JOURNAL OF RAMAN SPECTROSCOPY
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2022
·Vol. 54
·期 2
·191-200
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IF 2.727
Yuhao Xie,Siwei Yang,Shenghua Zhou,Jiazhen Liu,Shuai Zhao,Shangzhong Jin,Qiang Chen,Pei Liang
Raman spectroscopy is widely used in the identification of substances. Raman spectra contain molecular information from various components and interference from noise and instruments. Therefore, using Raman spectroscopy to identify components is still challenging, especially for substances with high similarity. In this study, a class of highly similar products (methanol and ethanol) and a multicomponent mixture of propanol and water were tested using a portable Raman spectrometer. They are divided into 11 categories according to the volume fraction ratio. A total of 5,060 groups of Raman spectrum data were obtained, constituting the data set of this study. The deep neural network structure adopted in this study is based on ResNet architecture, on which the SE module in the attention mechanism is added, which increases the weight of some spectral features and achieves significant performance improvement. Finally, SE-ResNet achieves a recall of 0.95, a precision rate of 0.95, a Micro-F1 of 0.95, and an accuracy rate of 99.20%.
研究领域:
分析化学
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人工智能
·
光谱学
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产品关联
DOI
高影响因子
Microorganisms
·
2022
·Vol. 10
·期 3
·575
·
IF 4.926
Ge Gao,Yan Zhang,Shaofang Niu,Yu Chen,Shaojing Wang,Nusratgul Anwar,Shuai Chen,Guoqiang Li,Ting Ma
Precise classification of bacteria facilitates prediction of their ecological niche. The genusEnterobacterincludes pathogens of plants and animals but also beneficial bacteria that may require reclassification. Here, we propose reclassification ofEnterobacterFY-07 (FY-07), a strain that has many plant-growth-promoting traits and produces bacterial cellulose (BC), to theKosakoniagenera. To re-examine the taxonomic position of FY-07, a polyphasic approach including 16S rRNA gene sequence analysis, ATP synthase β subunit (atpD) gene sequence analysis, DNA gyrase (gyrB) gene sequence analysis, initiation translation factor 2 (infB) gene sequence analysis, RNA polymerase β subunit (rpoB) gene sequence analysis, determination of DNA G + C content, average nucleotide identity based on BLAST, in silico DNA–DNA hybridization and analysis of phenotypic features was applied. This polyphasic analysis suggested thatEnterobactersp. FY-07 should be reclassified asKosakonia oryzendophyticaFY-07. In addition, the potential of FY-07 to promote plant growth was also investigated by detecting related traits and the colonization of FY-07 in rice roots.Keywords:Enterobacter;Kosakonia;reclassification;FY-07;promote plant growth
研究领域:
微生物学
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植物科学
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DOI
PubMed
高影响因子
BIOCHEMICAL SYSTEMATICS AND ECOLOGY
·
2022
·
IF 1.462
Xue-Feng Xu,De-Cai Dai,Hao Yan,Yu Zhang
The phytochemical investigation of the stems of Dendrobium officinale Kimura et Migo led to the isolation of a new chromone , chromcinale ( 1 ) and a new phenolic glycoside , leonuriside C ( 5 ), together with three known biogenetically related phenanthrenes ( 2 – 4 ), three known biogenetically related phenolic glycosides ( 6 – 8 ) and four known biogenetically related phenylpropanoids ( 9 – 12 ). The structures of these compounds were elucidated using comprehensive spectroscopic methods . Compounds 1–3 , 5–12 were isolated from the D. officinale for the first time. The chemotaxonomic significance of the isolates was also discussed.
