The Journal of Light Scattering, Volume. 37, Issue 2, 205(2025)
Quantitative Analysis of Overnight Waste Oil Adulterated Sunflower Seed Oil Based on Portable Raman Spectroscopy Assisted by One-Dimensional Convolutional Neural Network Algorithm
[13] [13] Ramos M P, Ruisnchez I. Noise and background removal in Raman spectra of ancient pigments using wavelet transform[J]. Journal of Raman Spectroscopy, 2005, 36(9): 848-856.
[14] [14] Tar T H M, Jordi C, Putthiporn K, et al. PLS-regression-model-assisted raman spectroscopy for vegetable oil classification and non-destructive analysis of alpha-tocopherol contents of vegetable oils[J]. Journal of Food Composition and Analysis, 2021, 103: 104119.
[15] [15] Liu H, Chen Y, Shi C, et al. FT-IR and Raman spectroscopy data fusion with chemometrics for simultaneous determination of chemical quality indices of edible oils during thermal oxidation[J]. LWT, 2020, 119: 108906.
[16] [16] Iago H B, Layla S P, Mrcia H C N, et al. Use of portable Raman spectroscopy in the quality control of extra virgin olive oil and adulterated compound oils[J]. Vibrational Spectroscopy, 2021, 116: 103299.
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LU Mingxing, WEI Min, ZHOU Fuxia, HE Chunhua. Quantitative Analysis of Overnight Waste Oil Adulterated Sunflower Seed Oil Based on Portable Raman Spectroscopy Assisted by One-Dimensional Convolutional Neural Network Algorithm[J]. The Journal of Light Scattering, 2025, 37(2): 205
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Received: Jul. 4, 2024
Accepted: Jul. 31, 2025
Published Online: Jul. 31, 2025
The Author Email: LU Mingxing (lumingxing1981@126.com)