A Tendency Toward Further Advancement In Forest Digitalization Via Combined Sap Flow, Spectrometer, Soil, And Microclimate Data

Abstract

The science of forest digitalization via technological innovation offers an opportunity to develop new methods for mass monitoring forest resources. A key constraint has been cost restraints preventing the mobilization and collection of big data to efficiently capture, store, and analyze retrieved data. The Internet of Things (IoT) and advances in microprocessing are steadily changing this. The TreeTalker® is a multisensory IoT-driven platform designed to detect and collect information on individual trees, where its nested sensor approach captures several key ecophysiological parameters autonomously and in quasi-real time at a relatively low cost.Here we combine a new additional probe for the detection of soil parameters, mainly soil temperature and soil moisture. The aim of this study was to design a compatible soil probe with TreeTalker® platform with reasonable accuracy maintaining the principle of lower cost for mass monitoring. For this purpose, two surficial sensing frequency domain-based soil probes with 50 and 3000 kHz bands were designed and integrated into the TreeTalker® platform for real-time and continuous soil data collection. In order to demonstrate the capability of the new additional part, a three-phase experimental process was performed including (1) sensor sensitivity analysis, (2) sensor calibration using eight different soil types, (3) a survey on signal correlation with soil water content and soil matric potential and (4) long-term field data monitoring. A negative linear correlation was demonstrated under temperature sensitivity analysis for both types of probes, and for calibration, nonlinear regression analysis was applied to collected samples, explaining the relationship between the sample volumetric water content (collected by digital scale) and the sensor frequency output. Based on a preliminary trial, we investigate that frequency signal has a stronger correlation with soil matric potential (R2= 80%) rather than soil water content (R2= 62%) due to the sensitivity of the probe under free and bound water. This opens a new window for water potential measurement which is a key parameter for the understanding of Plant-Soil interactions. Furthermore, in a field scenario, three TreeTalkers were mounted near the commercial precise soil sensors, so-called TDR systems (time domain reflectometry) to analyze the accuracy of the low-cost soil probe in comparison to TDR system for both wet and dry seasons in silty-loamy soil type. The results revealed a better correlation for collected data in the wet season than in the dry period. We also present an innovative electrical impedance analysis for detecting soil water potential and soil water content.  system for both wet and dry seasons in silty-loamy soil type. The results revealed a better correlation for collected data in the wet season than in the dry period.