Discrimination of milk species using Raman spectroscopy coupled with partial least squares discriminant analysis in raw and pasteurized milk

2020 ◽  
Vol 100 (13) ◽  
pp. 4756-4765 ◽  
Author(s):  
Nazife N Yazgan ◽  
Huseyin E Genis ◽  
Tugba Bulat ◽  
Ali Topcu ◽  
Sahin Durna ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Pasteurized Milk

Discrimination of Human and Nonhuman Blood by Raman Spectroscopy and Partial Least Squares Discriminant Analysis

2016 ◽  
Vol 50 (2) ◽  
pp. 379-388 ◽  
Author(s):  
Pengli Bai ◽  
Jun Wang ◽  
Huancai Yin ◽  
Yubing Tian ◽  
Wenming Yao ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares

scholarly journals Preprocessing Tools Applied to Improve the Assessment of Aldrin Effects on Prostate Cancer Cells Using Raman Spectroscopy

2017 ◽  
Vol 72 (3) ◽  
pp. 489-500 ◽  
Author(s):  
Víctor Olmos ◽  
Carmen Bedia ◽  
Romà Tauler ◽  
Anna de Juan
Keyword(s):  
Prostate Cancer ◽  
Raman Spectroscopy ◽  
Discriminant Analysis ◽  
Least Squares ◽  
Cancer Cells ◽  
Partial Least Squares ◽  
Cancer Cell Line ◽  
Prostate Cancer Cell Line ◽  
Environmental Response ◽  
Prostate Cancer Cells

The study of pollutant effects on living organisms provides information about the possible biological and environmental response to a contaminant. Progression of prostate cancer may be related to exposure to pesticides or other chemical substances. In this work, the effect of the pesticide aldrin on human prostate cancer cells (DU145) is studied using Raman spectroscopy and chemometric techniques. Prostate cancer cell line DU145 has been exposed acutely the pesticide aldrin. Individual Raman spectra coming from control and treated cell populations have been acquired. Partial least squares discriminant analysis (PLSDA) has been used to assess differences among treated and control samples and to identify spectral biomarkers associated with pollutant stress. Some preprocessing methodologies have been tested in order to improve the capability of discrimination between fingerprints. Partial least squares discriminant analysis results suggest that the best normalization–scaling preprocessing combination is provided by Euclidean normalization (EN)-SIMPLISMA-based scaling (SBS). SIMPLISMA-based scaling has been proposed as a scaling method focused on the classification objective, which enhances variables with high relative variation among samples. The most relevant spectral variables related to aldrin effect on DU145 seem to be mainly related to lipids, proteins, and variations in nucleic acids.

Raman Spectroscopy with Self-Organising Feature Maps and Partial Least Squares Discriminant Analysis for Discrimination and Source Correspondence of Red Gel Ink Pens

2022 ◽  
pp. 107170
Author(s):  
Muhammad Naeim Mohamad Asri ◽  
Rajesh Verma ◽  
Naji Arafat Mahat ◽  
Nor Azman Mohd Nor ◽  
Wan Nur Syuhaila Mat Desa ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Feature Maps

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.

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