## 1 Introduction  
Plants and animals, including humans and microorganisms, can produce volatile organic compounds (VOCs). For example, VOCs in exhaled breath show specific profile patterns with respect to various cancers [1; 2; 3; 4; 5; 6; 7; 8]. _In vitro_ and _in vivo_ experiments have been conducted for VOC profiling in rat and cattle breath as case studies of animal VOCs [9; 10]. Microorganisms can produce various types of VOCs, which are likely to have crucial effects on soil ecology [11] and on interactions across other organisms [12; 13; 14; 15]. Plants also contain a large variety of VOCs, including simple gases and other VOCs. At present, approximately 1,700 compounds are identified as VOCs, and these account for more than 1% of plant secondary metabolites [16; 17]. The main classes of plant VOCs are terpenoids, phenylpropanoids/benzenoids and fatty acid and amino acid derivatives [18]. Plants can emit various types of VOCs, not only to communicate with herbivores, microbes and neighboring plants, but also to respond to abiotic factors, such as light and/or temperature, atmospheric CO\({}_{2}\) concentration or nutrition [19; 20; 21]. Therefore, plant VOCs are potential biomarkers capable of identifying the physiological states of plants and the stresses to which they have been subjected. Sensitive methods have been developed for headspace (HS) sampling and VOC analysis. HS sampling is a non-destructive method for collecting volatile compounds. Static and dynamic sampling methods are widely used for collecting HS samples [22]. Static HS sampling is suited for qualitative analyses of VOCs and surveys of VOC profiles of different plant species or cultivars at a single time point, while dynamic HS sampling enables us to quantify changing VOC emissions in the form of real-time analysis. Many devices can be used to collect VOCs, e.g., solid phase microextraction (SPME) fibers, stir bar sportive extraction (SBSE) devices [23; 24] and in-tube extraction (ITEX) [25; 26]. Sensor arrays composed of thin nanostructure films, such as monolayer-capped metallic nanoparticles and chemiresistive random network of single-walled carbon nanotubes, can be used as diagnostic tools to detect VOCs in exhaled breath samples [27; 28]. Gas chromatography (GC)-based techniques are widely used for static HS analyses, including GC-mass spectrometry (GC-MS), GC-flame ionization detection (GC-FID), GC-electroantennogram detection (GC-EAD) and two-dimensional GC-MS (GC\(\times\)GC-MS) [17; 22; 29]. We can directly inject a mixture of VOCs into GC instruments, since no derivatization steps are required. Fast isoprene sensor chemiluminescence detection (FIS), laser-based infrared photoacoustic (PA) spectroscopy and proton transfer reaction-mass spectrometry (PTR-MS) enabled us to conduct real-time detection of VOCs from plants [18]. One ultimate goal of metabolomics is to identify and quantify the metabolome in organisms, which includes VOCs. Development of MS-based technologies in metabolomics enables the measurement of hundreds of metabolites [30, 31, 32]. In particular, electron impact-time-of-flight-MS (EI-TOF-MS) provides us with comprehensive information on molecular fragments as mass-to-charge ratios [33]. Annotation of each spectrum of a VOC is performed by finding an exact match to a reference spectrum from well-established libraries, such as NIST/EPA/NIH Mass Spectral Library [34], Adams Library [35], Terpenoids Library ([[http://massfinder.com/wiki/Terpenoids_Library](http://massfinder.com/wiki/Terpenoids_Library)]([http://massfinder.com/wiki/Terpenoids_Library](http://massfinder.com/wiki/Terpenoids_Library))) and VocBinbase [36]. The Kovats retention index (RI), calculated by comparing the chromatographic retention time of _n_-alkane peaks, is often used to annotate detected peaks [37]. A combination of these libraries and RI information is indispensable to annotate detected peaks in a non-targeted matter.