Discrimination of organic and conventional rice by chemometric analysis of NIR spectra: a pilot study

  • Ran Xiao
  • Li Liu
  • Dongjie Zhang
  • Ying MaEmail author
  • Michael O. NgadiEmail author
Original Paper


A pilot study was conducted to develop nondestructive calibration models to discriminate organic and conventional rice from selected field trials in Heilongjiang Province, China using near-infrared (NIR) spectroscopy with the absorption mode in the wave number range of 12000–4000 cm−1. Multivariate methods such as principal component analysis (PCA) and partial least squares (PLS) regression were used to interpret the NIR spectral data. PLS regression was used for discrimination between organic and conventional rice samples after several pretreatments of the spectra. The coefficient of determination (R2) value for the PLS regression model was 0.8430 with a standard error for cross validation (SECV) of 0.1992 and a root mean square error for cross validation (RMSECV) of 0.1982. Overall, the results indicated good performance of the prediction models and supported the capability of NIR spectroscopy to classify between discriminate organic and conventional rice. This study further supports the utilization of NIR in the discriminative analysis of foods and as a noteworthy method for the authentication of organic rice at the industrial level.

Graphical abstract


Organic rice Near-infrared (NIR) spectroscopy PCA PLS regression 



The authors would like to acknowledge the financial support provided by the Research & Development Projects of Heilongjiang Province (Project GA14B104). We would also like to thank the Heilongjiang Academy of Agricultural Sciences for providing rice grain information and McGill University and Northeast Agricultural University for scientific support and technical advice.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Chemical Engineering and TechnologyHarbin Institute of TechnologyHarbinChina
  2. 2.Department of Bioresource EngineeringMcGill UniversityMontrealCanada
  3. 3.Department of Food ScienceHeilongjiang Bayi Agricultural UniversityDaqingChina

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