Non-destructive Analysis of Volatile Compounds for Geographical Identification of Rice

Abstract

Background In recent years, high-quality rice adulteration has become a serious problem. It is essential to prevent false origin labels and dishonest transactions. However, there is still a lack of rapid identification methods for discriminating rice from different sources. In this study, we developed a method to profile volatile organic compounds (VOCs) using headspace solid phase microextraction (HS-SPME) combined with gas chromatography mass spectrometry (GC-MS). In addition, the identification efficiency of the biomarkers was determined using several multivariate analysis methods. Results Based on the t-test, fold changes and volcano plots, eight typical biomarkers were used based their differential levels. Among them, 2-acetyl-1-pyrroline (2-AP) is the most important source of aroma in rice flavor. Unsupervised analyses, including principal component analysis (PCA) and Cluster analysis, demonstrated the potential for geographic classification of rice between Wuchang and other regions. In addition, partial least squares discriminant analysis (PLS-DA) yielded a goodness of fit of 0.900, a goodness of prediction of 0.853, and a probability of substitution test of 0.012. Random forest (RF) algorithm further strengthened the discriminating ability of volatile compounds. Conclusion In short, the current method can quickly distinguish rice from Wu Chang and other regions, and the research method can facilitate controlling the authenticity and quality of rice.