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References from Multi-attribute spectral imaging with a wavelength-aware band-gated vision transformer for camellia oil adulteration detection. Local targets link to admitted publications; unresolved targets remain external evidence.
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Identifying camellia oil adulteration with selected vegetable oils by characteristic near-infrared spectral regions
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Detection of camellia oil adulteration based on near-infrared spectroscopy and smartphone combined with deep learning and multimodal fusion
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Adulteration detection of corn oil, rapeseed oil and sunflower oil in camellia oil by in situ diffuse reflectance near-infrared spectroscopy and chemometrics
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Application of visible/infrared spectroscopy and hyperspectral imaging with machine learning techniques for identifying food varieties and geographical origins
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Rapid classification and quantification of camellia oil blended with rapeseed oil using FTIR-ATR spectroscopy
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Recent methods in detection of olive oil adulteration: state-of-the-art
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Using three-dimensional fluorescence spectroscopy and machine learning for rapid detection of adulteration in camellia oil
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NI-Raman spectroscopy combined with BP-AdaBoost neural network for adulteration detection of soybean oil in camellia oil
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Qualitative and quantitative detection of camellia oil adulteration using electronic nose based on wavelet decomposition humidity correction
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Authentication of pure camellia oil by using near infrared spectroscopy and pattern recognition techniques
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Rapid and low-cost quantification of adulteration content in camellia oil utilizing UV-Vis-NIR spectroscopy combined with feature selection methods
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Camellia oil grading adulteration detection using characteristic volatile components GC-MS fingerprints combined with chemometrics
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Camellia oil authentication: a comparative analysis and recent analytical techniques developed for its assessment. a review
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Camellia oil adulteration detection using fatty acid ratios and tocopherol compositions with chemometrics
10.1016/j.foodcont.2021.108565 · 2022 · External reference
Rapid identification of multiplex camellia oil adulteration based on lipidomic fingerprint using laser assisted rapid evaporative ionization mass spectrometry and data fusion combined with machine learning
10.1016/j.lwt.2025.118078 · 2025 · External reference
Reflectance spectroscopy with multivariate methods for non-destructive discrimination of edible oil adulteration
10.3390/bios11120492 · 2021 · External reference
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2021 · External reference
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Adulteration detection of multi-species vegetable oils in camellia oil using Raman spectroscopy: comparison of chemometrics and deep learning methods
10.1016/j.foodchem.2024.141314 · 2025 · External reference
Adulteration detection of multi-species vegetable oils in camellia oil using sicrit-hrms and machine learning methods
10.3390/foods15030434 · 2026 · External reference
Quantitative analysis of camellia oil binary adulteration using near infrared spectroscopy combined with chemometrics
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Rapid quantitative authentication and analysis of camellia oil adulterated with edible oils by electronic nose and ftir spectroscopy
10.1016/j.crfs.2024.100732 · 2024 · External reference
Identification of camellia oil adulteration by using near infrared spectroscopy combined with two dimensional correlation spectroscopy analysis
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2015 · External reference
PLS-regression: a basic tool of chemometrics
10.1016/s0169-7439(01)00155-1 · 2001 · External reference
A fast and highly efficient strategy for detection of camellia oil adulteration using machine learning assisted SERS
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Identification and quantitation of multiplex camellia oil adulteration based on 11 characteristic lipids using UPLC-Q-Orbitrap-MS
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Identification and detection of adulterated Camellia oleifera abel. oils by near infrared transmittance spectroscopy
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“A transformer-based framework for multivariate time series representation learning,”
10.1145/3447548.3467401 · 2021 · External reference
Composition, bioactive substances, extraction technologies and the influences on characteristics of Camellia oleifera oil: a review
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Quantitative analysis of multi-component adulteration in camellia oil by near-infrared spectroscopy combined with long short-term memory neural networks algorithm
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Systematic review of camellia oil: from preparation, quality control, bioactive substances, authenticity identification to comprehensive application
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Label-free detection of trace level zearalenone in corn oil by surface-enhanced Raman spectroscopy coupled with deep learning models
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