Construction and application of exclusive flavour fingerprints from fragrant rice based on gas chromatography – ion mobility spectrometry (GC‐IMS)

Abstract

Fragrant rice has unique aroma characteristics appreciated by many consumers. In order to extract exclusive flavour fingerprints from Guangxi fragrant rice and to further verify its effectiveness by allowing the rapid identification of fragrant rice from two main production regions (Guangxi and Wuchang), gas chromatography-ion mobility spectrometry (GC-IMS) technology was applied to analyse flavour components of 53 fragrant rice samples. Based on the two-dimensional GC-IMS map, characteristic variables of flavour components from Guangxi fragrant rice were screened via image pretreatment and automatic threshold segmentation algorithm. The extracted variables were further processed by using principal component analysis and quadratic discriminant analysis to establish a non-linear model for discriminating two types of fragrant rice. The results showed that a total of 46 characteristic variables were extracted from Guangxi fragrant rice, and the first two principal components showed that the two types of rice samples had their own corresponding regions. 2-Butanone, 2-heptanone, pinene, 1-heptanal, 2-methyl-1-butanol acetate and octanal were the key different flavour components. The established model had an excellent recognition rate, which could be used to determine the geographical region of fragrant rice.The proposed method could achieve quick, non-destructive and accurate analysis of fragrant rice geographical properties. It can be further applied in feature extraction from the two-dimensional fingerprint map generated by other similar combined instruments.

The Effects of Genotype × Environment on Physicochemical and Sensory Properties and Differences of Volatile Organic Compounds of Three Rice Types (Oryza sativa L.)

“…According to Chen et al [ 30 ], the volatile organic components of six varieties with the lowest and highest SCR scores in the sensory evaluation were analyzed by HS-GC-IMS consisting of a 60-position headspace auto-sampler (PAL RSI, CTC Analytics AG, Zwingen, Switzerland), an Agilent 490 Micro GC (Agilent Technologies, Santa Clara, CA, USA) and a FlavourSpec ® advanced IMS (G.A.S. mbH, Dortmund, Germany).…”

Application of GC-IMS coupled with chemometric analysis for the classification and authentication of geographical indication agricultural products and food

“…The cultivar and production area are key rice price determinants ( 29 ), with that of GI Wuchang rice 20 times higher than non-GI products due to its high quality and unique flavor. The fingerprints of 53 rice samples from two main production areas (Wuchang and Guangxi) were extracted via GC-IMS, while their efficacy for the rapid identification of fragrant rice was verified ( 5 ). A three-dimensional GC-IMS map was employed to select the characteristic flavor substances from the rice specimens using an automatic threshold segmentation algorithm and image pretreatment, after which PCA and quadratic discriminant analysis (QDA) models were established to discriminate between fragrant rice from two areas.…”

“…Combining GC-IMS GI product fingerprinting with chemometric methods is widely used for the identification of quality, adulteration, and fraud in products such as Jingyuan lamb ( 4 ), Wuchang rice ( 5 ), Fu brick tea ( 6 ), Shaoxing yellow wine ( 7 ), and Iberian dry-cured ham ( 8 ). Chemometrics models, such as partial least squares discriminant analysis (PLS-DA), are commonly used for sample classification.…”

Construction of aroma association network of cooked rice based on gas chromatography–mass spectrometry (GC–MS) and sensory analysis

“…Gas chromatography‐olfactometry (GC‐O) explored the method of combining modern instrument analysis and sensory perception from the perspective of instrument development, and successfully discovered some aroma compounds with low content but low perception threshold, and also detected some difficulty with volatile aroma components 10 . The electronic nose introduces sensors into the analysis of aroma components and performs mathematical analysis on the collected odour sensitivity signals in order to simulate the human perception of odours 11 . Many mathematical analyses have been performed on the instrumental results of aroma components to achieve pattern discriminant analysis 12,13 .…”

“…10 The electronic nose introduces sensors into the analysis of aroma components and performs mathematical analysis on the collected odour sensitivity signals in order to simulate the human perception of odours. 11 Many mathematical analyses have been performed on the instrumental results of aroma components to achieve pattern discriminant analysis. 12,13 Petronilho et al conducted a comprehensive determination of the volatile components of six wines and established a method based on a bipartite network consisting of two different nodes by combining different extraction techniques with GC analysis.…”