研究领域:
植物化学
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药用植物学
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产品关联
DOI
高影响因子
Journal of Oceanology and Limnology
·
2023
·Vol. 41
·期 5
·1965-1977
·
IF 1.6
Liu Yan,Kociolek John Patrick,Kulikovskiy Maxim,Glushchenko Anton,Yu Pan,Wang Quanxi,Lu Xinxin,Fan Yawen
An interesting group of cymbelloid diatoms was collected from lakes in Yunnan Province, China, and observations on their valve morphology made using light and scanning electron microscopy. These cymbelloid species all have apical pore fields, slit-like areolae, and areolar occlusions, and they all lack of stigmata. In this paper we propose the new genus Qinia gen. nov. for these taxa and describe them as new: Q. lashii sp. nov., Q. aequalis sp. nov., and Q. daliensis sp. nov. The genus Qinia gen. nov. has lanceolate valves asymmetrical about their apical axes, raphe located in the middle of valve, distal raphe ends bent to the dorsal margin that bisects the apical pore fields (APFs), no stigmata, areolae with slit-like external openings and projections occluding the areolar openings internally. This genus resembles the genus Cymbella in the presence of APFs, but differs from Cymbella by a lack of stigmata, and by having external distal raphe ends that bisect the apical pore fields. Like Reimeria , the external distal raphe ends bisect the lobes of the APF, but Qinia species differ from Reimeria in that they have no stigmata and the distal raphe ends are deflected dorsally, not ventrally. Comparisons were made between Qinia and other cymbelloid genera whose members possess apical pore fields. Features that distinguish each species of the new genus are also discussed.
研究领域:
植物分类学
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淡水生态学
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藻类生物学
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形态学
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系统发育研究
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DOI
高影响因子
Fermentation-Basel
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2023
·Vol. 9
·期 6
·519
·
IF 3.7
Shuyue Fan,Yu Zhang,Yunkui Li
The classification of color is important in the management and evaluation of red wine color. Nevertheless, current reports have not given a sound solution. A novel scheme for the quantitative classification of red wine color from the perspective of micro and macro levels was proposed in this work. The overall color performance of 119 representative red wine samples was visualized and classified into 125 micro-classifications according to the partition of the chromaticity and lightness of the wine color. Considering the evolution of red wine color, quantitative macro-classification of the color of the wine samples was explored, and six macro-classifications were obtained. These few classifications determine the extent of aging and aging potential of colors between different red wines well. The performance of this approach was further verified by another set of 56 red wine samples. This efficient and easy-to-implement approach is expected to be helpful in the digital and visual color management, control, evaluation, comparison, and prediction of red wines.Keywords:wine color classification;wine color evolution;CIELAB;visual representation
研究领域:
食品科学
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化学计量学
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DOI
高影响因子
TALANTA
·
2023
·
IF 6.1
Jingwang Qin,Xiangdong Tian,Siying Liu,Zhengxia Yang,Dawei Shi,Sihong Xu,Yun Zhang
The spread of COVID-19 over the past three years is largely due to the continuous mutation of the virus, which has significantly impeded global efforts to prevent and control this epidemic. Specifically, mutations in the amino acid sequence of the surface spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have directly impacted its biological functions, leading to enhanced transmission and triggering an immune escape effect. Therefore, prompt identification of these mutations is crucial for formulating targeted treatment plans and implementing precise prevention and control measures. In this study, the label-free surface-enhanced Raman scattering (SERS) technology combined with machine learning (ML) algorithms provide a potential solution for accurate identification of SARS-CoV-2 variants. We establish a SERS spectral database of SARS-CoV-2 variants and demonstrate that a diagnostic classifier using a logistic regression (LR) algorithm can provide accurate results within 10 min. Our classifier achieves 100% accuracy for Beta (B.1.351/501Y.V2), Delta (B.1.617), Wuhan (COVID-19) and Omicron (BA.1) variants. In addition, our method achieves 100% accuracy in blind tests of positive and negative human nasal swabs based on the LR model. This method enables detection and classification of variants in complex biological samples. Therefore, ML-based SERS technology is expected to accurately discriminate various SARS-CoV-2 variants and may be used for rapid diagnosis and therapeutic decision-making.
