Jintao Liu, Li Luo, Xiangyang Yu, Yefan Cai, Weibin Hong
Spectral imaging is performed primarily using reflective devices, but for transparent objects, especially transparent liquids, a transmission-based device is required to obtain more effective spectral imaging data. For this purpose, a transmitted spectral imaging data acquisition device based on a miniature multispectral spectrometer was developed and demonstrated its capability in the analysis of transparent liquids. This device allows rapid and noncontact acquisition of spectral imaging signals from transparent liquid samples. The design of the device mainly includes two parts: a shooting system and a master computer, and the optical path is optimized by selecting the appropriate diffusion plate. As an application example, a concentration-absorbance model of liquid samples at characteristic wavelengths was established and used to predict the concentrations of different liquid samples. Experimental results showed that the relative error of the predicted concentration values was within 4%, indicating excellent detection performance. Therefore, the design of the device demonstrates favorable feasibility and wide applicability in liquid detection systems.
{"title":"Design and Application of a Liquid Detection Device Based on Transmission Near-Infrared Spectroscopic Imaging","authors":"Jintao Liu, Li Luo, Xiangyang Yu, Yefan Cai, Weibin Hong","doi":"10.1155/2024/8925458","DOIUrl":"https://doi.org/10.1155/2024/8925458","url":null,"abstract":"Spectral imaging is performed primarily using reflective devices, but for transparent objects, especially transparent liquids, a transmission-based device is required to obtain more effective spectral imaging data. For this purpose, a transmitted spectral imaging data acquisition device based on a miniature multispectral spectrometer was developed and demonstrated its capability in the analysis of transparent liquids. This device allows rapid and noncontact acquisition of spectral imaging signals from transparent liquid samples. The design of the device mainly includes two parts: a shooting system and a master computer, and the optical path is optimized by selecting the appropriate diffusion plate. As an application example, a concentration-absorbance model of liquid samples at characteristic wavelengths was established and used to predict the concentrations of different liquid samples. Experimental results showed that the relative error of the predicted concentration values was within 4%, indicating excellent detection performance. Therefore, the design of the device demonstrates favorable feasibility and wide applicability in liquid detection systems.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"37 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141191341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nan Zhou, Jin Hong, Bo Song, Shichao Wu, Yichen Wei, Tao Wang
The hydrological cycle, surface energy balance, and the management of water resources are all significantly impacted by soil moisture. Because it governs the physical processes of evapotranspiration and rainfall penetration, surface soil moisture is a significant climatic variable. In this work, visible-near infrared (VIS-NIR) bands were used to compare and analyze the spectra of loess samples with varying moisture concentrations. The investigation looked at how changes in the soil moisture content impacted the response of the soil spectra. The researchers used a genetic algorithm (GA), interval combination optimization (ICO), and competitive adaptive reweighted sampling (CARS) to filter feature variables from full-band spectral data. To forecast the moisture content of loess on the soil surface, models like partial least squares regression (PLSR), support vector machine (SVM), and random forest (RF) were created. The findings indicate that: (1) the most reliable spectrum preprocessing technique is the first derivative (FD), which can significantly enhance the model’s prediction power and spectral characteristic information. (2) The feature band selection method’s prediction effect of soil moisture content is typically superior to that of full-spectrum data. (3) The random forest (RF) prediction model for soil moisture content with the highest accuracy was built by combining the genetic algorithm (GA) with the FD preprocessed spectra. The results may provide a new understanding on how to use VIS-NIR to measure soil moisture content.
