## 4 Applications in Food Analysis  
The research of aroma-active compounds in foods was developed simultaneously with the introduction of the first gas chromatographs in the early 1960s [194]. In the headspace of foodstuffs the occurrence of around 10,000 compounds was estimated [195]. When considering the choice of suitable methods for food analysis, it is essential to realize that food is a complex, heterogeneous mixture composed of a multitude of different compounds. The analysis of volatile target analytes requires the extraction from the food matrix. It is nearly impossible to analyse food samples without sample pretreatment even though advanced techniques of separation and identification have been made available. Therefore, sample extraction, removal of interferences and the pre-concentration of analytes are mandatory procedures [196]. Developing reliable and sensitive SPME methods for food analysis requires the selection and optimization of parameters like the fiber coating, sampling technique, agitation conditions, sample volume and extraction and desorption conditions [197]. Simultaneous variation of several control variables is possible by applying multivariate test designs reducing the experimental effort for SPME optimization [198]. Multivariate test designs such as full factorial design, Doehlert matrix, \(2^{4}\) experimental design and Design of Experiments are valid multivariate test designs for SPME method optimization [55, 56, 199]. SPME has been widely applied to the sampling and analysis of food matrices. Table 3 provides a comprehensive overview of SPME applications divided into different analyte classes; aroma, off-flavor (food products), off-Flavor (food packaging migrants) and volatile toxic compounds. Figure 8 shows the numbers of papers dealing with applications of SPME to the different types of analytes based on a ScienceDirect literature research for years 2005 to 2015. Hundreds of papers reporting SPME applications in the field of food analysis have been published in recent years (see Table 3). The vast majority of which referred to aroma analysis (see Figure 8). The applications of SPME to different food matrices are shown in Figure 9. The majority of applications refer to the food classes fruits/vegetables, fats/oils, wine, meat, dairy and (non-) alcoholic-beverages. The results are comparable to those published by [PERSON] _et al_. [13] derived from a Web of Knowledge search in food aroma analysis between 2006 and 2011. The microextraction technology in greatest use second to SPME (91%) was SBSE (5%), followed by SDME and LLME. The advantage of SBSE is a particularly high sensitivity for semi volatiles. However, SBSE suffered for a long time due to only one available coating (PDMS). Due to the lack of automated versions of SDME and LLME, and also due to their lower popularity in the scientific community (compared to SPME and SBSE) their use in aroma analysis is yet not enough explored. The diversity of matrices for which microextraction methods other than SPME are used proves that these methods await broader applications in aroma analysis [13]. Figure 8: Application of SPME to different types of analytes. Number of papers based on ScienceDirect search for years 2005–2015. Figure 9: Application of SPME to different food matrices. Number of papers based on ScienceDirect search for years 2005–2015. ==ERROR: No output for this page==