# Current Trends in Fully Automated On-Line Analytical Techniques for Beverage Analysis
## 3 Solid-Phase Microextraction (SPME)  
Of all matrices, food - a group of diverse matrices that includes both liquid (beverages) and solid formats - present one the most diverse and complex compositions. This constitutional diversity creates challenges and difficulties that cause food analysts to search for the best sample preparation technique to carry out their analysis. Analysts face the challenge of developing faster and more precise methods that can guarantee the safety, quality, authenticity and traceability of food products. Nowadays, extensive efforts towards the modernization of analytical instrumentation have been greatly simplified and, at times, have even eliminated the need for complex and laborious sample preparation procedures before analysis [44].  
There are still situations in which the sample preparation represents the bottleneck in the search for ideal analytical methodologies. As such, simpler sample preparation methods are sought, not only to reduce the time required to process them, but also to reduce the errors associated with each step of the procedure, since, statistically, the amount of uncertainty in a method is directly related to the number of steps it contains. One of them was introduced at the beginning of the 1990s, so-called solid-phase microextraction (SPME). This technique addresses several advantages over the traditional sample preparation technique since it successfully integrates several analytical steps, such as sampling, extraction, pre-concentration and, in the case of applications coupled to GC, the direct introduction of the extract into the analytical instrument [44].  
SPME is a portable, simple, sensitive, time-efficient, cost-effective, reliable, easy-to-automate sample preparation technique that minimizes solvent consumption. Unlike conventional exhaustive extraction methods, such as SPE, SPME is a non-exhaustive technique based on the partition equilibrium of the analytes between the sample matrix and the extraction phase. In SPME,the extraction phase can be exposed directly to the sample medium (direct immersion, DI) or its head-space (HS). When the SPME coating is placed directly in contact with the sample, the amount of analyte extracted in equilibrium (\(n_{e}\)) can be described as [45]:  
\[n_{e}=\frac{K_{fs}\times V_{s}\times V_{f}}{K_{fs}\times V_{f}+V_{s}}\times C_{s} \tag{2}\]  
where \(n_{e}\) is proportional to the distribution coefficient of the analyte between the coating and the sample matrix (\(K_{fs}\)), the volume of the extraction phase (\(V_{s}\)), the volume of the sample (\(V_{f}\)) and the concentration of the analyte in the sample matrix (\(C_{s}\)). This implies that the amount of analyte extracted on the coating (\(n_{e}\)) is linearly proportional to the concentration of the analyte in the sample (\(C_{s}\)), which is the basis for quantitative analysis using SPME. Considering that the volume of the extraction phase \(V_{s}\) is large enough (\(V_{s}>>K_{fs}V_{f}\)), Equation (2) can be simplified in the following way:  
\[n_{e}=K_{fs}\times V_{f}\times C_{s} \tag{3}\]  
According to this equation, the amount extracted by the coating is directly proportional to the concentration of the sample and completely independent of the volume of the sample. This conclusion is of great importance since it demonstrates the ability of the SPME to achieve reliable quantitative results [45].  
SPME is available in different configurations, represented in Figure 2. The best-known configuration is that consisting of a covered extraction phase on a fused silica bar. In applications where the SPME fiber is coupled to GC, complete automation is achieved due to the commercialization of automatic injectors dedicated to SPME and its similarity to the injection syringe used in GC [45]. Simple SPME configurations allow applications to increase in number, which in turn, motivated procuring improved and novel sorbent materials, to increase SPME applications in various sample matrices and analytes.