{"title":"Feature Variable Selection Based on VIS-NIR Spectra and Soil Moisture Content Prediction Model Construction","authors":"Nan Zhou, Jin Hong, Bo Song, Shichao Wu, Yichen Wei, Tao Wang","doi":"10.1155/2024/8180765","DOIUrl":"https://doi.org/10.1155/2024/8180765","url":null,"abstract":"The hydrological cycle, surface energy balance, and the management of water resources are all significantly impacted by soil moisture. Because it governs the physical processes of evapotranspiration and rainfall penetration, surface soil moisture is a significant climatic variable. In this work, visible-near infrared (VIS-NIR) bands were used to compare and analyze the spectra of loess samples with varying moisture concentrations. The investigation looked at how changes in the soil moisture content impacted the response of the soil spectra. The researchers used a genetic algorithm (GA), interval combination optimization (ICO), and competitive adaptive reweighted sampling (CARS) to filter feature variables from full-band spectral data. To forecast the moisture content of loess on the soil surface, models like partial least squares regression (PLSR), support vector machine (SVM), and random forest (RF) were created. The findings indicate that: (1) the most reliable spectrum preprocessing technique is the first derivative (FD), which can significantly enhance the model’s prediction power and spectral characteristic information. (2) The feature band selection method’s prediction effect of soil moisture content is typically superior to that of full-spectrum data. (3) The random forest (RF) prediction model for soil moisture content with the highest accuracy was built by combining the genetic algorithm (GA) with the FD preprocessed spectra. The results may provide a new understanding on how to use VIS-NIR to measure soil moisture content.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"210 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141063441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Soybean saponin is a natural antioxidant and is anti-inflammatory. Hyperspectral analysis technology was applied to detect soybean saponin content rapidly and nondestructively in this paper. Firstly, spectral preprocessing methods were studied, and standard normal variable (SNV) was used to remove noise information. Secondly, a two-step hybrid variable selection approach based on synergy interval partial least squares (SiPLS) and iteratively retains informative variables (IRIV) was proposed to extract characteristic variables. Then, the ensemble learning model was constructed by back propagation neural network (BPNN), deep forest (DF), partial least squares regression (PLSR), and extreme gradient boosting (EXG). Finally, image information was combined into spectral data to improve model accuracy. The prediction coefficient of determination () of the final model reached 0.9216. It can provide rapid, nondestructive, and accurate detection technology of soybean saponin content. A combination of spectral and image information will provide a new idea for application of hyperspectral.
{"title":"Soybean Saponin Content Detection Based on Spectral and Image Information Combination","authors":"Hongmin Sun, Xifan Meng, Yingpeng Han, Xiao Li, Xiaoming Li, Yongguang Li","doi":"10.1155/2024/7599132","DOIUrl":"https://doi.org/10.1155/2024/7599132","url":null,"abstract":"Soybean saponin is a natural antioxidant and is anti-inflammatory. Hyperspectral analysis technology was applied to detect soybean saponin content rapidly and nondestructively in this paper. Firstly, spectral preprocessing methods were studied, and standard normal variable (SNV) was used to remove noise information. Secondly, a two-step hybrid variable selection approach based on synergy interval partial least squares (SiPLS) and iteratively retains informative variables (IRIV) was proposed to extract characteristic variables. Then, the ensemble learning model was constructed by back propagation neural network (BPNN), deep forest (DF), partial least squares regression (PLSR), and extreme gradient boosting (EXG). Finally, image information was combined into spectral data to improve model accuracy. The prediction coefficient of determination (<span><svg height=\"11.7978pt\" style=\"vertical-align:-0.2063999pt\" version=\"1.1\" viewbox=\"-0.0498162 -11.5914 13.2276 11.7978\" width=\"13.2276pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"></path></g><g transform=\"matrix(.0091,0,0,-0.0091,8.151,-5.741)\"></path></g></svg>)</span> of the final model reached 0.9216. It can provide rapid, nondestructive, and accurate detection technology of soybean saponin content. A combination of spectral and image information will provide a new idea for application of hyperspectral.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"107 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140933614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yasir Hanif Mir, Anzhen Qin, Shakeel Mir, Shafeeq Ur Rahman, Mehnaza Mushtaq, Mumtaz A. Ganie, M. H. Chesti, Javid A. Bhat, Zahoor A. Baba, M. Auyoub Bhat, Inayat M. Khan, Rehana Rasool, Aanisa Manzoor Shah, Shazia Sadiq, Syed Mohammed Basheeruddin Asdaq, Mohammad Javed Ansari, Ghulam Yasin