研究领域:
病毒学
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生物医学工程
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机器学习
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分析化学
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公共卫生
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产品关联
DOI
PubMed
高影响因子
Analytical Methods
·
2025
·
IF 2.6
De-Huan Yang,Li-Lin Lin,Zhang-Feng Tang,Zengping Chen,Yao Chen,Tong Wang,Ruqin Yu
Lu'an Gua Pian tea (LAGP) is a traditional historical tea and one of the top ten famous teas in China. The price of LAGP from the same place of origin with different harvest time varies greatly in the market, among which the LAGP before the Qingming Festival (between April 4th and 6th every year) is regarded as a precious product. To accurately determine the harvest time of LAGP, especially around Qingming, HPLC-DAD combined with three different data analysis strategies (including targeted components analysis, non-targeted components analysis, and non-targeted fingerprint analysis) was evaluated and compared. Four machine learning algorithms are used to build the corresponding classification models, among which principal component analysis coupled with linear discriminant analysis (PCA-LDA), partial least squares discriminant analysis (PLS-DA) and K-nearest neighbors (K-NN) achieved more than 95% classification accuracy. In addition, the non-targeted component analysis can classify LAGP picking time to a much smaller extent with an accuracy of 100% for PLS-DA. The advantages and disadvantages of three data analysis strategies were compared. Regardless of the data analysis strategy used, the final classification accuracy was satisfactory. The corresponding data analysis strategy can be selected according to the specific experimental purpose. This work provides a variety of alternative solutions based on HPLC-DAD for identifying the picking time of Lu'an Gua Pian.
研究领域:
食品科学
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分析化学
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DOI
PubMed
高影响因子
LWT-FOOD SCIENCE AND TECHNOLOGY
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2022
·
IF 6.056
Xiaoqing Ye,Yan Liu,Changbo Peng,Xi Guan,Yi Liu,Zhenming Che,Hongbin Lin,Xu Min,Qi Zhu,Wenwu Ding
In this study, Pixian Douban (PXDB) was produced in a closed system of multi-scale temperature and flow fields constructed with the materials of pseudoplastic fluid in a gradient steady-state temperature field. The flavors and microorganisms of PXDB in the MTFF were compared with those in the traditional process with original materials (TPOM) and the traditional process with materials of pseudoplastic fluid (TPPF). The contents of organic acids, free amino acids and flavors in the MTFF were higher than those in the TPPF and TPOM. Chitinophagaceae_Unclassified and Bradyrhizobium_Unclassified were the predominant bacteria while Phyllachora sp . UB03986 and Rhizopus oryzae were identified as the core fungi at the species levels in the processes. The correlation analysis showed that 26 bacterial and 6 fungal were significantly correlated with the flavors. The results indicated that the closed system of MTFF could improve the product quality and was helpful to realize the controllable PXDB production.
研究领域:
食品科学
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微生物学
·
发酵技术
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产品关联
DOI
高影响因子
Analytical Methods
·
2024
·Vol. 16
·期 34
·5812-5819
·
IF 2.7
Xizhe Li,Fan Yang,Haojie Li,Zhi Hu,Weiting Yu,Yuchen Zhang,Jie Gao
The early detection of bacterial species plays a crucial role in patient prognosis and the development of effective therapeutic regimens. This study introduces an accessible and promising colorimetric sensor array designed to classify gram-positive (G+) and gram-negative (G−) bacterial species. The classification relies on 6 chemical ligands with dimethylamino/amino groups as sensing elements and silver nanotriangles as colorimetric probes. Using these specific sensor arrays, we successfully differentiated G− and G+ bacterial species and discriminated individual bacterial strains, and the sensors exhibited remarkable reproducibility and high sensitivity. Moreover, the sensor array can identify bacterial mixtures and bacteria at varying concentrations, underscoring its versatility. In summary, this sensor array offers an effective tool for bacterial analysis with promising applications in the field of biomedical diagnostics.
