Optimizing DD-SIMCA modeling for accurate classification of rice varieties via raman spectroscopy

Optimizing DD-SIMCA modeling for accurate classification of rice varieties via raman spectroscopy

Rice variety significantly affects its processing and quality This study established an efficient, fast, trustworthy and nondestructive method for identifying rice varieties by coupling Raman spectroscopy and multivariate data analysis. 164 rice samples, consisting of 68 Hashemi, 21 Tarom, 24 Fajr,...

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Bibliographic Details
Main Authors: Somaye Vali Zade, Hamed Sahebi, Adel Mirza Alizadeh, Behrooz Jannat, Hossein Rastegar, Solmaz Abedinzadeh, Fataneh Hashempour-Baltork, Amin Mousavi Khaneghah
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Applied Food Research
Subjects:
Adulteration
Chemometrics
Purity
Rice
Raman spectroscopy
Online Access:http://www.sciencedirect.com/science/article/pii/S2772502225002173
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http://www.sciencedirect.com/science/article/pii/S2772502225002173

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