## 4 Current Analytical Techniques  
Due to their low concentration, functional groups, polarity, and physical and chemical properties, VOCs are challenging to detect without precise analytical equipment [12; 30]. Gas chromatography and mass spectroscopy (GC-MS) are widely used to analyze a sample's volatilome based on its polarity and boiling point. Subsequently, these VOCs can be identified and quantified using mass spectra with authentic standards, chemical library spectra, and chromatographic retention indices, as reported by [PERSON] and [PERSON] [43]. Table 2 shows examples of the main analytical techniques used to quantify VOCs emitted by fungi and bacteria in agricultural products. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Analytical Technique** & **Microorganism** & **Result** & **Reference** \\ \hline \multirow{6}{*}{GC-MS and e-nose.} & \multirow{6}{*}{_Botrytis_ sp., _Penicillium_ sp., and _Rhizopus_ sp. & Strawberry was analyzed by GC-MS, which found five compounds common among fungi: hexyl acetate, methyl hexanoate, ethyl hexanoate, hexanoate, hexanoic acid, hexol ester, and trans-nerolidol. E-nose could detect strawberry fruits’ decay on the second storage day. Changes in VOCs of inoculated peaches were correlated with total amounts and species of fungi. Terpenes and aromatic compounds were the main contributors to e-nose responses. This technique had high discrimination accuracy, among fungal contamination in peaches. Orange leaves were inoculated with _Diaphorina citri_, the vector responsible for Huanglongbing disease. The VOCs generated were analyzed by HS-GC-IMS, reporting 36 compounds released by the leaves during infection, limonene being the main one. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Analytical Technique** & **Microorganism** & **Result** & **Reference** \\ \hline \multirow{6}{*}{GC-MS and e-nose.} & \multirow{6}{*}{_Botrytis_ sp., _Penicillium_ sp., and _Rhizopus_ sp. & Strawberry was analyzed by GC-MS, which found five compounds common among fungi: hexyl acetate, methyl hexanoate, ethyl hexanoate, hexanoic acid, hexol ester, and trans-merolidol. E-nose could detect strawberry fruits’ decay on the second storage day. Changes in VOCs of inoculated peaches were correlated with total amounts and species of fungi. Terpenes and aromatic compounds were the main contributors to e-nose responses. This technique had high discrimination accuracy, among fungal contamination in peaches. Orange leaves were inoculated with _Diaphorina citri_, the vector responsible for Huanglongbing disease. The VOCs generated were analyzed by HS-GC-IMS, reporting 36 compounds released by the leaves during infection, limonene being the main one.  
\end{table} 
Table 2: Analytical techniques used to detect phytopathogens through VOCs. According to Clarivate [11], as a tool to detect microbial contamination in agricultural products, GC-MS is used in disciplines such as food science technology, applied chemistry, microbiology, agriculture, entomology, and biotechnology. For example, [PERSON] et al. [50] analyzed fresh grapes contaminated with _Aspergillus carbonarius_ using HS-SPME-GC-MS. They found that ochratoxins produced by the fungi can be detected from VOCs such as ethyl acetate (\(p<0.01\)), styrene (\(p<0.05\)), and 1-hexanol (\(p<0.05\)), and VOCs such as (E)-2-hexenal (\(p<0.05\)) and nerolic acid (\(p<0.05\)) are negatively correlated. Similarly, [PERSON] et al. [51] used GC-MS to analyze the volatilome of pathogenic and non-pathogenic _E. coli_ strains to identify if strawberry is a suitable host and to detect if strawberries absorbed the bacterial VOCs. They found that the pathogenic and non-pathogenic _E. coli_ O157:H7 emitted a profile of volatile compounds comprising predominantly indole and methyl ketones. Strawberry was a suitable host for _E. coli_ O157:H7, which either proliferated at relatively low inoculum levels (\(10^{5}\) cells mL\({}^{-1}\)) or remained at a stable population at higher inoculum levels (\(10^{6}\)-\(10^{7}\) cells mL\({}^{-1}\)).