研究领域:
生物医学
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化学传感
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微生物学
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产品关联
DOI
PubMed
高影响因子
JOURNAL OF ANALYTICAL CHEMISTRY
·
2023
·Vol. 78
·期 11
·1502-1510
·
IF 1.1
Wang Ce,Wang Zhaoliang,Lu Yifei,Hao Tingting,Hu Yufang,Wang Sui,Guo Zhiyong
Abstract In this work, an image classification based on deep learning for quantitative field determination of aluminum ions (Al 3+ ) was developed. Carbon quantum dots with yellow fluorescence were synthesized by a one-pot hydrothermal method which could specifically recognize Al 3+ and produce enhanced green fluorescence. Using the convolutional neural network model in deep learning, an image classification was constructed to classify Al 3+ samples at different concentrations. Then, a fitting method for classification information was proposed for the first time which could convert discontinuous, semi-quantitative concentration classification information into continuous, quantitative, and accurate concentration information. Recoveries of 92.0–110.3% in the concentration range of 0.3–320 μM were obtained with a lower limit of detection of 0.3 μM, exhibiting excellent accuracy and sensitivity. It could be completed in 2 min simply without requiring large equipment. Thus, the deep learning-enabled image classification paves a new way for the determination of metal ions.
研究领域:
化学
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环境科学
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计算机科学
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DOI
高影响因子
INDUSTRIAL CROPS AND PRODUCTS
·
2021
·
IF 5.645
Caihong Li,Yan Zhao,Wenjing Li,Rongrong Xing,Jing Lu,Rongxia Liu
Euodiae Fructus (EF, the fruit of Tetradium ruticarpum ) belongs to the family Rutaceae which has a complex genetic background, making classification a challenge. In order to classify the three closely related cultivars (small flower EF, medium flower EF, and big flower EF) and simplify the identification procedure in the future, an approach integrating ultra-high performance liquid chromatography-ultraviolet spectrum-hybrid quadrupole-Orbitrap high resolution mass spectrometry (UHPLC-UV-Q-Orbitrap HRMS) with machine learning algorithms was developed. Orthogonal partial least squares-discriminant analysis (OPLS-DA) and random forest (RF) were used to assort the processed EF products and select the chemical markers to differentiate among the three EF cultivars, respectively. Then the thresholds of classification were determined using the eXtreme Gradient Boosting (XGboost) model based on the quantitative data of chemical markers by the UHPLC-Q-Orbitrap HRMS. The results demonstrated that the approach successfully discriminated among three closely related cultivars of EF, and five chemical markers (neochlorogenic acid, (+)-catechin, chlorogenic acid, dehydroevodiamine, and limonin) were selected. Thresholds were obtained to classify the three cultivars. If the content of neochlorogenic acid was greater than 7.52 mg/g, the sample belonged to small flower EF, otherwise, it belonged to medium flower EF or big flower EF. Furthermore, if the content of dehydroevodiamine was greater than 3.84 mg/g, the sample was medium flower EF, otherwise, it was big flower EF. In general, this research provides a novel strategy for the discrimination of Euodiae Fructus cultivars to avoid misapplication and possible side effects.
研究领域:
药学
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分析化学
·
植物学
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产品关联
DOI
高影响因子
Agriculture-Basel
·
2024
·Vol. 14
·期 10
·1763
·
IF 3.3
Yixin Qiu,Yong Tan,Yingying Zhou,Zhipeng Li,Zhuang Miao,Changming Li,Xitian Mei,Chunyu Liu,Xing Teng
The origin of agricultural products significantly influences their quality and safety. Fluorescence spectroscopy was used to analyse Japonica rice 830, grown in different areas of Jilin Province, by examining rice seed, brown rice, and rice flour from 12 origins. Fluorescence spectra were pre-processed through normalisation and smoothing to remove noise. These processed spectra were input into decision trees, support vector machines (SVMs), K-nearest neighbour (KNN), and neural network models for classification. The analysis revealed that the combined four models achieved an average classification accuracy of 98.05% with a computation time of 180 s, while the reduced-scale models improved accuracy to 98.36% and reduced computation time to 11.25 s. Additionally, prediction models using standard rice starch content values across different states achieved R² values over 0.8. This method provides a rapid, precise approach for assessing rice quality and origin, demonstrating significant potential for application in rice analysis.
研究领域:
食品科学
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光谱学
·
农业科学
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产品关联
DOI
高影响因子
危险品化学品经营许可证（带存储）