Soils exhibit structural heterogeneity across diverse spatio-temporal scales, yielding myriad of microhabitats, highlighting the need for a nuanced understanding of the intricate interactions within the soil matrix. At the nanometer scale, the interplay among organic matter (OM), mineral particles, and microbiota intricately govern the long-term destiny of soil carbon (C), nutrient cycling, and the fate of both organic and inorganic pollutants. Notably, the sorption of soil organic matter (SOM) onto smaller clay particles and its entrapment in microaggregates further contribute to this complex dynamic. Understanding these processes depends on recognizing their scale-dependent nature, necessitating sophisticated techniques for investigation. Although various methods are employed across scales, the current set of techniques still lacks the requisite sensitivity and resolution for microscale data collection. To address this limitation, the adoption of novel microscopic and spectroscopic techniques capable of probing molecular, isotopic, and elemental patterns at the micro to nano scale becomes imperative. Among these cutting-edge methodologies, the nano-scale secondary ion mass spectrometer (NanoSIMS) emerges as a paradigm-shifting tool. Representing the latest evolution in ion microprobes, NanoSIMS seamlessly integrates high-resolution microscopy and isotopic analysis, maintaining unparalleled signal transmission and spatial resolution, reaching as fine as 50 nm. Its capabilities extend beyond conventional applications in science, as evidenced by recent breakthroughs in utilizing NanoSIMS to study biophysical interfaces in soils. This article underscores the pressing need to advance the incorporation of NanoSIMS as a pioneering instrumentation technique in soil studies. Furthering the implementation of this novel instrumentation technique in soil studies will pave avenues and aid in the advancement of future research.
{"title":"Nano-Scale Secondary Ion Mass Spectrometry: A Paradigm Shift in Soil Science","authors":"Yasir Hanif Mir, Anzhen Qin, Shakeel Mir, Shafeeq Ur Rahman, Mehnaza Mushtaq, Mumtaz A. Ganie, M. H. Chesti, Javid A. Bhat, Zahoor A. Baba, M. Auyoub Bhat, Inayat M. Khan, Rehana Rasool, Aanisa Manzoor Shah, Shazia Sadiq, Syed Mohammed Basheeruddin Asdaq, Mohammad Javed Ansari, Ghulam Yasin","doi":"10.1155/2024/3625623","DOIUrl":"https://doi.org/10.1155/2024/3625623","url":null,"abstract":"Soils exhibit structural heterogeneity across diverse spatio-temporal scales, yielding myriad of microhabitats, highlighting the need for a nuanced understanding of the intricate interactions within the soil matrix. At the nanometer scale, the interplay among organic matter (OM), mineral particles, and microbiota intricately govern the long-term destiny of soil carbon (C), nutrient cycling, and the fate of both organic and inorganic pollutants. Notably, the sorption of soil organic matter (SOM) onto smaller clay particles and its entrapment in microaggregates further contribute to this complex dynamic. Understanding these processes depends on recognizing their scale-dependent nature, necessitating sophisticated techniques for investigation. Although various methods are employed across scales, the current set of techniques still lacks the requisite sensitivity and resolution for microscale data collection. To address this limitation, the adoption of novel microscopic and spectroscopic techniques capable of probing molecular, isotopic, and elemental patterns at the micro to nano scale becomes imperative. Among these cutting-edge methodologies, the nano-scale secondary ion mass spectrometer (NanoSIMS) emerges as a paradigm-shifting tool. Representing the latest evolution in ion microprobes, NanoSIMS seamlessly integrates high-resolution microscopy and isotopic analysis, maintaining unparalleled signal transmission and spatial resolution, reaching as fine as 50 nm. Its capabilities extend beyond conventional applications in science, as evidenced by recent breakthroughs in utilizing NanoSIMS to study biophysical interfaces in soils. This article underscores the pressing need to advance the incorporation of NanoSIMS as a pioneering instrumentation technique in soil studies. Furthering the implementation of this novel instrumentation technique in soil studies will pave avenues and aid in the advancement of future research.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"14 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140836372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bin Jia, Ziying Mai, Chaoqun Xiang, Qiwen Chen, Min Cheng, Longkai Zhang, Xue Xiao
