HS-SPME is founded upon the equilibrium between the sample matrix, the headspace of the vial, and SPME fiber; it permits direct sampling and does not necessitate the use of organic solvents. Volatiles diffuse from the sample into the headspace, where they then adsorb onto the fiber and finally thermally desorb at the injection port of the GC for analysis [2; 14]. The HS-SPME method is capable of extracting a greater quantity of low-molecular-weight volatiles [15]. GC-MS has been proven to be very sensitive with respect to the known and unknown VOCs, GC for detection and separation, and mass spectrometry (MS) for the identification and characterization of individual atomic compounds in the sample matrix [3]. HS-SPME is often combined with GC-MS for the identification and quantification of VOCs. HS-SPME-GC-MS is extensively utilized to analyze a diverse array of products, including rice [16; 17], tea [18], passion fruit [19], prickly ash [20], pomegranate [21], walnut [22], jasmium samabe [23], and so on. Headspace gas chromatography-ion mobility spectrometry (HS-GC-MS) combines GC and IMS to obtain VOC profiles based on the difference in the drift time of ionized VOC in a drift tube under atmospheric pressure; it is suitable for the detection of trace VOCs, and it is used to analyze the VOCs of aromatic and non-aromatic rice cultivars [24; 25]. HS-SPME combined with two-dimensional gas chromatography, as well as time-of-flight mass spectrometry (GC \(\times\) GC-TOFMS), can completely separate and collect spectral data in a full scan, which increases the possibility of identifying new compounds and mining potential key-marker volatile compounds. The method has previously been applied in the study of key-marker volatile compounds in aromatic rice grains [6]. The odor activity value (or relative odor activity value (rOAV)) is the ratio of the concentration of each VOC to the odor threshold (OT), serving as a critical metric for assessing the impact of specific aromatics [26]. It is generally believed that VOCs with OAV/rOAV > 1 significantly contribute to the overall aroma profile of a sample [27]. [PERSON] et al. [28] identified seven aroma-active compounds, including hexanal, octanal, nonanal, (E)-2-octenal, decanal, 1-heptanol, and 1-octanol in jasmine rice. [PERSON] et al. [29] studied the changes in aromatic substances during the growth of navel oranges and indicated that 14 substances were the key aroma components, among which linalool, \(\beta\)-myrcene, and limonene achieved the highest OAV. [PERSON] et al. [22] found that walnut oil odor in the early ripening stage derived from 1,8-cineole (OAV 280) and ethanol (OAV 134.5) and in the mid-ripening stage derived from nonanal (OAV 181.82), (E)-2-octenol (OAV 160), and hexanal (OAV 103.78), as well as the flavor of later ripening stage, were affected by nonanal (OAV 192.28), 1-heptanol (OAV 150), heptanal (OAV 71.11), and some organic acids. Combining the results of differential metabolites with OAV analysis allows the aroma profile of rice to be characterized, while key aromatic compounds can also be revealed. In this study, rice grains from three different varieties were collected at four critical ripening stages: 10 days after flowering (10 d), 15 days after flowering (15 d), 25 days after flowering (25 d), and 35 days after flowering (35 d), which are the important ripening stages of rice grain. We employed HS-SPME-GC-MS to detect the VOC components of rice-grain samples at each ripening stage. Next, we explored the characteristic VOCs and differential metabolites during the ripening of rice grains using chemometrics methods. Then, we assessed the impact of these VOCs on the overall aroma profile of the rice using rOAV. This research provides insights into the evolution of aroma profiles in rice grains, providing a foundation for the quality control of aromatic rice.