scholarly journals Chemical images of marine bio-active compounds by surface enhanced Raman spectroscopy and transposed orthogonal partial least squares (T-OPLS)

2012 ◽  
Vol 737 ◽  
pp. 37-44 ◽  
Author(s):  
Aamer Abbas ◽  
Mats Josefson ◽  
Göran M. Nylund ◽  
Henrik Pavia ◽  
Katarina Abrahamsson
Keyword(s):  
Raman Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Surface Enhanced Raman Spectroscopy ◽  
Active Compounds ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

scholarly journals Quantitative Determination of Thiabendazole in Soil Extracts by Surface-Enhanced Raman Spectroscopy

Molecules ◽  
2018 ◽  
Vol 23 (8) ◽  
pp. 1949 ◽  
Author(s):  
Pengcheng Nie ◽  
Tao Dong ◽  
Shupei Xiao ◽  
Lei Lin ◽  
Yong He ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Pesticide Residues ◽  
Surface Enhanced Raman Spectroscopy ◽  
Red Soil ◽  
Soil Extracts ◽  
Relative Standard ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

Thiabendazole (TBZ) is widely used in sclerotium blight, downy mildew as well as root rot disease prevention and treatment in plant. The indiscriminate use of TBZ causes the excess pesticide residues in soil, which leads to soil hardening and environmental pollution. Therefore, it is important to accurately monitor whether the TBZ residue in soil exceeds the standard. For this study, density functional theory (DFT) was used to theoretically analyze the molecular structure of TBZ, gold nanoparticles (AuNPs) were used to enhance the detection signal of surface-enhanced Raman spectroscopy (SERS) and the TBZ residue in red soil extracts was quantitatively determined by SERS. As a result, the theoretical Raman peaks of TBZ calculated by DFT were basically consistent with the measured results. Moreover, 784, 1008, 1270, 1328, 1406 and 1576 cm−1 could be determined as the TBZ characteristic peaks in soil and the limits of detection (LOD) could reach 0.1 mg/L. Also, there was a good linear correlation between the intensity of Raman peaks and TBZ concentration in soil (784 cm−1: y = 672.26x + 5748.4, R2 = 0.9948; 1008 cm−1: y = 1155.4x + 8740.2, R2 = 0.9938) and the limit of quantification (LOQ) of these two linear models can reach 1 mg/L. The relative standard deviation (RSD) ranged from 1.36% to 8.02% and the recovery was ranging from 95.90% to 116.65%. In addition, the 300–1700 cm−1 SERS of TBZ were analyzed by the partial least squares (PLS) and backward interval partial least squares (biPLS). Also, the prediction accuracy of TBZ in soil (Rp2 = 0.9769, RMSEP = 0.556 mg/L, RPD = 5.97) was the highest when the original spectra were pretreated by standard normal variation (SNV) and then modeled by PLS. In summary, the TBZ in red soil extracts could be quantitatively determined by SERS based on AuNPs, which was beneficial to provide a new, rapid and accurate scheme for the detection of pesticide residues in soil.

Detection and classification of fentanyl and its precursors by surface-enhanced Raman spectroscopy

The Analyst ◽  
2020 ◽  
Vol 145 (9) ◽  
pp. 3440-3446 ◽  
Author(s):  
Rustin Mirsafavi ◽  
Martin Moskovits ◽  
Carl Meinhart
Keyword(s):  
Raman Spectroscopy ◽  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Surface Enhanced Raman Spectroscopy ◽  
Analytical Technique ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

An analytical technique combining partial least squares-discriminant analysis, surface-enhanced Raman spectroscopy (SERS), and microfluidics for the detection and classification of fentanyl and its chemical precursors.

Label-Free Detection of Micro-RNA Hybridization Using Surface-Enhanced Raman Spectroscopy and Least-Squares Analysis

2012 ◽  
Vol 134 (31) ◽  
pp. 12889-12892 ◽  
Author(s):  
Justin L. Abell ◽  
Jeonifer M. Garren ◽  
Jeremy D. Driskell ◽  
Ralph A. Tripp ◽  
Yiping Zhao
Keyword(s):  
Raman Spectroscopy ◽  
Least Squares ◽  
Surface Enhanced Raman Spectroscopy ◽  
Micro Rna ◽  
Label Free ◽  
Label Free Detection ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

Bacterial detection and differentiation via direct volatile organic compound sensing with surface enhanced Raman spectroscopy

2017 ◽  
Author(s):  
Caitlin S. DeJong ◽  
David I. Wang ◽  
Aleksandr Polyakov ◽  
Anita Rogacs ◽  
Steven J. Simske ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Bacterial Infections ◽  
Direct Detection ◽  
Point Of Care ◽  
Surface Enhanced Raman Spectroscopy ◽  
E Coli ◽  
Recent Emergence ◽  
Surface Enhanced ◽  
Volatile Organic ◽  
Surface Enhanced Raman

Through the direct detection of bacterial volatile organic compounds (VOCs), via surface enhanced Raman spectroscopy (SERS), we report here a reconfigurable assay for the identification and monitoring of bacteria. We demonstrate differentiation between highly clinically relevant organisms: <i>Escherichia coli</i>, <i>Enterobacter cloacae</i>, and <i>Serratia marcescens</i>. This is the first differentiation of bacteria via SERS of bacterial VOC signatures. The assay also detected as few as 10 CFU/ml of <i>E. coli</i> in under 12 hrs, and detected <i>E. coli</i> from whole human blood and human urine in 16 hrs at clinically relevant concentrations of 10<sup>3</sup> CFU/ml and 10<sup>4</sup> CFU/ml, respectively. In addition, the recent emergence of portable Raman spectrometers uniquely allows SERS to bring VOC detection to point-of-care settings for diagnosing bacterial infections.

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