The precise and prompt determination of quality control indicators such as moisture, stilbene glycosides, and anthraquinone glycosides is crucial in assessing the quality of Polygoni Multiflori Radix. Near-infrared spectroscopy is a nondestructive analytical technique that offers a more desirable approach than traditional methods for assessing content levels. In this study, various spectral preprocessing techniques were used to preprocess the raw spectral data. The spectral data were correlated with the determination of three-component contents using the partial least squares regression (PLSR) method. Then different algorithms, such as competitive adaptive weighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE), and random frog hopping (RF), were used for model simplification and feature selection. The data suggest that the first-order deconvolution derivative (1st Dev.) processing of the spectral data is superior to other methods in all three model evaluation metrics. The PLSR model for moisture, stilbene glycosides, and anthraquinone glycosides produced the calibration coefficient of determination (R2C) of 0.82, 0.52, and 0.58, the root mean square error of cross validation (RMSECV) of 0.91%, 0.77%, and 0.69%, the prediction coefficient of determination (R2P) of 0.72, 0.28, and 0.54, the root mean square error of prediction (RMSEP) of 0.65%, 0.81%, and 0.75%, and relative percentage differences (RPDs) of 1.7, 1.0, and 0.8. After optimizing the model using CARS, R2C increased by 0.15%, 0.41%, and 0.34%, RMSECV decreased by 0.53%, 0.32%, and 0.24%, R2P increased by 0.21%, 0.63%, and 0.35%, RMSEP decreased by 0.36%, 0.41%, and 0.31%, and RPD increased by 1.1, 0.9, and 0.6, significantly improving the predictive capacity of the model. This research provides a feasible method for rapid compliance testing of Polygoni Multiflori Radix. To further improve the model’s performance and applicability, it is necessary to continuously expand the sample set with different varieties and locations for wide variation.
{"title":"Rapid Quality Assessment of Polygoni Multiflori Radix Based on Near-Infrared Spectroscopy","authors":"Bin Jia, Ziying Mai, Chaoqun Xiang, Qiwen Chen, Min Cheng, Longkai Zhang, Xue Xiao","doi":"10.1155/2024/2477754","DOIUrl":"https://doi.org/10.1155/2024/2477754","url":null,"abstract":"The precise and prompt determination of quality control indicators such as moisture, stilbene glycosides, and anthraquinone glycosides is crucial in assessing the quality of <i>Polygoni Multiflori</i> Radix. Near-infrared spectroscopy is a nondestructive analytical technique that offers a more desirable approach than traditional methods for assessing content levels. In this study, various spectral preprocessing techniques were used to preprocess the raw spectral data. The spectral data were correlated with the determination of three-component contents using the partial least squares regression (PLSR) method. Then different algorithms, such as competitive adaptive weighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE), and random frog hopping (RF), were used for model simplification and feature selection. The data suggest that the first-order deconvolution derivative (1<sup>st</sup> Dev.) processing of the spectral data is superior to other methods in all three model evaluation metrics. The PLSR model for moisture, stilbene glycosides, and anthraquinone glycosides produced the calibration coefficient of determination (<i>R</i><sup>2</sup><sub><i>C</i></sub>) of 0.82, 0.52, and 0.58, the root mean square error of cross validation (RMSE<sub>CV</sub>) of 0.91%, 0.77%, and 0.69%, the prediction coefficient of determination (<i>R</i><sup>2</sup><sub><i>P</i></sub>) of 0.72, 0.28, and 0.54, the root mean square error of prediction (RMSE<sub><i>P</i></sub>) of 0.65%, 0.81%, and 0.75%, and relative percentage differences (RPDs) of 1.7, 1.0, and 0.8. After optimizing the model using CARS, <i>R</i><sup>2</sup><sub><i>C</i></sub> increased by 0.15%, 0.41%, and 0.34%, RMSE<sub><i>CV</i></sub> decreased by 0.53%, 0.32%, and 0.24%, <i>R</i><sup>2</sup><sub><i>P</i></sub> increased by 0.21%, 0.63%, and 0.35%, RMSE<sub><i>P</i></sub> decreased by 0.36%, 0.41%, and 0.31%, and RPD increased by 1.1, 0.9, and 0.6, significantly improving the predictive capacity of the model. This research provides a feasible method for rapid compliance testing of <i>Polygoni Multiflori</i> Radix. To further improve the model’s performance and applicability, it is necessary to continuously expand the sample set with different varieties and locations for wide variation.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"30 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140172007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Romcevic, B. Hadzic, P. Dziawa, T. Story, W. D. Dobrowolski, M. Romcevic
Lead telluride and germanium telluride are well-known IV-VI semiconductors, which is now the focus of research due to the perspective of application as thermoelectrics for midrange temperatures. Solid solutions and heterostructures on this basis, obtained by molecular beam epitaxy, are a promising direction for the development of these materials. In this paper, we have focused on the Raman spectra excited by the 514.5 nm laser line (out of resonance) of PbTe, GeTe, (Pb, Ge)Te, and (Pb, Ge, Eu)Te layers grown on BaF2 (111) monocrystalline substrates. The obtained phonon properties are related to the properties of the corresponding bulk materials or can be explained by a model that takes into account the difference in the masses of the constituent elements only, as is the case with the local mode of Ge in PbTe (registered at about 181 cm−1). Multiphonon processes registered for this phonon are a consequence of the change in the electronic structure of PbTe and electron-phonon interaction. An improvement in the quality of thin films due to doping with Eu ions was also registered.
