Hyperspectral identification of oil adulteration using machine learning techniques

Hyperspectral identification of oil adulteration using machine learning techniques

Food adulteration is a global concern, drawing attention from safety authorities due to its potential health risks. Detecting and categorizing oil adulteration is crucial for consumer safety and food industry integrity. This research explores hyperspectral imaging (HSI) analysis to identify substand...

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Bibliographic Details
Main Authors: Muhammad Aqeel, Ahmad Sohaib, Muhammad Iqbal, Hafeez Ur Rehman, Furqan Rustam
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Current Research in Food Science
Subjects:
Adulteration
Edible oil
Food quality control
Hyperspectral imaging
Artificial intelligence
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2665927124000996

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http://www.sciencedirect.com/science/article/pii/S2665927124000996

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