Ag-IoT application for Vital Monitoring of Plant Ecophysiological Data and Soil Parameters

Ag-IoT systems enable a data pipeline for modern agricultural production. Using Ag-IoT technologies, growers can make better management decisions by leveraging the real-time field data while researchers could utilize these data to answer key scientific questions. Here, we designed a flexible microprocessor-based platform, called TreeTalker, to monitor in real-time plant sap flow rate via thermal approaches. TreeTalker has an onboard spectrometer to collect data in near infrared and visible areas using 12 bands from 450 to 860 nm. Moreover, TreeTalker collects microclimate data (air temperature and air relative humidity) as well as soil moisture and temperature measurement. Sap flow and soil moisture measurements are the main tools to understand the plant water demand for precision irrigation and water-energy efficiency. In this study, 9 TreeTalker units are mounted on Soreli Kiwifruit trees in the Lazio region, Italy. The site is divided into three clusters with different irrigation regimes, 100, 80 and 60 %, respectively. The first objective of this study was to apply new algorithms for sap flow measurement considering the heating and cooling phases of the heat flow curve at the same time and secondly, a compare of phenological and ecohydrological trends of trees under full and deficit irrigation systems. Data captured was used to analyze the correlation between fruit quality, productivity, health, and fertility of trees with ecophysiological parameters under different irrigation systems. The result of continuous monitoring for one growing season in 2022 revealed that sap flow function based on cooling phase data has higher accuracy than heating phase due to independency to the zero-flux condition as well as semi-theoretical flow index. Given sap flow results, plants with the full irrigation system have ∼ 1.3 to 3 times greater sap flow rate than plants with deficit irrigation regimes. Kiwi peak water demand occurred in July coinciding with max VPD confirming maximum sap flow rates between each irrigation regime. A variation between the 80% and 60% irrigation regimes, ∼ 4 to 15 %, is linked to slight differences in sap flow rates and is most prominent in the early part of the growing season. Considering fruit quality data, kiwifruit trees with full irrigation showed lower acidity, and higher Vitamin C concentration while sugar concentrations were noticeably lower. Our results suggest that the 80% irrigation schedule achieves the optimum water energy efficiency as well as reaching optimum fruit quality conditions. This finding requires validation via continued monitoring over successive seasons and irrigation regimes. The revolution in the Internet of trees offers a promising new big data solution for assessing optimal conditions for fruit tree agricultural production considering future and potential water scarcity scenarios.