{"title":"Raman Spectra of PbTe- and GeTe-Based Monocrystalline Epitaxial Layers","authors":"N. Romcevic, B. Hadzic, P. Dziawa, T. Story, W. D. Dobrowolski, M. Romcevic","doi":"10.1155/2024/5524783","DOIUrl":"https://doi.org/10.1155/2024/5524783","url":null,"abstract":"Lead telluride and germanium telluride are well-known IV-VI semiconductors, which is now the focus of research due to the perspective of application as thermoelectrics for midrange temperatures. Solid solutions and heterostructures on this basis, obtained by molecular beam epitaxy, are a promising direction for the development of these materials. In this paper, we have focused on the Raman spectra excited by the 514.5 nm laser line (out of resonance) of PbTe, GeTe, (Pb, Ge)Te, and (Pb, Ge, Eu)Te layers grown on BaF<sub>2</sub> (111) monocrystalline substrates. The obtained phonon properties are related to the properties of the corresponding bulk materials or can be explained by a model that takes into account the difference in the masses of the constituent elements only, as is the case with the local mode of Ge in PbTe (registered at about 181 cm<sup>−1</sup>). Multiphonon processes registered for this phonon are a consequence of the change in the electronic structure of PbTe and electron-phonon interaction. An improvement in the quality of thin films due to doping with Eu ions was also registered.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"115 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140106251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gem-quality blue octahedral crystalline gahnite was produced in Nigeria. This paper investigated gemological and spectroscopic characteristics by basic gemological experiments, electron probes, infrared reflectance spectroscopy, laser Raman spectroscopy, photoluminescence spectroscopy, and ultraviolet-visible spectroscopy. The results show that the refractive index (RI) of Nigerian gahnite is 1.792∼1.794, and the specific gravity is 4.45∼4.66, with no fluorescence. The main chemical composition is ZnAl2O4, accounting for 93.57%, and the rest is mainly FeAl2O4, which also contains Na, Mg, Co, Mn, Cr, Cu, Si, K, and Ca elements. The infrared spectra showed midinfrared absorption bands near 510 cm−1, 559 cm−1, and 664 cm−1 in the fingerprint region, corresponding to the Zn-O stretching vibration, bending vibration, and Al-O bending vibration, respectively. The Raman spectra showed three of the five Raman active modes of the spinel group, with characteristic Raman absorption peaks located at 418 cm−1, 508 cm−1, and 660 cm−1, corresponding to Eg, T2g(2), and T2g(3) modes, respectively, and the comparison revealed a higher degree of Zn and Al ordering in this paper for gahnite. The photoluminescence spectra show the common Cr3+-activated fluorescence splitting peaks of natural spinel, of which the 686 nm (R-line) fluorescence peak is obvious and sharp. The UV-vis absorption spectra located at 444 nm and 489 nm are the most obvious, which are caused by the d-d electron leap of TFe2+ (5E ⟶ 5T2), and the blue-gray tones of the samples are mainly caused by the spin-forbidden electronic transitions in TFe2+ and MFe2+ ↔ MFe3+; the weak absorption peak at 609 nm was determined to be associated with Co2+ by derivative spectra.
