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Climate change and intensive agriculture are responsible for the increasing frequency and intensity of abiotic stresses generating conditions of water scarcity. Currently, there is the need to select and release, in a short time, plants adaptable to the current and future environmental conditions and resistant to biotic and/or abiotic stress. This study presents the design and validation of a High-Throughput Screening (HTS) system for the continuous and simultaneous monitoring of the plant stress response to drought in a semi-controlled environment.Structurally, the HTS-system is formed by three hardware segments to detect with high-frequency the agrometeorological variables (i.e., atmometry), the weights (i.e., gravimetry), and the soil water content (SWC) (i.e., time domain reflectometry, TDR) of sixteen pots in which the medicinal crop Salvia officinalis L (sage) was grown. Two irrigation treatments, one based on full irrigation and the second on soil water deficit conditions, were applied following a feedback control irrigation scheduling protocol, and an automated micro-irrigation system was designed to manage them.The system was able to model the sage water stress function following the root water uptake (RWU) macroscopic approach. The threshold of soil water status below which crop water stress occurred was also identified. The gravimetric-based daily evapotranspiration (ETc act) and the time domain reflectometry (TDR) -based RWU rates showed a high correlation, which allowed validating the RWU indicators based on soil moisture sensors to estimate the ETc act fluxes.Keywords. Agro-hydrological modelling, high-throughput systems; root water uptake; sage; water stress function

The EM-38 is a Handheld Electrical Magnetic Induction (EMI) device, non-invasive and commonly used for monitoring salinity, mapping bulk soil properties, and evaluating soil nutrient status. The measured data is an electrical conductivity, [mS/m], which was referred to a representative soil volume of 1.0-1.5 m depth and 2.0 m width.The Data AcQuisition (DAQ) system for EM-38 (Geonics Inc.) conductivity meter, used for recording the spatial variability of the soil bulk electrical conductivity (EC), is expensive, according to the proprietary software, and do not provide detailed, modifiable circuit schematics.To address these issues, we developed an easy-to-use, modifiable, and inexpensive data acquisition (DAQ) system for EC data recording and spatializing. In particular, this work investigates the feasibility of using a low-cost open-source DAQ system to be installed on an EM-38 conductivity meter (Geonics Inc.). This DAQ system is based on Raspberry Pi and allows collecting speed and position of the EM-38 device by carrying it on a specific designed sled system.The EM-38 data (± 200mV) were acquired by A/D converter 24 bit and GPS data ($GPGGA, $GPRMC [NMEA 0183]) were obtained by serial input RS232. The Data logger (Raspberry Pi 4) stored the acquired data and transferred it to the server using an internet connection (Router 4G). The control Firmware has been written in Python language. To ensure the accuracy and reliability of the collected data, the system has been evaluated and tested in well-known open-filed (CIRAAA-a reserch center of the University of Pisa), where the spatial variability of the main soil physical properties (i.e. soil texture, organic matter, electrical conductivity) are known.The performance has been evaluated by comparing the data string with the one generated by a professional DAQ system. The latter includes a CR1000 data logger (Campbell Scientific) to control and store the EC data and integrats a GPS receiver (GPS16X-HVS, Garmin Inc.) which provides the position, velocity, and timing information.First results allowed to approve the possibility to extract the analogical signal from the device, which is strongly responsive to the variation of the physical properties of the soil environment. Moreover, the device is able to estimate accurately the spatial patterns of the investigated soil physical properties. Keywords: Precision farming, Zoning, EMI sensors, soil bulk electrical conductivity, open source DAQ

In this work, we propose to transfer a soil moisture-based wireless sensor network (SM-WSN) to support the reduction of irrigation water consume in the Tuscany region (Italy). The SM-WSN was designed and validated in a commercial pear orchard during two growing seasons (2019-2020) in which the smart irrigation strategy was implemented and applied.Initially, the micro irrigation system was assessed based on its performance in terms of water distribution uniformity (DU) evaluated with field measurements of emitter flow rates. Then, a zoning analysis was carried out to divide the orchard into homogeneous areas according to the normalized difference vegetation index (NDVI) detected with unmanned aerial vehicle (UAV) and GIS tools. These areas were used to define the topology of the SM-WSN and to investigate how water distribution uniformity can affect the vigour of the trees. A total of 6 “drill & drop” capacitance probes (Sentek Pty Ltd, Stepney, Australia) were installed in the field, after following a simplified laboratory calibration procedure. The hardware and the smartphone-based application, AgriNET, used to download from remote the sensors’ readings were provided by Tuctronics (Walla Walla, Washington, USA).Assuming that the zoning outcome was only associated with the soil spatial variability, the effect of DU on the vigour of the trees has been identified. Moreover, unlike the ordinary irrigation scheduling applied in the farm, the smart system allowed maintaining the soil water content within a pre-defined optimal range, in which the upper and lower limits corresponded respectively to the soil field capacity and the threshold below which water stress occurs. Based on the smart irrigation management, a water-saving up to 50% of the total water supplied with ordinary scheduling was achieved during both the investigated growing seasons. Moreover, the quality of the productions (i.e °Brix, fruit size and firmness) were in line with the standard required by the farmer. The adoption of the new technology, aiming at identifying the most appropriate irrigation management, has the potential to generate positive economic returns and to reduce the environmental impacts.

