## 1 Introduction  
Aroma is an important quality indicator of edible plant oil. Aroma is determined by the volatile organic compounds (VOCs) present in oil, which vary depending on factors like raw materials, processing techniques, cooking practices, and freshness [1; 2; 3; 4]. Sesame oil is a popular type of fragrant edible plant oil with a consumption history dating back to the Babylonian era [5]. Making up approximately 50% of the total mass, oil can be easily obtained from sesame seeds by various oil pressing techniques, including cold pressing, hot pressing, and small milling (\"Xiao Mo\" in Chinese), as well as solvent extraction [6; 7]. In both hot pressing and small milling, mechanical force is used to extract oil from roasted sesame seeds. However, in small milling, hot water is used to separate oil and undesirable components by their difference in density [8]. Hence, small milling is sometimes referred to as the hot-water floatation method [9]. In both processes, the oil produced does not undergo further refining, so as to preserve the aroma. Existing studies have found that fragrant sesame oil produced by different techniques has different VOC profiles [10]. Fragrant sesame oil is sometimes blended with refined oil for various purposes [11; 12; 13]. Since refining removes most of the VOCs from oil, the resultant blended oil has a VOC profile that is different from pure fragrant sesame oil [14]. Such differences in VOC profiles affect the sensory attributes and, subsequently, consumer preference [9; 10; 15]. Considering the increasing demand for high-quality fragrant sesame oil, aroma analysis is always a topic of interest in the industry. In the food industry, the aroma of sesame oil is commonly assessed by human sensory evaluators. Despite being closer to consumer perception, sensory analysis is constrained by many factors, including a long training time and the subjective nature of individuals' feelings [16; 17; 18]. Over the years, various laboratory-based methods have been adopted to assist humans in aroma analysis, with gas chromatography (GC) being the most widely adopted method. However, discrepancies in signal interpretation exist between GC-based techniques and human olfaction. Unlike human olfaction, where the electrochemical signals generated by olfactory receptors are integrated into one scent \"fingerprint\", GC-based techniques are analytical in nature and hence, information on aroma is fragmentized into molecular compositions [19]. To mimic humans in odor sensing, artificial noses utilizing a diverse range of materials and mechanisms have been developed since 1982 [20]. Similar to the human olfactory system, an artificial nose consists of a sensor array with cross-reactiveness and a pattern recognition system that functions similarly to the human brain [21; 22]. Although research on analyzing edible plant oil VOCs with artificial noses has been ongoing for the past two decades, most of the studies employed general-purpose commercial electronic noses (E-noses), making it difficult to correlate the results to the chemistry of oil VOCs [23]. Moreover, E-noses require sophisticated and expensive equipment for data collection and a professional background for data interpretation. Hence, there is a need to explore a cost-effective and simple alternative. Colorimetry is a principle frequently used in VOC sensors, whereby the presence of target VOCs is reflected as a color change. Compared with other sensing techniques, colorimetric sensors could achieve higher sample throughput and faster response without compromising sensitivity and accuracy. Most importantly, sensor readouts can be observed by the naked eye, and no complex data processing is required. As a result, colorimetric sensors have become a topic of interest in food testing, especially in the freshness monitoring of perishable food products like meat and fruits [24; 25; 26; 27].