Continuous and stable oxygen supply is very necessary for plant tissues to maintain their normal metabolism. The evaluation of oxygen environment in the root zone can also serve to assess whether or not trees and plants are experiencing hypoxic stress. Research on detection and analysis technology is of great significance for the development of agroforestry and the environmental conservation. This study aims to summary the detection and analysis strategies of soil oxygen distribution. The current technologies were also reviewed to obtain the spatial and temporal distribution of soil oxygen in the root zone, such as the fluorescence imaging, the oxygen sensor point detection, and the soil oxygen diffusion analysis. The future directions were clarified on the root zone soil oxygen detection. The buried oxygen sensor was utilized to monitor the oxygen environment in the soil. Three categories of detection were divided: the zirconia, the electrochemical approach, and the fiber optic sensing. It is difficult to capture the oxygen content of the entire root zone, leading to disrupt the structure of the soil and then cause harm to the root system of the plant. However, the high level of accuracy was obtained for the detection of oxygen concentrations and time resolution. It is possible to acquire the soil oxygen concentration gradient in a short amount of time by modelling soil oxygen diffusion. According to the physical and chemical features of the soil, the gradient can also be obtained to estimate the soil oxygen environment where the plant roots are located. The structure and parameters of the model were closely connected to the chemical and physical characteristics of the soil. It is very necessary to modify the model suitable for the specific situation using the reliable input data from the soil sampling spots. The fluorescence in-situ imaging approach can be used to acquire the real-time distribution of the oxygen concentration in the soil rhizosphere. The non-invasive monitoring can also be employed to uncover the interactions that occur between organisms and the environment in the similar natural conditions. The procedure can be carried out in a laboratory setting to predict the field. The latest advances were compared under the different applicable scenarios in the field of oxygen sensors combined with various types of oxygen transport models. The hot topics and development directions were finally summarized on the detection techniques and models of soil oxygen distribution in the root zone: 1) Oxygen sensors can be the promising trend of miniaturization and integration, and the new types of materials can also be introduced to improve the sensitivity and durability of the oxygen sensors; 2) The accuracy of the models can be continuously improved to consider the multi-scale and multi-factor interactions under the complex soil oxygen environment in the root zone; 3) Sustainable fluorescent dyes can be developed to improve the resolution and depth of fluorescence imaging for the clear imaging of smaller and deeper structures; 4) The water-oxygen relationship can be further analyzed in the plant transpiration. The physiological adaptive capacity of plants can be used to reflect the oxygen environment in the root zone using the oxygen concentration in the xylem. The finding can provide a strong reference for the soil oxygen environment in the root zone of plants.

Tree trunks with thick bark can be expected to serve as the potential water storage capacity. Moisture content is one of the most important indicators to monitor the physiological condition of tree trunks in the development of agriculture and forestry. Therefore, it is crucial to accurately obtain the thickness and relative dielectric constant of the layered medium in tree trunks. The growth and health status of trees can be evaluated to optimize the water management strategies. To this end, this study aims to invert the dielectric parameters of tree trunk layered structure using radar detection. Non-invasive detection was realized for the internal structure of tree trunk. The electrical characteristics of different layers were obtained for the medium layers in the tree trunk. According to Snell's law, the physiological structure of tree trunks were combined to construct the propagation model of radar signals in the layered structure of tree trunks. Electromagnetic properties of different media layers in tree trunks were considered, such as the thickness and relative dielectric constant differences of bark, sapwood, and heartwood. These key parameters were then evaluated using radar echo signals. In addition, the accurate inversion was also performed on the dielectric parameters of tree trunks using sparse decomposition. K-SVD dictionary training was combined to process and analyze radar signals. A software defined radio (SDR) platform was used to build a tree trunk detection radar system in the experiment. The accuracy of detection was further improved to easily adjust the operating frequency of the radar, and then modify the signal processing under different environments. Layer stripping algorithm was selected to invert the dielectric constant and thickness of the layered structure in the tree trunks. The echo signals detected by radar were collected to evaluate the performance of the improved model. A comparative experiments were conducted on the radar detection under two conditions: aliasing and no aliasing in the echo signal. In the absence of aliasing, the inversion errors of the relative dielectric constant and layer thickness of the tree trunk were within 2.93% and 3.5%, respectively; In the case of echo aliasing, the inversion errors of relative dielectric constant and thickness were 7.52% and 7.61%, respectively. The experimental results show that the robustness and practicality were achieved to accurately estimate the thickness and relative dielectric constant of the layered medium in tree trunks under different signal environments. Application prospects were also offered to promote the plant physiology. The finding can provide the accurate data support to monitor the tree health status. Effective technical references can also be provided to promote the garden management and water control in the sustainable agriculture and forestry.