{"title":"Gemological and Spectral Characteristics of Gem-Quality Blue Gahnite from Nigeria","authors":"Yifang Chen, Junhao Zheng, Mingmei Lu, Ziqi Liu, Zhengyu Zhou","doi":"10.1155/2024/6693346","DOIUrl":"https://doi.org/10.1155/2024/6693346","url":null,"abstract":"Gem-quality blue octahedral crystalline gahnite was produced in Nigeria. This paper investigated gemological and spectroscopic characteristics by basic gemological experiments, electron probes, infrared reflectance spectroscopy, laser Raman spectroscopy, photoluminescence spectroscopy, and ultraviolet-visible spectroscopy. The results show that the refractive index (RI) of Nigerian gahnite is 1.792∼1.794, and the specific gravity is 4.45∼4.66, with no fluorescence. The main chemical composition is ZnAl<sub>2</sub>O<sub>4</sub>, accounting for 93.57%, and the rest is mainly FeAl<sub>2</sub>O<sub>4</sub>, which also contains Na, Mg, Co, Mn, Cr, Cu, Si, K, and Ca elements. The infrared spectra showed midinfrared absorption bands near 510 cm<sup>−1</sup>, 559 cm<sup>−1</sup>, and 664 cm<sup>−1</sup> in the fingerprint region, corresponding to the Zn-O stretching vibration, bending vibration, and Al-O bending vibration, respectively. The Raman spectra showed three of the five Raman active modes of the spinel group, with characteristic Raman absorption peaks located at 418 cm<sup>−1</sup>, 508 cm<sup>−1</sup>, and 660 cm<sup>−1</sup>, corresponding to E<sub>g</sub>, T<sub>2g(2)</sub>, and T<sub>2g(3)</sub> modes, respectively, and the comparison revealed a higher degree of Zn and Al ordering in this paper for gahnite. The photoluminescence spectra show the common Cr<sup>3+</sup>-activated fluorescence splitting peaks of natural spinel, of which the 686 nm (R-line) fluorescence peak is obvious and sharp. The UV-vis absorption spectra located at 444 nm and 489 nm are the most obvious, which are caused by the <i>d-d</i> electron leap of <sup>T</sup>Fe<sup>2+</sup> (<sup>5</sup>E ⟶ <sup>5</sup>T<sub>2</sub>), and the blue-gray tones of the samples are mainly caused by the spin-forbidden electronic transitions in <sup>T</sup>Fe<sup>2+</sup> and <sup>M</sup>Fe<sup>2+</sup> ↔ <sup>M</sup>Fe<sup>3+</sup>; the weak absorption peak at 609 nm was determined to be associated with Co<sup>2+</sup> by derivative spectra.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"25 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139750599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Honey is considered as a premium food produced by honeybees. It is highly appreciated by consumers around the world and raises a major concern nowadays which is ensuring its authenticity in respect to its production and its botanical origin. In Lebanon, honey is mainly multifloral which makes its authentication rather difficult. While mid-infrared (MIR) spectroscopy combined with multivariate analysis has proven to be successful in authenticating unifloral honey, the challenge with Lebanese honey lies in assessing its performance with multifloral honey. Therefore, this work aims to test the performance of common components analysis (CCA) applied on mid-infrared spectra in the authentication of multifloral Lebanese honey. For this purpose, 96 multifloral Lebanese honey samples of different floral sources were collected from different regions of the Lebanese territory and analyzed using MIR spectroscopy. CCA applied to the spectral data, allowed a separation between honeydew honey samples and floral honey samples. In addition, honey samples collected from the Bekaa plain region were differentiated from the other honey samples collected from all the other Lebanese geographical regions. This discrimination between the groups of honey samples is based essentially on their sugar composition.
