# Influence of Electrohydrodynamics on the Drying Characteristics and Volatile Components of Ginger
## 3 Results and Discussion
### Volatile Components
In general, the change of volatile components in materials is related to microbial metabolism, bacterial proliferation, and some chemical reactions, and the drying characteristics of different drying methods differ, in which the active substances produced by the discharge plasma during the drying process react with the volatile components of the materials, thus changing the volatile components of ginger. Natural air-drying causes a substantial oxidation of ginger throughout the drying process due to the abnormally extended drying time, which damages ginger's volatile components. As a result, the volatile contents of the various drying techniques differed significantly. The research results of gas chromatography-mass spectrometry (GC-MS) were analyzed using chemometrics. The first stage of data analysis used principal component analysis (PCA) to provide an overall picture of all sample differences and identify the biomarkers that caused these differences. Principal component analysis (PCA) was conducted on the volatile components of ginger under different drying procedures, with 70 common volatile components as independent variables and several drying methods as independent factors [47]. PCA has been found to be effective at simplifying data and revealing interrelationships between samples. This approach, which describes unsupervised categorization trends between data, is increasingly commonly utilized [48]. Figure 9a shows the results, with PC1 (39.3%) and PC2 (24.6%) accounting for 63.9% of the total variation. Ginger dried using different ways may be clearly recognized based on volatile components, with electrohydrodynamic drying (EHD) concentrated in quadrants two, three, and four and natural air drying concentrated in quadrant one. As can be observed, the effect of different drying processes on volatile components varies greatly. The PCA helps us to identify different drying methods. In addition, using the content of volatile compounds as the dependent variable and different drying voltages as independent variables, orthogonal partial least squares discriminant analysis (OPLS-DA) can effectively distinguish ginger under different drying conditions (Figure 9b). The results revealed that the experimental group was in the first, second, or fourth quadrants, but the control group was in the third quadrant. In the OPLS-DA model analysis, the model fitting index R\({}^{2}\)\({}_{X}\) is 0.978, R\({}^{2}\)\({}_{Y}\) is 0.999, and Q\({}^{2}\) is 0.998. Both R\({}^{2}\) and Q\({}^{2}\) are greater than 0.5, indicating a good fit of the model [49]. In addition, 200 repeated permutation tests were conducted to evaluate the robustness of the OPLS-DA model. As shown in Figure 9c, the intersection points between the Q\({}^{2}\) regression line and the vertical axis is less than zero, indicating that the model is not overfitting and is effective. The findings are valuable for identifying and analyzing volatile chemicals in ginger using various drying processes. The variable projected importance (VIP) was utilized to assess each variable's influence and explanatory power in classification and discrimination. When the VIP surpassed 1, the variable was thought to play a significant effect.