## 1 Introduction  
Indonesia is the world's third-largest rice producer in addition to one of the world's major rice consumers [1]. Within this region, rice dominates not only food security but also national economies. Rice has been cultivated in Indonesia from the time between 2000 and 1400 B.C., while the production has considerably increased since 1925, thereby giving rise to a number of rice varieties. There are two groups of the grains based on their aroma (i.e., aromatic and non-aromatic) [2]. Some rice varieties are known as aromatic rice. They contain some typical volatile compounds released from the grain that discriminate these rice varieties from the ordinary ones [3]. These varieties have become more widely appreciated in the current market for their specific aroma properties in addition to their appearance and taste. Since the grain aroma is a primary sensory attribute of high-quality rice that has a critical impact on consumer preference, recent researches have led to an increase in rice breeding programs and genetic modifications focusing on the odour profile to generate high-quality aromatic rice cultivars [4]. Henceforth, an analytical method for key-marker volatile compounds determination is crucial to facilitate the characterization [5] that is useful for the selection of lines with superior quality attributes. In addition to the marker-assisted breeding in question, the need for a novel analytical method to improve the accuracy of the determination of volatile compounds is also essential to confirm the geographical origin discrimination [6]. Therefore, in particular, this study comprised three main parts: (i) Contrast the volatile composition of Indonesian aromatic and non-aromatic rice varieties to define the key-marker volatile compounds; (ii) focus on optimisation and validation of the analytical method for the extraction of key-marker compounds from rice grains; and, lastly, (iii) applying the developed method to assess a number of aromatic rice samples. Research into key-marker volatile compounds in rice was started more than thirty years ago [7] and this has continued to be an active field of the recent studies, indicated by numerous reports mainly focused on a single compound recognised as the most important marker for rice volatile, viz., 2-acetyl-1-pyrroline [8; 9; 10; 11; 12; 13]. However, updated researches on volatile compounds that contribute to prominent distinction of a premium quality of rice grains have been limited by the concentration of the compounds and complexity of rice matrices that contain a diverse range of primary and secondary metabolites [14]. A two-dimensional gas chromatography (GC\(\times\)GC) coupled with time-of-flight mass spectrometry (TOFMS) detector offers a solution to the aforementioned problem, as a cutting-edge chromatographic technique that provides complete separation and full scan collection of spectral data, for thousands of compounds to low pg Kg\({}^{-1}\) concentrations. This approach can provide a broad fingerprint, which greatly increases the probability of recognising new compounds and commences potential key-marker volatile compounds. In this study, volatile compounds identified by the GC\(\times\)GC-TOFMS were then evaluated using principal component analysis (PCA) for screening the main compounds that are responsible for the typical volatile compounds of aromatic rice. Prior to GC\(\times\)GC-TOFMS analysis, modern studies have shown that headspace solid-phase microextraction (HS-SPME) is a suitable sample preparation technique to increase the extraction efficiency for various trace compounds in food matrices [15; 16; 17]. The factors that influence the yield of the HS-SPME are predominantly related to adsorption time and temperature. Additionally, pre-incubation time and headspace volume were also found to affect the HS-SPME recovery [18]. As a number of factors can involve in the course of the extraction, the screening and optimisation of the significant factors must be carried out in order to establish a reliable analytical HS-SPME method.