蜂蜜被认为是蜜蜂生产的优质食品。它受到世界各地消费者的高度赞赏，并引起了当今人们的主要关注，即确保其生产和植物来源的真实性。在黎巴嫩，蜂蜜主要是多花蜂蜜，这就给蜂蜜的鉴定带来了很大困难。事实证明，中红外（MIR）光谱与多元分析相结合可成功鉴定单花蜜，但黎巴嫩蜂蜜面临的挑战在于评估其在多花蜜方面的性能。因此，这项工作的目的是测试在中红外光谱上应用常见成分分析法（CCA）鉴定黎巴嫩多花蜂蜜的性能。为此，我们从黎巴嫩不同地区采集了 96 个不同花源的黎巴嫩多花蜂蜜样品，并使用中红外光谱进行了分析。将 CCA 应用于光谱数据，可以将蜜露蜂蜜样本和花蜜样本区分开来。此外，从贝卡平原地区采集的蜂蜜样品也与从黎巴嫩其他地区采集的蜂蜜样品区分开来。各组蜂蜜样品之间的区分主要基于其糖分组成。
{"title":"Application of Common Components Analysis to Mid-Infrared Spectra for the Authentication of Lebanese Honey","authors":"Rita El Hajj, Wadih Skaff, Nathalie Estephan","doi":"10.1155/2024/3370665","DOIUrl":"https://doi.org/10.1155/2024/3370665","url":null,"abstract":"Honey is considered as a premium food produced by honeybees. It is highly appreciated by consumers around the world and raises a major concern nowadays which is ensuring its authenticity in respect to its production and its botanical origin. In Lebanon, honey is mainly multifloral which makes its authentication rather difficult. While mid-infrared (MIR) spectroscopy combined with multivariate analysis has proven to be successful in authenticating unifloral honey, the challenge with Lebanese honey lies in assessing its performance with multifloral honey. Therefore, this work aims to test the performance of common components analysis (CCA) applied on mid-infrared spectra in the authentication of multifloral Lebanese honey. For this purpose, 96 multifloral Lebanese honey samples of different floral sources were collected from different regions of the Lebanese territory and analyzed using MIR spectroscopy. CCA applied to the spectral data, allowed a separation between honeydew honey samples and floral honey samples. In addition, honey samples collected from the Bekaa plain region were differentiated from the other honey samples collected from all the other Lebanese geographical regions. This discrimination between the groups of honey samples is based essentially on their sugar composition.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"24 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139750601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Soil water content is a critical environmental parameter in research and practice, though various technological and contextual constraints limit its estimation in arid areas with vegetation cover. This study combined the multitemporal remote sensing data of Sentinel-1 and Landsat 8 to conduct an inversion study on surface soil water content under low vegetation cover in Nagqu, central Tibetan Plateau. Four vegetation indices (NDVI, ARVI, EVI, and RVI) were extracted from optical remote sensing data. A water cloud model was used to eliminate the influence of the vegetation layer on the backscattering coefficient associated with vegetation cover, and a predictive model suitable for the Nagqu area was constructed. The water cloud model effectively incorporated a vegetation index instead of vegetation water content. We found that VV polarization was more suitable for soil water content inversion than VH polarization. Among the four vegetation indices, the soil water content inversion model constructed with RVI under VV polarization had the best fit (R2 = 0.8212; RMSE = 6.30). The second-best fit was observed for vegetation water content-NDVI (R2 = 0.8201). The soil water content inversion models all had an R2 > 0.6, regardless of the vegetation index used, though the RVI had the best fitting effect, indicating that this vegetation index is highly applicable in the water cloud model, as a substitute for vegetation water content, and is expected to perform well in similar study sites.
