查看更多>>摘要：Raman spectroscopy attempts to reflect food quality by characterizing molecular vibration and rotation. However, the blocking of optical signals by packaging materials and the interference of the optical signal generated by the packaging itself make the detection of internal food quality without destroying packaging highly difficult. In this regard, this paper proposes a novel packaged food internal signal separation based on spatially offset Raman spectroscopy (SORS) coupled with improved fast independent component analysis (FastICA). Firstly, the Raman scattering image of the packaged food with offset laser incident point was obtained. Then, the movable quadratic mean of information entropy was used to select the observation feature region of the image. Thirdly, the main independents decomposed by the optimized FastICA method were identified by spectral attenuation characteristics of the SORS peak signal. Finally, the non-negativity of the separated signal was ensured by baseline recognition and correction. The effectiveness of this method was verified by refactoring the similarity between the signal and the reference signal by testing three different packaging and four internal materials under standard experimental conditions. The applicability of the method was proved by the internal signal separation of three packaged foods on sale. The experimental results indicate that the proposed method can separate the Raman signal of packaged food and can be used as a pretreatment method and auxiliary analysis means for the detection of packaged food. (C) 2022 Elsevier B.V. All rights reserved.
查看更多>>摘要：Hyperspectral remote sensing is a rapid and nondestructive method to estimate the soil copper content. However, before establishing the spectral estimation model, it is crucial to preprocess the hyperspectral data to eliminate noise and highlight the spectral response characteristics of copper. The two commonly used spectral preprocessing approaches, i.e., the first- and second-order derivatives, may not provide sufficient information on the copper in the soil spectra. Therefore, this study investigates the potential of using the fractional-order derivative (FOD) of the spectra (FOD spectra) for estimating the soil copper content. A total of 170 soil samples were collected, and the soil reflectance spectra were measured outdoors using an ASD FieldSpec3 portable spectrometer. The soil copper content was obtained by chemical analysis in the laboratory. A quantitative estimation model of the soil copper content was established by combining the FOD spectra with different orders and using the partial least squares (PLS) method. The results revealed that the accuracy and prediction ability of the models using different orders of the FOD spectra varied significantly. The model using the 0.8-order FOD spectra performed the best, and the coefficient of determination (R-2) and the ratio of the performance to deviation (RPD) of the validation set were 0.6416 and 1.63, respectively. The performance of the model using three characteristic bands (2365.5 nm and 2375.5 nm of the 0.9-order derivatives and 864.5 nm of the 1.1-order derivatives) provided significantly better performance than utilizing all wavelength bands from 400 to 2400 nm. This model provided the optimum predictive ability (R-2: 0.6552 vs. 0.6416, RPD: 1.65 vs. 1.63) and was straightforward, requiring only three bands. These results show that it is feasible and practical to establish an accurate and rapid estimation model of the soil copper content using FOD spectra. (C) 2022 Elsevier B.V. All rights reserved.
查看更多>>摘要：As a fast and non-destructive detection method, near infrared spectroscopy, mainly containing overtones and combinations, can be used to quantify the components with a concentration of >= 1% in the analytical sample. Aquaphotomics uses the characteristic that the water structure changes with the addition of solute, which is reflected in the region of the water spectrum. Thus, it provides the possibility to unlock the information hidden in the spectrum. In our work, near infrared spectroscopy combined with aquaphotomics was used to quantify aqueous solution containing salvianolic acid B. It has shown that the aquaphotomics approach accurately quantifies the aqueous solution's salvianolic acid from 0.51 mg/mL to 25.86 mg/mL. The obtained RMSEP, R-2, RPD, and MRE of prediction were 0.52 mg/mL, 0.995, 14.88 and 4.74%, respectively. For the salvianolic acid A reaction solution, the predicted R-2 was 0.93, RMSEC was 0.85 mg/mL, and RMSEP was 0.82. The results of this study supported the concept of aquaphotomics, and the aquaphotomics approach was successfully applied in the reaction system of salvianolic acid A at 120 degrees C. This method was conducive to understanding the reaction and improving the accuracy of the quantitative model. It is a rapid and accurate alternative for analysis and measurement of transformation reactions at high temperature and high pressure, even for the substance with a concentration of less than 5 mg/mL. (C) 2022 Elsevier B.V. All rights reserved.
