Methods and Applications in Fluorescence
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2018
·Vol. 6
·期 2
·025006
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IF 2.165
Jiajia Shan,Xue Wang,Hao Zhou,Shuqing Han,Dimas Firmanda Al Riza,Naoshi Kondo
Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models' performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.
研究领域:
分析化学
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食品科学
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化学计量学
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DOI
PubMed
高影响因子
Plant Methods
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2021
·Vol. 17
·期 1
·1-14
·
IF 4.993
Wang Maoyao,Li Xinru,Shen Yinjuan,Adnan Muhammad,Mao Le,Lu Pan,Hu Qian,Jiang Fuhong,Khan Muhammad Tahir,Deng Zuhu,Chen Baoshan,Huang Jiangfeng,Zhang Muqing
Background Sugarcane (Saccharum officinarum L.) is an economically important crop with stalks as the harvest organs. Improvement in stalk quality is deemed a promising strategy for enhancing sugarcane production. However, the lack of efficient approaches for systematic evaluation of sugarcane germplasm largely limits improvements in stalk quality. This study is designed to develop a systematic near-infrared spectroscopy (NIRS) assay for high-throughput phenotyping of sugarcane stalk quality, thereby providing a feasible solution for precise evaluation of sugarcane germplasm.Results A total of 628 sugarcane accessions harvested at different growth stages before and after maturity were employed to take a high-throughput assay to determine sugarcane stalk quality. Based on high-performance anion chromatography (HPAEC-PAD), large variations in sugarcane stalk quality were detected in terms of biomass composition and the corresponding fundamental ratios. Online and offline NIRS modeling strategies were applied for multiple purpose calibration with partial least square (PLS) regression analysis. Consequently, 25 equations were generated with excellent determination coefficients (R2) and ratio performance deviation (RPD) values. Notably, for some observations, RPD values as high as 6.3 were observed, which indicated their exceptional performance and predictive capability.Conclusion sThis study provides a feasible method for consistent and high-throughput assessment of stalk quality in terms of moisture, soluble sugar, insoluble residue and the corresponding fundamental ratios. The proposed method permits large-scale screening of optimal sugarcane germplasm for sugarcane stalk quality breeding and beyond.
研究领域:
农业
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植物科学
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光谱学
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生物技术
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DOI
PubMed
高影响因子
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
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2022
·
IF 4.831
Zongbao Sun,Haodong Pan,Min Zuo,Junkui Li,Liming Liang,Chi-Tang Ho,Xiaobo Zou
This study utilized equivalent umami concentrations (EUC) to characterize umami intensity in salmon with different freeze–thaw times. A rapid and non-destructive method was established to determine EUC values in salmon which is based on hyperspectral imaging (HSI) system combined with multiple characteristic variable screening methods. The established CARS-PLS model showed greater advantages in correlating the reference values of spectral data with EUC in salmon with Rc of 0.9012, Rp of 0.9009, RMSECV of 0.82, and RMSEP of 0.88. The model was employed pixel-wise to visualize the distribution of EUC with different freeze–thaw times, which demonstrated the reduction of EUC value with the increasing of freeze–thaw times. Therefore, this reseearch showed hyperspectral imaging (HSI) system combined with chemometrics possesses a substantial capability to predict and visualize the EUC of salmon, which would provide an intuitive understanding of salmon quality prediction and detection.
研究领域:
食品科学
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化学计量学
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成像技术
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DOI
PubMed
高影响因子
SENSORS AND ACTUATORS B-CHEMICAL
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2021
·
IF 7.46
Rui Liu,Hengye Chen,Xiuyun Bai,Yun Huang,Huiling Li,Wanjun Long,Wei Lan,Yuanbin She,Haiyan Fu
Sesame oil is a kind of vegetable oil, which is loved by people all over the world due to its unique aroma, edible and medicinal value. Driven by interests, counterfeit and shoddy sesame oil products often appear on the market. This study is based on the color change caused by the competitive coordination of Zn 2 + at the phase interface between four polyphenol dyes (Alizarin Red S, bromocatechol red, pyrogallol red and catechol violet) and volatile authenticity markers (VAM) in sesame oil. The DD-SIMCA model was constructed based on the RGB values of each sensing point after the reaction of real sesame oil and adulterated sesame oil with four polyphenol dyes. The results of the DD-SIMCA classification model show that the accuracy of sesame oil classification can reach 100%, and the result of the array sensor is much better than that of the single dye. Furthermore, the PLSR quantitative analysis model is used to verify that the RGB value obtained by the sensor is linearly related to the adulteration concentration. Therefore, this study established a visual array sensor for rapid authenticate of sesame oil adulteration based on the flavor compounds .
