Geographical origin traceability of rice using a FTIR-based metabolomics approach

Area of Science:

• Analytical Chemistry
• Food Science
• Metabolomics

Background:

• Origin traceability of rice is crucial for quality control and consumer trust.
• Traditional methods face limitations in data mining and accuracy.
• Infrared spectroscopy offers potential but requires advanced analytical approaches.

Purpose of the Study:

• To develop a novel infrared spectroscopy-based metabolomics method for rice origin traceability.
• To identify specific 'wave number markers' for discriminating rice from different geographical origins.
• To validate the method's efficacy in distinguishing rice products from 14 Chinese cities.

Main Methods:

• Utilized infrared spectroscopy coupled with metabolomics analysis.
• Applied multivariate statistical methods including Principal Component Analysis (PCA), Cluster Analysis, and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA).
• Screened and verified characteristic 'wave number markers' using S-plot, permutation tests, Variable Importance in Projection (VIP), and pairwise t-tests.

Main Results:

• Successfully identified 55-265 'wave number markers' for 14 distinct rice groups.
• Characteristic wave number bands were identified, with most rice groups showing significantly low absorbance at their respective marker bands.
• A mixed rice sample demonstrated a distinct spectral profile, validating the method's sensitivity and accuracy in detecting variations.

Conclusions:

• Infrared spectroscopy combined with metabolomics provides a robust and effective approach for rice origin traceability.
• The developed method enables accurate and rapid discrimination of rice based on geographical origin.
• This study offers a novel perspective for applying metabolomics in spectral analysis, extending beyond origin traceability.