查看更多>>摘要：Here, the high fluorescent silicon-doped carbon quantum dots (Si-CQDs) were prepared by a facile and one-pot hydrothermal assay using 3-aminopropyltrimethoxysilane as the carbon and silicon source. The prepared Si-CQDs exhibit favorable water-soluble, high-temperature resistance, acid resistance, alkali resistance, high ionic strength resistance, high photostability, film-forming ability and solid-state fluorescence. Compared to other Si-CQDs that have been reported, the prepared Si-CQDs show unique up-conversion fluorescence. Furthermore, it is found that berberine hydrochloride (BH) can effectively quench the down- and up-conversion fluorescence of the Si-CQDs, making it can be used as a highly sensitive and specific probe for BH dual-mode sensing. Meanwhile, the linear range of down-conversion fluorescence detection for BH is 0.5-30.0 mu mol/L with a limit of detection (LOD) of 50 nmol/L, and the linear range of up-conversion fluorescence assay for BH is 0-25.0 mu mol/L. The mechanism of down-conversion fluorescence quenching by BH was investigated through a series of studies. The results show the quenching mechanism is the inner filter effect (IFE). Moreover, this proposed strategy has been well used to analyze BH in urine samples with satisfactory results. (C) 2022 Elsevier B.V. All rights reserved.
Li, Xin KangLi, Ze YingYang, Zhuo YingQiu, Dian...
7页
查看更多>>摘要：In this paper, a hybrid technique is proposed to establish quantitative models for the determination of target compounds in different spectral datasets. The proposed hybrid method is the hybridization of interval partial least squares (iPLS) method with gradient descent (GD) algorithm. Here, the novelty of the proposed method is that the iPLS method is applied to variable selection and the GD algorithm is employed to establish quantitative models based on the selected optimal variables. In the application of the hybrid iPLS-GD method, the factors, i.e., the number of the interval for the iPLS method and the learning rate, the number of iterations for the GD method, that affect the quantitative accuracy of the method are optimized and determined. Then three spectral datasets, including the near-infrared spectroscopy (NIR) dataset, nuclear magnetic resonance (H-1 NMR) dataset and excitation-emission matrix fluorescence (EEM) dataset, are used to test and verify the performance of the iPLS-GD method. We compare the hybrid iPLS-GD method with the PLS and iPLS methods from the aspects of modeling ability and predictive ability. The results demonstrated that the iPLS-GD method can be used as an effective and promising tool for the determination of target compounds in complex samples in practice. (C) 2022 Elsevier B.V. All rights reserved.
Taher-Ghahramani, FarhadZheng, FuluEisfeld, Alexander
8页
查看更多>>摘要：A common task is the determination of system parameters from spectroscopy, where one compares the experimental spectrum with calculated spectra, that depend on the desired parameters. Here we discuss an approach based on a machine learning technique, where the parameters for the numerical calculations are chosen from Gaussian Process Regression (GPR). This approach does not only quickly converge to an optimal parameter set, but in addition provides information about the complete parameter space, which allows for example to identify extended parameter regions where numerical spectra are consistent with the experimental one. We consider as example dimers of organic molecules and aim at extracting in particular the interaction between the monomers, and their mutual orientation. We find that indeed the GPR gives reliable results which are in agreement with direct calculations of these parameters using quantum chemical methods. (C) 2022 Elsevier B.V. All rights reserved.
Ulenikov, O. N.Gromova, O., VBekhtereva, E. S.Nikolaeva, N., I...
13页
查看更多>>摘要：The infrared spectra of germane, purified and enriched up to 88.1% of (GeH4)-Ge-76, was measured at the temperature of (22.6 +/- 0.1) degrees C and different pressures with a Bruker Fourier transform infrared spectrometer IFS125HR and analyzed for the first time in the region of 2700-3200 cm(-1 )where the stretching-bending Tetrad (nu(1) + nu(2), nu(1) + nu(4), nu(2) + nu(3) and nu(3) + nu(4) bands) of the ro-vibrational Octad of germane is located. The 3595 transitions belonging to the eight sub-bands of the Tetrad were assigned and theoretically analysed in the frame of the effective Hamiltonian model. The obtained set of 106 fitted parameters reproduces the initial 3595 experimental line positions with the d(rms) = 6.81 x 10(-4 )cm(-1). The presence of numerous resonance interactions in the Tetrad is discussed. (C) 2022 Elsevier B.V. All rights reserved.
