Plants have been discovered to emit acoustic signals when experiencing drought stress. These acoustic emissions originate from sudden tension releases in the xylem vessels, which transport water within the plant. The rate at which the plants emit these signals increases in the initial stages of the desiccation process, but will reduce later on. Instead of monitoring these acoustic emissions, drought stress can also be identified by actively sending acoustic signals through the stem. This method is applied by Plense Technologies, who develop sensors that transmit ultrasound signals through the plant stem and aim to identify drought stress in an early stage. This can be used as a tool to improve crop irrigation management. However, knowledge on the vibratory dynamics of plant stems and xylem vessels is lacking due to the complexity of the material and frequency spectra, which makes the identification of drought stress in the stems difficult.

State-of-the-art research shows that stem characterization can be performed through modal analysis using Laser Doppler Vibrometry. This method has been performed on both stems and leaves and has been proven to accurately depict the effective properties of the material. This method is suitable for obtaining the vibratory dynamics of the bulk material of the stem, while the acoustic measurements can be implemented to capture xylem vibrations. In addition, computational modeling of the dynamics of plant stems and xylem vessels has rarely been performed, as observed from the state-of-the-art literature. The experiments using Laser Doppler Vibrometry and acoustics, combined with computation modeling of the stems and xylem vessels, form the research gap of this project.

In this thesis, the desiccation behavior of chrysanthemum stems is identified from its elastic and dynamic properties. Chrysanthemums are one of the largest commercial flowers and were selected for their straight stems and usability in the experiments. Experimental modal analysis was performed on the 38 stem over a period of 3 weeks, using a laser Doppler vibrometer and the acoustic sensor developed by Plense Technologies. The goal of these methods was to obtain empirical data on the vibratory dynamics of the stems and xylem vessels over time, respectively. In addition, the mass and diameters of the stems were captured and used to calculate the density of the stems. These parameters were analyzed to determine whether they show desiccation behavior. The laser Doppler vibrometry method was validated through a 3-point bending test to see whether the eigenfrequency is suitable to derive the elastic properties of the stems. The eigenfrequency and bending stiffness were analyzed to determine whether they are suitable parameters for identifying desiccation. Microscopic imaging of the cross sections of the stems was performed to obtain the diameters of the xylem vessels and to get an idea of the inner structure of the stems. Finally, a desiccation experiment was performed in parallel to the mentioned experiments, where 10 plants were measured for a duration of 6 weeks. The parameters suitable for identifying and monitoring desiccation were the mass, density and bending stiffness of the stems. The diameter and eigenfrequency were observed not to be statistically significant enough to monitor desiccation.

Three computational models were designed to simulate the vibratory dynamics of the stems, with three different geometries. The geometries of the models were a cylinder, an elliptical cylinder and a frustum. An optimization script was designed, which minimizes the error between empirically obtained and simulated eigenfrequencies of the stems and computes the related Young's modulus. This optimization was performed on both the first and second bending modes and from the results it was concluded that the frustum model had the best performance. The Young's moduli obtained from all three models were observed to be statistically significant, indicating that it is a suitable parameter to identify desiccation behavior. The xylem vessels were modeled using computational models designed by Dutta et al., 2022, which were adjusted to be implemented in this study. A section of the data obtained from the acoustic modal analysis contained clipped signals, which could not be used for the analysis. A resonance peak was identified, but could not be determined with certainty to be a eigenfrequency of the xylem vessels, due to the lack of knowledge on this matter. However, it was investigated what type and order of eigenmode it would be if it was a resonance of the xylem. It turned out to be a third-order bending mode and this was simulated, accordingly. The results from the model showed significantly higher eigenfrequencies, related to the third eigenmode. Further research on vessels and vascular tissue is required to improve the results.