Integrated HS-GC-IMS and E-nose analysis reveals aroma differentiation in representative Chinese high-quality rice varieties.

Aroma is a key determinant of rice quality. This study systematically examined the divergence in aroma profiles between high-quality indica and japonica rice varieties grown across distinct ecological regions of China. We employed an integrated analytical framework combining sensory evaluation, volatile organic compound (VOC) profiling using HS-GC-IMS, E-nose response patterns, and fatty acid composition analysis. Clear differences in VOC composition were observed between indica and japonica varieties. Orthogonal partial least squares-discriminant analysis (OPLS-DA) effectively distinguished their flavor characteristics; notably, japonica rice exhibited higher mean levels of 2-acetyl-1-pyrroline (2-AP) and 1-octen-3-ol than indica rice. These VOC variations were closely associated with fatty acid profile. Significantly, a Ridge regression model was established by combining HS-GC-IMS and E-nose data, enabling the accurate prediction (R2 = 0.720) of cooked rice aroma.