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אלון ויין: Field Deployment and Evaluation of a Scalable Inductance-Based Dendrometer Network with Analytical Modeling of the Sensing Element Continuous monitoring of tree stem dimensions can provide valuable information on plant water status, growth, and response to environmental and irrigation conditions. Daily variations in stem diameter reflect the balance between water uptake, transpiration, and internal water storage [1], making dendrometric measurements a potentially useful tool for evaluating plant response to different irrigation regimes [2]. However, extending such measurements from individual trees to distributed field-scale monitoring requires sensing systems that are stable, scalable, and capable of operating simultaneously over long periods under agricultural conditions. This work investigates the establishment and field evaluation of a distributed inductance-based dendrometer system for monitoring stem-diameter dynamics in mango trees, building on the previously introduced all-electrical frequency-shift dendrometer [3]. The sensing approach is based on a variable inductive element installed around the tree stem, whose inductance changes as its geometry varies with stem expansion and contraction. An analytical model was developed to relate the geometry of the sensing element to its inductance and, consequently, to changes in stem dimensions, using established formulations for self and mutual inductance [4]. The model also provides a basis for simplified formulations suitable for practical implementation. A network of 12 dendrometer units was deployed on mango trees under field conditions at the Central and Northern Arava-Tamar R&D experimental site. The trees were subjected to three irrigation-water salinity treatments, enabling simultaneous comparison of stem-diameter dynamics under different irrigation conditions; dendrometric monitoring has previously been shown to capture mango stem responses to irrigation regime [5]. Long-term measurements were used to evaluate the stability and consistency of the sensing units, examine the influence of environmental conditions on the measured response, and extract physiological indicators describing daily stem contraction, recovery, and growth. The resulting data were further examined to assess whether differences in stem dynamics could be associated with the applied irrigation treatments. In addition to evaluating the sensing performance itself, the work examines the practical requirements of extending the system to multi-sensor agricultural deployments, including communication architecture, hardware complexity, and cost. In the talk, the analytical model, the distributed measurement architecture, the field deployment, and the recorded stem-diameter dynamics will be presented, with particular emphasis on the ability of the system to distinguish plant responses to different irrigation-water salinity treatments and on its potential for scalable agricultural monitoring. References [1] R. Zweifel, H. Item, and R. Häsler, “Link between diurnal stem radius changes and tree water relations,” Tree Physiology, vol. 21, nos. 12-13, pp. 869-877, 2001. doi: 10.1093/treephys/21.12-13.869. [2] M. F. Ortuño et al., “Could trunk diameter sensors be used in woody crops for irrigation scheduling? A review of current knowledge and future perspectives,” Agricultural Water Management, vol. 97, no. 1, pp. 1-11, 2010. doi: 10.1016/j.agwat.2009.09.008. [3] S. Haimovich, A. Vain, N. Lazarovitch, and M. Gal-Katziri, “An all-electrical dendrometer based on a frequency-shift sensor,” Smart Agricultural Technology, vol. 12, Art. no. 101356, 2025. doi: 10.1016/j.atech.2025.101356. [4] F. W. Grover, Inductance Calculations: Working Formulas and Tables. New York, NY, USA: D. Van Nostrand Company, 1946. [5] F. Hahn and J. A. García, “Mango Stem Response under Different Irrigation Regimes,” International Journal of Fruit Science, vol. 22, no. 1, pp. 35-56, 2022. doi: 10.1080/15538362.2021.1970080. אלון אלגרט: Dynamic Refocusing of a Flexible Phased Array via Shape Tracking This work demonstrates a dynamically self-correcting flexible phased array capable of maintaining stable beamforming performance during continuous mechanical deformation. The array integrates embedded strain-gauge curvature sensors and a multichannel ADC with a real-time reconstruction algorithm that estimates the array geometry, calculates the required phase corrections, and continuously updates the phase of each antenna element. The reconstructed array shape and resulting beamforming performance show good agreement with image-based shape estimation. In dynamic experiments, uncompensated deformation produces received-power variations and deep fades approaching −23 dB, whereas the proposed tracking and correction system maintains the received power within approximately ±1.5 dB throughout the motion, while operating at a 26 Hz correction rate. These results demonstrate real-time beam stabilization of a flexible phased array under continuous deformation, extending previous approaches that were primarily demonstrated under static or quasi-static conditions. שלומי אבידן: A Novel Low-Cost Soil Moisture Sensing Technique Low-cost measurement of soil water content is needed for irrigation scheduling and environmental monitoring, but accurate commercial instruments remain expensive for dense deployment. This report characterizes a capacitive water-volume-fraction sensor built around a dual-frequency excitation scheme: a 100 kHz signal, at which the resistive component of the load dominates, and a 42 MHz signal, at which the capacitive component dominates, so that resistance and capacitance are estimated separately from two peak-detector channels. An on-device 4-point linearization calibration corrects the detector nonlinearity. Four experiments validate the architecture. Bench characterization against reference loads defines a validity region (R ≥ 1.5 kΩ, C ≤ 12 pF) with mean absolute errors of 1.9% in R and 0.59% in C, and a maximum water-volume-fraction error of 0.37 vol% after Topp conversion. The capacitance response to water mass is linear (pooled R2 = 0.981, mean sensitivity 145 fF/g), salinity is tolerated to roughly 1000 ppm, and in a soil dry-down, sensor-derived permittivity and water-volume fraction (via the Topp equation) agree with a commercial HydraProbe with R2 = 0.99 during the dry-out phase, all at a bill of materials of about 10 USD

תחילת שנת הלימודים האקדמית תשפ"ז 2026-2027