Revealing the adulteration of sesame oil products by portable Raman spectrometer and 1D CNN vector regression: A comparative study with chemometrics and colorimetry
- 14 October 2023
- journal article
- research article
- Published by Elsevier in Food Chemistry
- Vol. 436, 137694
Abstract
No abstract availableKeywords
This publication has 40 references indexed in Scilit:
- Safety analysis of edible oil products via Raman spectroscopyTalanta, 2019
- Fast quantitative detection of sesame oil adulteration by near-infrared spectroscopy and chemometric modelsVibrational Spectroscopy, 2018
- Preliminary identification of unicellular algal genus by using combined confocal resonance Raman spectroscopy with PCA and DPLS analysisSpectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2018
- Convolutional neural networks for vibrational spectroscopic data analysisAnalytica Chimica Acta, 2017
- Spectroscopic and Chemometric Analysis of Binary and Ternary Edible Oil Mixtures: Qualitative and Quantitative StudyAnalytical Chemistry, 2016
- Detection and quantification of adulteration of sesame oils with vegetable oils using gas chromatography and multivariate data analysisFood Chemistry, 2015
- Deep learningNature, 2015
- Classification of edible oils using 532 nm laser-induced fluorescence combined with support vector machineAnalytical Methods, 2013
- Baseline correction using adaptive iteratively reweighted penalized least squaresThe Analyst, 2010
- Application of a new, simple and economic colorimetric method for the determination of non-esterified fatty acids in vegetable oilsFood Chemistry, 1991