with
Display omitted
•A novel PDMS@PDA@E. coli coated stir bar was prepared for specific extraction of TPMs.•A hand-held stir device is installed with the stir bar for on-site extraction of TPMs.•The ...assay can detect 4 TPMs with LOD of 0.13 μg/kg in aquatic samples within 30 min.
Rapid, accurate, and simultaneous detection of triphenylmethane (TPM) residues and their metabolites in aquaculture products is vital to ensure the safety of aquatic products. In this study, a novel Escherichia coli (E. coli) engineering bacteria-polydopamine (PDMS@PDA@E. coli) coated stir bar was prepared for the extraction and enrichment of malachite green (MG), leucomalachite green (LMG), crystal violet (CV), and leucocrystal violet (LCV), which are typical TPM drugs utilised in aquaculture. A PDMS stir bar was first modulated to show hydrophilic properties via plasma treatment to enhance the evenness and stability of PDA coating. Subsequently, the PDMS@PDA stir bar was adsorbed with E. coli to form PDMS@PDA@E. coli coating, which showed enhanced extraction capacity and selectivity towards TPMs. These characteristics were due to the specific adsorption properties of TPM dyes by Gram-negative bacteria. A hand-held stirring device was installed with the stir bar for on-site extraction. To directly detect the eluted targets without separation, a portable mass spectrometer was utilised. Under the optimal conditions, the samples can be rapidly pretreated (within 30 min) and used for the analysis of 4 TPMs with a recovery of 77.8 %-97.0 % together with the detection limits of 0.13–0.38 μg/kg. These findings prove that the assay has potential application value and broad prospects for the on-site detection of TPM residues in fish.
In this work, we study the detection of acetylene (C2H2), carbon dioxide (CO2) and water vapor (H2O) gases in the near-infrared (NIR) range using an on-chip silicon micro-electro-mechanical system ...(MEMS) Fourier transform infrared (FT-IR) spectrometer in the wavelength range 1300–2500 nm (4000–7692 cm−1). The spectrometer core engine is a scanning Michelson interferometer micro-fabricated using a deep-etching technology producing self-aligned components. The light is free-space propagating in-plane with respect to the silicon chip substrate. The moving mirror of the interferometer is driven by a relatively large stroke electrostatic comb-drive actuator corresponding to about 30 cm−1 resolution. Multi-mode optical fibers are used to connect light between the wideband light source, the interferometer, the 10 cm gas cell, and the optical detector. A wide dynamic range of gas concentration down to 2000 parts per million (ppm) in only 10 cm length gas cell is demonstrated. Extending the wavelength range to the mid-infrared (MIR) range up to 4200 nm (2380 cm−1) is also experimentally demonstrated, for the first time, using a bulk micro-machined on-chip MEMS FT-IR spectrometer. The obtained results open the door for an on-chip optical gas sensor for many applications including environmental sensing and industrial process control in the NIR/MIR spectral ranges.
Tree diseases endanger forestry and fruit tree plantations seriously worldwide in the past decades, leading to significant economic losses for the agricultural production sector. Rapid and accurate ...detection of tree diseases is crucial in tree protection. Despite molecular biological detection methods have prominent specificity, they are time-consuming and laborious, and are not suitable for large-scale detection of tree diseases. Spectroscopy with nondestructive, rapid, and high throughput characteristics has been applied to plant disease detection. Spectral detection systems are divided into three categories according to the spectrometer's carrying platform: portable hand-held spectrometer, airborne vehicle-mounted spectrometer, and large laboratory spectrometer. This review summarized three main spectral detection systems and their advantages and disadvantages in detecting various diseases of forestry and fruit trees: including detection of the single disease, multiple stress, and early disease using Visible/near-infrared, Raman, and hyperspectral imaging. Finally, spectroscopy detection technology applications of challenges were summarized, highlighting future trends.
On-site material inspection and quality analysis of food and agricultural produce require portable sensing systems. We report the development of a miniaturized spectrometer with an integrated light ...source operating in the visible and near-infrared range, for chemometrics based material-sensing applications. The proposed system uses off-the-shelf light source and detector. The electronic circuit is designed, developed, and tested in-house. To validate the system's usability, a set of classification experiments are carried out with measured spectra from culinary white powders and medicinal pills. Several classification algorithms are used to build predictive models and the best-suited ones give prediction accuracies of 80% and 92.6% respectively. A regression model built to estimate the curcumin content in turmeric shows a coefficient-of-determination of 0.97 for prediction. With more than 90% repeatability in the measured reflectance spectra, robustness of the device is demonstrated. Realization of a portable spectrometer, along with a framework for building appropriate prediction models, is expected to spur the development of point-of-use material sensing in the Vis-NIR range.
PDF