查看更多>>摘要：The higher chalkiness level of the white core kernel is prone to breakage during the high degree polishing. So, grading white core kernel based on chalkiness level is crucial to making premium quality Sake (rice wine) in the brewing industry. The chalkiness level in the white core kernel is currently performed destructively. Thus, a chalkiness index is required to assess the level in the white core kernel. This research assesses the white core rice kernel based on the chalkiness index non-destructively. Here, the optical transmission property in the visible to near-infrared (VIS-NIR) region of rice was measured using a V-670 spectrophotometer equipped with an integrating sphere to investigate the variation of chalkiness level rice samples. The images were then acquired by transmission mode of four types of intact Sake rice kernel using blue light-emitting diodes (LEDs), green, red, and NIR LEDs in which the peak wavelength of the LEDs was 465 nm, 525 nm, 630 nm, and 830 nm, respectively. The result indicates that the rice samples were more penetrated and better visualized chalkiness by light in the NIR region. Therefore, the wavelength region in NIR showed better discrimination between transparent and opaque parts in white core's Sake rice. Furthermore, the proposed chalkiness index was inversely correlated with the gray-level intensity of the transmittance image. This gray value was significantly correlated (R-2 = 0.89) with the chalkiness index in the NIR region. So, gray values of NIR transmittance images were identified as sensitive for chalkiness index, which would be applied for sorting the white core kernel with different levels of chalkiness in the Sake brewing industry. (C) 2022 Elsevier B.V. All rights reserved.
Brito, Anna Luiza B.Brueggen, CarlottaIldiz, Gulce OgrucFausto, Rui...
13页
查看更多>>摘要：The ending of estrogen production in the ovaries after menopause results in a series of important physiologic changes, including hair texture and growth. In this study we demonstrate that Raman spectroscopy can be used successfully as a tool to probe menopause-induced changes on hair, in particular when coupled with suitable chemometrics approaches. The detailed analysis of the average Raman spectra (in particular of the Amide I and vS-S stretching spectral regions) of the hair samples of women pre- and post-menopause allowed to estimate that absence of estrogen in post-menopause women leads to an average reduction of similar to 12% in the thickness of the hair cuticle, compared to that of pre-menopause women, and revealed the strong prevalence of disulphide bonds in the most stable gauche-gauche-gauche conformation in the hair cuticle. From the analysis of the vS-S stretching spectral region it could also be concluded that the amount of alpha-helix keratin is slightly higher for post-menopause than for pre-menopause women. A series of statistical models were developed in order to classify the hair samples. Outperforming the traditional PCA-LDA (principal component analysis - linear discriminant analysis) approach, in the present study a GA-LDA (genetic algorithm - linear discriminant analysis) strategy was used for variable reduction/selection and samples' classification. This strategy allowed to develop of a statistical model (L16), which has exceptional prediction capability (total accuracy of 96.6%, with excellent sensitivity and selectivity) and can be used as an efficient instrument for the hair samples' classification. In addition, a new chemometrics approach is here presented, which allows to overcome the intrinsic limitations of the GA algorithm and that can be used to develop statistical models that use GA as the variable reduction/selection method, but superseding its stochastic nature. Three suitable models for classification of the hair samples according to the menopause status of the women were developed using this novel approach (LV17, BLV20 and PLS7 models), which are based on the Fisher's and Bayers' LDA approaches and the PLS-DA method. The followed new chemometrics approach uses the results of a large set of GA-LDA runs over the full data matrix for the selection of the reduced data matrices. The criterion for the selection of the variables is their statistical significance in terms of number of occurrences as solutions of the whole set of GA-LDA runs. (C) 2022 Elsevier B.V. All rights reserved.
查看更多>>摘要：The excited-state intramolecular proton transfer (ESIPT) mechanism, photophysical properties of 8-(benzo[D] thiazole-2-yl)-7-hydroxy-2H-benzopyran-2-one (L-HKS) and the effect of O/Se atomic substitution on L-HKS have been studied in detail based on density functional theory (DFT) and timedependent DFT (TD-DFT) methods. The S atom in the thiazole ring of L-HKS has been replaced by O/Se atom (denoted to L-HKO/L-HKSe) to analyze the effects of atomic electronegativity on the intramolecular H-bond, absorption/emission spectrum and ESIPT process. Through the analysis of series of calculated results, it can be found that the intramolecular H-bonds at normal form and tautomer form are enhanced and weakened in the S-1 state, respectively, which is favorable to ESIPT process. The potential energy curves revealed that the ESIPT process is much easier to occur gradually from L-HKO to L-HKS and L-HKSe, as the electron-withdrawing ability of atom (from O to S and Se) is weakened. The atomic substitution also has an effect on the photophysical properties. From L-HKO to L-HKS, the emission peak at tautomer form red-shifts 70 nm. The energy gaps of the three compounds follow the decreased order of L-HKO (4.866 eV) > L-HKS (4.753 eV) > L-HKSe (4.371 eV) with the weakened electron-withdrawing ability of atom (from O to S and Se), which leads to the gradual red-shift of the absorption spectra from L-HKO to L-HKS and L-HKSe. (C) 2022 Elsevier B.V. All rights reserved.
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