Detection of Water Distribution in Plant Leaves Using Thermoacoustic Imaging
Objective The distribution of water content in plant leaves is an important indicator for measuring plant physiology and biochemistry,and it is also an important basis for formulating drought resistance strategies in the field of agricultural science.Microwave imaging has high contrast and sensitivity in the distribution and variation of water content,while ultrasound imaging has high resolution.Based on this,this paper proposes a non-destructive microwave thermoacoustic imaging(TAI)technology that combines the advantages of microwave and ultrasound imaging,and uses this technology to carry out non-destructive testing research on the distribution of plant leaf water content,which is of great significance for achieving precise irrigation,developing water-saving agriculture,and improving water resource utilization.Methods This study constructs a two-dimensional transmissive TAI system with an excitation frequency of 3.0 GHz and a lateral resolution of 0.406 μm.Based on active heating technology(150℃ hot air,90 s),3 sets of mandala leaf moisture loss processes were simulated,and their TAI images were quantitatively analyzed.Results The results showed that heating caused local moisture loss and reduced thermoacoustic signals,verifying the feasibility of non-destructive detection of plant leaf water content changes based on TAI,which achieves non-destructive detection of water content distribution in leaves of Datura,Crassocephalum crepidioides and Perilla.The results are consistent with magnetic resonance imaging(MRI).Conclusion This study contributes to achieve precise irrigation and provides technical support for studying the response characteristics of plants to the environment under normal and stress environments.Especially when combined with non-contact ultrasound detection technology,remote sensing of plant leaf water content can be achieved,which has more practical value.
microwavethermoacoustic imagingplant leaveswater distribution
万方数据
维普