{"title":"Collaborative Inversion of Soil Water Content in Alpine Meadow Area Based on Multitemporal Polarimetric SAR and Optical Remote Sensing Data","authors":"Meng Kong, Xiaoqing Zuo, Yongfa Li","doi":"10.1155/2024/2585610","DOIUrl":"https://doi.org/10.1155/2024/2585610","url":null,"abstract":"Soil water content is a critical environmental parameter in research and practice, though various technological and contextual constraints limit its estimation in arid areas with vegetation cover. This study combined the multitemporal remote sensing data of Sentinel-1 and Landsat 8 to conduct an inversion study on surface soil water content under low vegetation cover in Nagqu, central Tibetan Plateau. Four vegetation indices (NDVI, ARVI, EVI, and RVI) were extracted from optical remote sensing data. A water cloud model was used to eliminate the influence of the vegetation layer on the backscattering coefficient associated with vegetation cover, and a predictive model suitable for the Nagqu area was constructed. The water cloud model effectively incorporated a vegetation index instead of vegetation water content. We found that VV polarization was more suitable for soil water content inversion than VH polarization. Among the four vegetation indices, the soil water content inversion model constructed with RVI under VV polarization had the best fit (<i>R</i><sup>2</sup> = 0.8212; RMSE = 6.30). The second-best fit was observed for vegetation water content-NDVI (<i>R</i><sup>2</sup> = 0.8201). The soil water content inversion models all had an <i>R</i><sup>2</sup> > 0.6, regardless of the vegetation index used, though the RVI had the best fitting effect, indicating that this vegetation index is highly applicable in the water cloud model, as a substitute for vegetation water content, and is expected to perform well in similar study sites.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"99 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139559812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sedimentary rocks are produced by the weathering of preexisting rocks and the subsequent transportation and deposition of the weathering products. Among the sedimentary rocks, especially limestone is a crucial raw material for cement production. The purpose of this study was to characterize the valuable industrial raw materials, limestone, gypsum, clay, coal, and iron ore, along with the Nile River basin. For sample collection, a random sampling method was applied. Different analytical methods were carried out for complete oxide analysis such as LiBO2 fusion, HF attack, and gravimetric, calorimetric, and atomic absorption spectroscopy (AAS). The percentages of oxides detected in this study are in the range of acceptable values (high content of CaO ranging from 47.3 to 50.4% and less content of SiO2 ranging from 8.72 to 11.24%) for good proposal as a potential raw material for cement production. The most dominant and wide-range coverage of limestone along with the Nile basin, particularly near Arsema Monastery, was found as matured limestone. The petrographic analysis of gypsum, sandstone, and clay samples indicated that all the samples taken from Wegidi revealed that the high percentage of gypsum ranges from 90 to 95%. Sandstone is dominantly preset in Kelala to Jamma road along with Beto River with high content of SiO2 ranging from 61 to 95%. The results of this study indicate that the treated coal samples are relative to high calorific value, fixed carbon, and low ash content. Coal and iron ore from Jamma revealed that high calorific value is 4929.24 and hematite content is 52.2, respectively. The result of this study revealed that a huge amount of limestone reservoir is detected in Borena Wereda, Amhara, Ethiopia.
{"title":"Geochemical Characterization of Sedimentary Materials (Limestone, Gypsum, Coal, and Iron Ore) along the Nile River Basin, South Wollo, Ethiopia","authors":"Sisay Awoke Endalew, Assamen Ayalew Ejigu, Desalegn Gezahegn Ketemu, Wudu Yimer Assen","doi":"10.1155/2024/8809894","DOIUrl":"https://doi.org/10.1155/2024/8809894","url":null,"abstract":"Sedimentary rocks are produced by the weathering of preexisting rocks and the subsequent transportation and deposition of the weathering products. Among the sedimentary rocks, especially limestone is a crucial raw material for cement production. The purpose of this study was to characterize the valuable industrial raw materials, limestone, gypsum, clay, coal, and iron ore, along with the Nile River basin. For sample collection, a random sampling method was applied. Different analytical methods were carried out for complete oxide analysis such as LiBO<sub>2</sub> fusion, HF attack, and gravimetric, calorimetric, and atomic absorption spectroscopy (AAS). The percentages of oxides detected in this study are in the range of acceptable values (high content of CaO ranging from 47.3 to 50.4% and less content of SiO<sub>2</sub> ranging from 8.72 to 11.24%) for good proposal as a potential raw material for cement production. The most dominant and wide-range coverage of limestone along with the Nile basin, particularly near Arsema Monastery, was found as matured limestone. The petrographic analysis of gypsum, sandstone, and clay samples indicated that all the samples taken from Wegidi revealed that the high percentage of gypsum ranges from 90 to 95%. Sandstone is dominantly preset in Kelala to Jamma road along with Beto River with high content of SiO<sub>2</sub> ranging from 61 to 95%. The results of this study indicate that the treated coal samples are relative to high calorific value, fixed carbon, and low ash content. Coal and iron ore from Jamma revealed that high calorific value is 4929.24 and hematite content is 52.2, respectively. The result of this study revealed that a huge amount of limestone reservoir is detected in Borena Wereda, Amhara, Ethiopia.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"1 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139495786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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