Study on stage quality discrimination during the rice mildew process based on multi-source flavor information fusion

Abstract

In order to discriminate the early stages of rice mildew process, headspace solid-phase microextraction equipped with gas chromatography-mass spectrometry (HS-SPME-GC-MS) and gas chromatography-ion mobility spectrometry (GC-IMS) were used to analyze volatile organic compounds (VOCs) changes in the process of rice mildew respectively. Two types of VOCs data were fused using primary fusion and feature-level fusion methods, and orthogonal partial least squares discrimination analysis (OPLS-DA) was applied to establish a discriminant model by combining the clustering results of multi-physicochemical indicators. The clustering analysis of physicochemical indicators exhibited that the rice mildew process could be divided into 6 stages. The OPLS-DA model based on primary fusion demonstrated the highest effectiveness in distinguishing different stages of rice mildew; the goodness of fit (R²) was 0.98, and the goodness of prediction (Q²) was 0.93. In conclusion, the combination of GC-MS and GC-IMS technologies could effectively distinguish the early stages of rice mildew process, which would serve as a valuable reference for the rapid and nondestructive detection of rice quality throughout the mildew process.