研究领域:
食品科学
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化学传感器
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分析化学
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机器学习
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DOI
高影响因子
Small
·
2018
·Vol. 14
·期 20
·1704433
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IF 9.598
Yizhi Zhang,Zhuyuan Wang,Lei Wu,Shenfei Zong,Binfeng Yun,Yiping Cui
Isolating and in situ profiling the heterogeneous molecular phenotype of circulating tumor cells are of great significance for clinical cancer diagnosis and personalized therapy. Herein, an on-chip strategy is proposed that combines size-based microfluidic cell isolation with multiple spectrally orthogonal surface-enhanced Raman spectroscopy (SERS) analysis for in situ profiling of cell membrane proteins and identification of cancer subpopulations. With the developed microfluidic chip, tumor cells are sieved from blood on the basis of size discrepancy. To enable multiplex phenotypic analysis, three kinds of spectrally orthogonal SERS aptamer nanovectors are designed, providing individual cells with composite spectral signatures in accordance with surface protein expression. Next, to statistically demultiplex the complex SERS signature and profile the cellular proteomic phenotype, a revised classic least square algorithm is employed to obtain the 3D phenotypic information at single-cell resolution. Combined with categorization algorithm partial least square discriminate analysis, cells from different human breast cancer subtypes can be reliably classified with high sensitivity and selectivity. The results demonstrate that this platform can identify cancer subtypes with the spectral information correlated to the clinically relevant surface receptors, which holds great potential for clinical cancer diagnosis and precision medicine.
研究领域:
生物医学工程
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癌症研究
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分析化学
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微流控技术
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DOI
PubMed
高影响因子
LUMINESCENCE
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2022
·Vol. 37
·期 9
·1414-1426
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IF 2.613
Xiaoyu Yang,Lulu Lei,Donghui Song,Yue Sun,Meng Yang,Zhen Sang,Jianan Zhou,Hui Huang,Yongxin Li
To realize the efficient differential sensing of phenolic pollutants in sewage, a novel sensing strategy was successfully developed based on a nanozyme (GMP-Cu) with polyphenol oxidase activity. Phenolic pollutants can be oxidized using GMP-Cu, and the oxidation products reacts subsequently with 4-aminoantipyrine to produce a quinone-imine compound. The absorption spectra of final quinone-imine products that resulted from different phenolic pollutants showed obvious differences, which were due to the interaction difference between GMP-Cu and phenolic pollutants, as well as the different molecular structures of the quinone-imine products from different phenolic pollutants. Based on the difference in the absorption spectra, a novel differential sensing strategy was developed. A genetic algorithm was used to select the characteristic wavelengths at different enzymatic reaction times. Hierarchical cluster analysis and PLS-DA algorithms were utilized for the discriminant sensing of seven representative phenolic pollutants, including hydroquinone, resorcinol, catechol, resorcinol, phenol, p -chlorophenol, and 2,4-dichlorophenol. A scientific wavelength selection algorithm and a recognition algorithm resulted in the successful identification of phenolic pollutants in sewage with a discriminant accuracy of 100%, and differentiation of the phenolic pollutants regardless of their concentration. These results indicated that a sensing strategy can be used as an effective tool for the efficient identification and differentiation of phenolic pollutants in sewage.
研究领域:
环境科学
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分析化学
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纳米技术
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DOI
PubMed
高影响因子
ANALYTICAL LETTERS
·
2020
·
IF 1.467
Jiajia Hong,Xiaotang Hao,Tiantian Liu,Weiting Liu,Meiyi Xie,Mei Wang,Qian Xu,Bingyi Yang
A sensitive method termed rapid synergistic cloud point extraction (RS-CPE) combined with partial least squares (PLS) was developed for the extraction and simultaneous determination of trace amounts of phenol and three detrimental chlorophenols (CPs) via a microplate assay (MPA). In this study, n-pentanol was used as a novel synergistic inducer and the linear nonionic surfactant Tergitol 15-S-7 was used as an extractant. The whole process of RS-CPE was accomplished in a few minutes without the need for the time-consuming water- or ice-bath steps used in traditional cloud point extraction. An automated and high-throughput assay using a 96-well plate allowed for the simultaneous processing of multiple samples with low sample volume requirements (approximately 200 µL). However, synchronized determination of several CPs using MPA method was problematic because of spectral interferences. Fortunately, a multivariate calibration method using PLS was applied to circumvent these limitations. Under the optimum conditions, the linear dynamic concentration ranges were from 0.5 to 15 µg/mL for 2-chlorophenol and 0.5 to 20 µg/mL for the other analytes. The detection limit range was from 0.275 to 0.419 µg/mL. The enrichment factor was up to 15.4 fold. The developed methodology was successfully applied to quantitative analysis of phenol and three CPs in water samples with recoveries from 90.0% to 109%.
