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Camellia oil grading adulteration detection using characteristic volatile components GC-MS fingerprints combined with chemometrics
Research article (Food Control, 2024) · cited 10× · AI/ML
Camellia oil grading adulteration detection using characteristic volatile components GC-MS fingerprints combined with chemometrics
Summary
Camellia oil grading adulteration detection using characteristic volatile components GC-MS fingerprints combined with chemometrics is a scholarly article[1].
Key Facts
Camellia oil grading adulteration detection using characteristic volatile components GC-MS fingerprints combined with chemometrics's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Camellia oil grading adulteration detection using characteristic volatile components GC-MS fingerprints combined with chemometrics. Retrieved May 24, 2026, from https://4ort.xyz/entity/camellia-oil-grading-adulteration-detection-using-characteristic-volatile-components-gc-ms-fingerprints-combined-with-ch