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Journal of Food Measurement and Characterization

, Volume 13, Issue 3, pp 1705–1712 | Cite as

Evaluation of sample pretreatment method for geographic authentication of rice using Raman spectroscopy

  • Min ShaEmail author
  • Dongdong Gui
  • Zhengyong Zhang
  • Xinyan Ji
  • Xiaojing Shi
  • Jun Liu
  • Ding Zhang
Original Paper
  • 52 Downloads

Abstract

The constituents of rice are heterogeneously distributed in a grain, collection of Raman spectra providing a better compositional representation of rice is an essential requirement for accurate discrimination of rice samples according to geographical origin. Homogeneity of rice flour with four different particle sizes was investigated by relative standard deviation (RSD) analysis and hierarchical clustering analysis (HCA) of Raman spectra. RSDs of Raman spectra of rice flour at 100–140 mesh were the smallest while HCA showed the highest similarities. Besides, Raman spectra of rice flour at 100–140 mesh were similar to those of rice flour with diameter below 0.6 mm. In addition, the experimental results were universally applicable for different batches and geographical origins of rice. The discrimination accuracy performed by support vector machine was obviously improved when using the Raman data of rice flour at the size of 100–140 mesh, hence, the recorded Raman spectra could provide reproducible and reliable data for discrimination the geographical origin of rice.

Keywords

Rice Geographical origin Raman spectroscopy Sample representation Discriminant analysis 

Notes

Funding

This research was financially supported by the Natural Science Foundation of Jiangsu Province under Grant BK20180816; Natural Science Foundation of Jiangsu University under Grant 17KJD550001; and the National Natural Science Foundation of China under Grant 61602217.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Management Science & EngineeringNanjing University of Finance & EconomicsNanjingChina
  2. 2.School of Chemical EngineeringNanjing University of Science and TechnologyNanjingChina

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