研究领域:
分析化学
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环境科学
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产品关联
DOI
高影响因子
LWT-FOOD SCIENCE AND TECHNOLOGY
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2022
·
IF 6.056
Bingsong Ma,Jiacai Wang,Binxing Zhou,Zihao Wang,Youyi Huang,Cunqiang Ma,Xinghui Li
To explore the impact of harvest season in white tea, high-performance liquid chromatography (HPLC) and amino acid analyzer were developed for the determinations of 17 phenolic compounds, 3 purine alkaloids, 19 amino acids, γ-aminobutyric acid (GABA) and 4 main quality components in 18 Bai mudan sub-type of Xinyang white teas harvested in spring, summer and autumn seasons, respectively. Additionally, the in vitro antioxidant capacity was evaluated by 5 various assays. Principal component analysis (PCA), hierarchical cluster analysis (HCA) and partial least squares-discriminant analysis (PLS-DA) could completely classify these white teas by the harvest season, and indicated its profound impact on chemical composition in white tea. 14 Characteristic compounds (VIP ≥1.0), such as (−)-epigallocatechin (EGC), gallic acid, caffeine, l -theanine, conduced to identify the harvest season of white tea. Through comparison, the spring tea was observed to possess the highest amino acids, catechins contents and in vitro antioxidant capacity. (−)-Epicatechin (EC), EGC, (−)-epicatechin gallate (ECG) and (−)-epigallocatechin gallate (EGCG) were considered as the major antioxidants in white tea due to their highly significantly ( p < 0.01) positive correlations. Overall, the research results provided support for the identification of harvest season in white tea.
研究领域:
食品科学
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化学
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农业科学
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DOI
高影响因子
Processes
·
2026
·Vol. 14
·期 7
·1147
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IF 3.4
Yitao Lei,Jingong Zhang,Tao Zhang,Feng Zhang,Bolong Wang,Zhaoyu Zhang,Ruilong Suo
This study aims to evaluate the controlling factors of tight sandstone reservoir sensitivity in the third member of the Yanchang Formation, Xunyi–Yijun area, southern Ordos Basin. Based on core samples from 12 wells, we established a partial least squares regression (PLS) model through thin section observation, SEM, XRD, high-pressure mercury injection, and sensitivity flow experiments, to quantitatively analyze the relationship between reservoir sensitivity and its controlling factors. The results show that the study area reservoirs are dominated by feldspathic sandstone with moderate compaction, characterized by low porosity (4.4–17.8%, avg. 10.93%), low permeability (0.104–2.33 mD, avg. 0.82 mD), and heterogeneous distribution of clay minerals (mainly chlorite, illite, kaolinite, and illite/smectite mixed layer). The reservoirs generally show weak to moderately weak sensitivity. The PLS model reveals that reservoir sensitivity is controlled by the coupled effects of multiple factors, with no single absolute dominant factor for any sensitivity type. Porosity is the most influential variable for overall reservoir sensitivity, followed by feldspar, illite, and illite/smectite mixed layer, and porosity exerts the strongest control on most sensitivity types via VIP score analysis. This study provides a theoretical basis for reservoir damage prevention in the study area and a technical reference for quantitative sensitivity evaluation of similar tight sandstone reservoirs.
