FOOD SCIENCE ›› 2023, Vol. 44 ›› Issue (8): 212-218.doi: 10.7506/spkx1002-6630-20220424-308

• Component Analysis • Previous Articles     Next Articles

Differential Fingerprint Analysis of Volatile Compounds in Rice with Remained Germ Roasted to Different Degrees by Gas Chromatography-Ion Mobility Spectrometry and Principal Component Analysis

WANG Ziyan, DOU Boxin, JIA Jianhui, ZHANG Yu, LIU Ying, ZHANG Na   

  1. (1. College of Food Engineering, Harbin University of Commerce, Harbin 150028, China;2. College of Life Science and Technology, Mudanjiang Normal University, Mudanjiang 157011, China; 3. College of Food Engineering, East University of Heilongjiang, Harbin 150076, China)
  • Online:2023-04-25 Published:2023-05-06

Abstract: The volatile flavor substances of rice with remained germ roasted to different degrees were analyzed and compared by gas chromatography-ion mobility spectrometry (GC-IMS) combined with principal component analysis (PCA), with the aim of establishing fingerprints of volatile components of rice with different roasting degrees. The results showed that the volatile substances of rice samples with different roasting levels could be well separated by GC-IMS, and in total 61 flavor compounds were detected in four rice samples at all roasting stages. Aldehydes, esters and heterocyclic compounds contributed more to the characteristic flavor of roasted rice, while alcohols and ketones also contributed to the characteristic aroma components of roasted rice. The types and contents of aroma compounds of rice with different roasting degrees were significantly different. PCA showed that the GC-IMS spectra of volatile components differed among rice with different roasting degrees, and the cumulative contribution rates of the first two principal components were both 94%, indicating that the flavor fingerprints of rice samples at different roasting levels can be successfully established using GC-IMS.

Key words: rice with remained germ; roasting; gas chromatography-mass spectrometry; principal component analysis; fingerprint of volatile components

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