New technologies in agriculture present the opportunity to create intuitive and user-friendly decision support systems, and to improve the productivity of the systems requiring water and energy. In the last few years, the adoption of these technologies have been increasing through third mission activities, and the collaboration between researchers, consultants, agri-food managers and farmers.The general objective of the proposed dissemination activity carried out by the AgrHySMo laboratory of the University of Pisa, was to transfer a soil moisture-based wireless sensor network (SM-WSN) to a commercial pear orchard named Illuminati Frutta (Arezzo, Italy), for the feedback control of irrigation.The plan of the third mission activity was designed by the following phases: i) the team evaluated the hydraulic performance and management of the irrigation system in the pear orchard; ii) the use of proximal sensing provided the NDVI for the biophysical characterization of the crop in a pilot area extended thirteen ha; iii) the open-source QGIS suite program was used to elaborate the collected images, to assess a zoning analysis, and to discretize homogeneous areas inside the orchard. These zoning maps were used to define the topology of the SM-WSN.The orchard was characterized by four homogeneous zones, inside which at least one sensor of soil water content (FDR Drill and Drop probe, Sentek Inc.) was installed. A total of 6 probes were installed in the pilot area. The hardware and the smartphone of the dedicated sensor network applications, AgriNET, were provided by Tuctronics (Walla Walla, Washington, USA). The measurements of volumetric soil water contents are sent to a platform using the MODBUS RTU protocol interfaced with a communication board and then delivered, using the cellular 3G data network, to a MySQL database operated by AgriNET/Tuctronics accessible from the web. According to the ordinary scheduling of irrigation, the expert system allowed the farmer to maintain the soil water content within a pre-defined optimal range, which upper limit corresponds to the soil field capacity and the lower is the threshold below which water stress occurs. During the first experimental growing season, by considering the results obtained in the pilot plot, compared with the ordinary irrigation scheduling the farmer saved up to 35% of the water and energy supply. In the future, the proposed feedback control of irrigation protocol will be extended to the entire farm. Thus, the adoption of this new technology aimed at identifying the most appropriate irrigation management, have the potential to generate positive economic returns and to reduce the environmental impacts.

Actual evapotranspiration from typical Mediterranean crops has been assessed in a Sicilian study area by using surface energy balance (SEB) and soil-water balance models. Both modelling approaches use remotely sensed data to estimate evapotranspiration fluxes in a spatially distributed way. The first approach exploits visible (VIS), near-infrared (NIR) and thermal (TIR) observations to solve the surface energy balance equation whereas the soil-water balance model uses only VIS-NIR data to detect the spatial variability of crop parameters. Considering that the study area is characterized by typical spatially sparse Mediterranean vegetation, i.e. olive, citrus and vineyards, alternating bare soil and canopy, we focused the attention on the main conceptual differences between one-source and two-sources energy balance models. Two different models have been tested: the widely used one-source SEBAL model, where soil and vegetation are considered as the sole source (mostly appropriate in the case of uniform vegetation coverage) and the two-sources TSEB model, where soil and vegetation components of the surface energy balance are treated separately. Actual evapotranspiration estimates by means of the two surface energy balance models have been compared vs. the outputs of the agro-hydrological SWAP model, which was applied in a spatially distributed way to simulate one-dimensional water flow in the soil-plant-atmosphere continuum. Remote sensing data in the VIS and NIR spectral ranges have been used to infer spatially distributed vegetation parameters needed to set up the upper boundary condition of SWAP. Actual evapotranspiration values obtained from the application of the soil water balance model SWAP have been considered as the reference to be used for energy balance models accuracy assessment. Airborne hyperspectral data acquired during a NERC (Natural Environment Research Council, UK) campaign in 2005 have been used. The results of this investigation seem to prove a slightly better agreement between SWAP and TSEB for some fields of the study area. Further investigations are programmed in order to confirm these indications.