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DOI
高影响因子
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
·
2024
·
IF 4.3
Changfei Ma,Qun Zhang,Jing Liang,Shan Yang,Tianlong Zhang,Fangqi Ruan,Hongsheng Tang,Hua Li
Polycyclic aromatic hydrocarbons (PAHs) present in oily sludge generated by the petroleum and petrochemical industries have emerged as a prominent concern within the realm of environmental conservation. The precise determination of PAHs holds immense significance in both petroleum geochemistry and environmental protection. In this study, a combination of surface-enhanced Raman spectroscopy (SERS) and solid–liquid extraction was employed for the screening of PAHs in oily sludge. Methanol was utilized as the extraction solvent for PAHs, while nanosilver-silicon coupling substrates were employed for their detection. The SERS spectrum was acquired using a portable Raman spectrometer. The nano silver-silicon coupling substrate exhibits excellent uniformity, with relative standard deviations (RSDs) of Phenanthrene, Fluoranthrene, Fluorene and Naphthalene (Phe, Flt, Flu and Nap) being 2.8%, 1.08%, 1.41%, and 5.44% respectively. Moreover, the limits of detection (LODs) achieved remarkable values of 0.542 μg/g, 0.342 μg/g, 0.541 μg/g, and 5.132 μg/g. The quantitative analysis of PAHs in oily sludge was investigated using SERS technology combined with partial least squares (PLS). The optimal PLS calibration model was optimized by combining spectral preprocessing methods and using the SiPLS (Synergy interval partial least squares)-VIP (Variable Importance in Projection) hybrid variable selection strategy. The prediction performance of the D1st (First derivative)-WT (Wavelet transform)-SiPLS-VIP-PLS model was deemed satisfactory, as evidenced by high R 2 P values of 0.9851, 0.9917, and 0.9925 for Phe, Flt, and Flu respectively; additionally, the corresponding MREP values were found to be 0.0580, 0.0668, and 0.0669 respectively. However, for Nap analysis, the D1st-WT-PLS model proved to be a better calibration model with an R 2 P value of 0.9864 and an MREP (Mean relative error of prediction) value of 0.0713. In summary, SERS technology combined with PLS based on different spectral pretreatment methods and mixed variable selection strategies is a promising method for quantitative analysis of PAHs in oily sludge, which will provide new ideas and methods for the quantitative analysis of PAHs in oily sludge.
研究领域:
环境科学
·
分析化学
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产品关联
DOI
PubMed
高影响因子
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS
·
2020
·
IF 3.209
Lijuan Huang,Tongtong Li,Yingjun Zhang,Xiaohong Sun,Yongan Wang,Zhiyong Nie
The detection of psychoactive substances is an important branch of modern analytical chemistry and has many legally and socially relevant implications. The use of a surface plasmon resonance (SPR)-based gene–nanoparticle system has emerged as a promising technique for the rapid and ultrasensitive detection of molecular species such as drugs of abuse in biofluids. However, the development of a viable screening tool for the detection of multiple classes of drugs in complex media is a considerable challenge because the existing techniques lack affinity toward certain species due to matrix interference. Our aim was to develop a simple optical sensor array for the classification of nine narcotic drugs in aqueous solution and human urine. The UV–vis spectra of DNA–gold nanoparticles in the presence of nine narcotic drugs (pentobarbital sodium, caffeine, morphine, remifentanil, fentanyl, ketamine, etomidate, carfentanil, and sulfentanyl) were distinctly different. Furthermore, the narcotic drugs present in aqueous solution and in human urine were classified correctly through partial least squares discriminant analysis (PLS-DA). Combination with a multi-sensor unit further improved the prediction accuracy of the PLS-DA models. The proposed method has potential for on-site drug detection and drug abuse screening.
研究领域:
分析化学
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纳米技术
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化学计量学
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法医学
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产品关联
DOI
PubMed
高影响因子
BIOSENSORS & BIOELECTRONICS
·
2023
·
IF 12.6
Dechan Lu,Yanping Chen,Longfeng Ke,Weilin Wu,Liwen Yuan,Shangyuan Feng,Zufang Huang,Yudong Lu,Jing Wang
DNA methylation plays a critical role in the development of human tumors. However, routine characterization of DNA methylation can be time-consuming and labor-intensive. We herein describe a sensitive, simple surface-enhanced Raman spectroscopy (SERS) approach for identifying the DNA methylation pattern in early-stage lung cancer (LC) patients. By comparing SERS spectra of methylated DNA bases or sequences with their counterparts, we identified a reliable spectral marker of cytosine methylation. To move toward clinical applications, we applied our SERS strategy to detect the methylation patterns of genomic DNA (gDNA) extracted from cell line models as well as formalin-fixed paraffin-embedded tissues of early-stage LC and benign lung diseases (BLD) patients. In a clinical cohort of 106 individuals, our results showed distinct methylation patterns in gDNA between early-stage LC (n = 65) and BLD patients (n = 41), suggesting cancer-induced DNA methylation alterations. Combined with partial least square discriminant analysis, early-stage LC and BLD patients were differentiated with an area under the curve (AUC) value of 0.85. We believe that the SERS profiling of DNA methylation alterations, together with machine learning could potentially offer a promising new route toward the early detection of LC.
研究领域:
癌症生物学
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分子生物学
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生物医学工程
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生物信息学
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产品关联
DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）