The oxygen content in the soil of tree root zones is a crucial environmental factor influencing the growth of trees. The study aimed to develop a novel sensor system for monitoring oxygen content in tree xylem and sap flow velocity, with the goal of investigating the relationship between oxygen levels in the root zone soil and those in the water transfer pathway. This research sought to address the limitations of direct soil oxygen measurements, which are often hindered by the complex spatial distribution of oxygen. By leveraging the dynamics of water movement within trees, the study provided a technical foundation for optimizing tree growth environments and enhancing water-oxygen management. A composite sensor was developed based on fluorescence quenching and thermal diffusion sap flow measurement principles to simultaneously detect oxygen content in tree xylem and sap flow velocity. Calibration experiments were conducted to ensure accuracy, with temperature correction applied to minimize environmental interference. The sensor's performance was evaluated through outdoor comparative tests against commercial fiber-optic oxygen sensors and sap flow sensors. Data from the sensor were integrated with micrometeorological parameters and analyzed using a tree water uptake model and a root-soil oxygen diffusion model to derive oxygen distribution patterns at different root depths. The calibration results demonstrated the sensor's high precision, with relative errors of less than 1.4% for oxygen content measurements below 30% and less than 5% for sap flow velocity. Outdoor comparative tests further validated the sensor's performance, showing strong correlations with commercial sensors. The correlation coefficients were 0.947 for oxygen content and 0.958 for sap flow velocity, confirming the sensor's reliability and accuracy. The integration of sensor data with micrometeorological parameters, such as temperature and humidity, enabled the derivation of oxygen distribution patterns at various root depths. The analysis revealed that oxygen content decreased with increasing root depth, reflecting the challenges of oxygen diffusion in denser soil layers. For example, oxygen levels in the upper root zone were significantly higher than those in deeper layers, highlighting the impact of soil structure on oxygen availability. The sensor system also captured temporal variations in oxygen content, showing fluctuations corresponding to changes in soil moisture and temperature. These findings provided detailed insights into the dynamic interplay between soil oxygen availability and tree physiological processes. By linking oxygen levels in the root zone to those in the water transfer pathway, the study demonstrated the sensor's ability to monitor root zone oxygen environments effectively. This capability is crucial for understanding how oxygen availability influences tree growth and health, particularly in environments where soil oxygen is a limiting factor. The results also underscored the potential of the sensor for large-scale applications, such as forest ecosystem monitoring and precision agriculture, where real-time data on water and oxygen dynamics can inform management decisions. Overall, the study highlighted the sensor's potential as a reliable tool for advancing research on tree physiology and optimizing growth environments. The study successfully developed and validated a composite sensor system for monitoring oxygen content and sap flow velocity in tree xylem, providing a reliable tool to investigate root zone oxygen dynamics. By linking oxygen levels in the root zone to those in the water transfer pathway, the research offers a scientific basis for optimizing tree growth environments and improving water-oxygen management. The findings highlight the sensor's potential for dynamic monitoring of root zone oxygen, enhancing tree health and productivity. This advancement addresses the limitations of traditional soil oxygen measurement methods and opens new research avenues into water-oxygen interactions in tree physiology. Future applications include forest ecosystem monitoring, precision agriculture, and urban tree management, supporting sustainable environmental practices.