Introduction
In the soil-plant-atmosphere continuum (SPAC), water movement is driven by the water potential gradients between the soil (Ψsoil), the plants (e.g. Ψleaf) and the atmosphere (Ψatm). The fundamental mechanism underlying this phenomenon in vascular plants, as depicted by the cohesion-tension theory (Bohm, 1893; Dixon & Joly, 1895), is the transpiration pull. This force in turn generates a negative pressure potential (Ψp) in xylem vessels. When water flows across non-selective tissues, such as cell walls and plasmodesmata, it follows the “downhill” gradients of summed Ψp and gravitational potential (Ψg) (i.e. from high to low potential). When water flows across a semi-permeable membrane, such as cell plasma membranes, a third additive component comes into play: the osmotic potential (Ψo). This component, which is a negative pressure, favors water flow towards the side with the highest solute concentration. At the root cylinder scale, radial water flow rate per unit root surface area (J [LT −1]) is generally described by the Fiscus (1975) equation, describing the root as a single “big membrane”. This equation assumes radial water flow rate to be the difference between the soil-root interface and xylem vessels “total” water potential (Ψtot [ML−1 T−2], expressed in units of pressure), multiplied by the root hydraulic conductivity (Lpr [L2 M−1 T]), (Fiscus, 1975):
where the degree of selectivity of the tissues on the radial pathway comes into play as a dimensionless reflection coefficient (σ
r, null when nonselective, one when fully selective) in the calculation of Ψ
tot:
Note that for simplicity, the notation Ψp is used for both pressure and matric potentials in the soil. Negative Ψ
p,soil expresses the pressure needed to counteract forces retaining water in the unsaturated soil matrix. Additionally, it will be assumed herein that frictional pressure drop along xylem vessels are negligible for the small plants of this study, and xylem water potential in the root and leaf are equivalent. As a support, Venturas et al. (2017) summarized that frictional pressure drops 1~2 MPa in trees under wet soil and dry air conditions, while this pressure drop is smaller in herbs under a shorter transport distance.
Ψleaf (herein may refer to water pressure potential or total water potential according to the method of quantification) is a central physiological variable that reflects the water status of plants, and influences critical processes such as photosynthesis, transpiration, and growth (De Swaef et al., 2022). Ψleaf acts as a primary indicator of plant hydration, offering insights into plant responses to environmental stresses, including drought (very negative Ψ
p,soil), salinity, and extreme temperatures etc. Understanding the concept of both Ψleaf and Ψsoil is essential for research efforts in plant water relations, drought resistance, and agricultural irrigation management (Shackel, 2011). Over the past century, the methods for measuring Ψleaf and Ψsoil have evolved significantly, driven by advancements in technology, materials science, and our understanding of soil-plant-water relations (Ding et al., 2020). This evolution has transformed the field of plant physiology and soil physics, enabling more accurate, efficient, and non-invasive monitoring of plant and soil water status.
In the early stages of research, Ψleaf was primarily measured or estimated by visual assessment (such as leaf wilting) and gravimetric techniques (measurement of water loss) (Veihmeyer & Hendrickson, 1927). In the 1950s and 1960s, direct measurements of Ψleaf were achieved by using thermocouple psychrometers (TCP), which typically measure the sum of Ψp and Ψo (Boyer & Knipling, 1965; Richards & Ogata, 1958). Concurrently, the Scholander pressure chamber proposed a direct but destructive measurement of (Ψleaf) (Scholander et al., 1965). Whether this technique measures Ψtot or Ψp remains a matter of debate (Boyer, 1969; Rodriguez-Dominguez et al., 2022). The method assumes that equilibrium is reached between the applied balancing pressure and the negative water potential in the leaf xylem, while the osmotic potential of the xylem/apoplastic sap is negligible (Boyer, 1969). However, this assumption may not always hold, as differences among measurement techniques and the presence of non-negligible xylem osmotic potential under certain physiological or environmental conditions can influence the interpretation of pressure chamber measurements (Rodriguez-Dominguez et al., 2022; Enns et al., 2000; Westhoff et al., 2008). Later, plant physiologists devoted much effort to develop new techniques for the measure of Ψleaf with Dew Point Hygrometry (Banks & Hirons, 2019; Brown & Tanner, 1981). Modern approaches now include infrared thermography (Cohen et al., 2005), microtensiometers (Pagay et al., 2014), optical and spectral methods (Cotrozzi et al., 2017; Wang et al., 2020), and nanosensors (Jain et al., 2021), allowing for continuous, in situ, and highly sensitive monitoring of plant water status. In the context of in-situ
continuous monitoring of Ψstem/leaf, TCP (Bellasio et al., 2024; Delval et al., 2024; Haverroth et al., 2025; Jerszurki et al., 2017) and microtensiometers (Bellasio et al., 2024; Christenson et al., 2024; Delval et al., 2024; Haverroth et al., 2025; Villalobos et al., 2024) have been predominantly utilized in recent years. The microtensiometer is restricted in its application to woody stems; whereas, the TCP can be utilized on both stems and leaves.
Ψsoil measurement techniques have also evolved from qualitative assessments to high-precision digital sensors (Bittelli, 2010; Singh et al., 2024; Yao et al., 2025; Yu et al., 2021). Most of the techniques rely on the measurement of the hydraulic equilibrium between soil water and external substances, i.e., solid, liquid and gas (Campbell & Campbell, 2005; Luo et al., 2022). The techniques are clarified into three main categories, which include solid-based (e.g., filter paper) (Al-Khafaf & Hanks, 1974; Gardner, 1937), liquid-based (e.g., tensiometer) (Cassel & Klute, 1986), and vapor-based (e.g., hygrometer) (Campbell & Campbell, 1974). In field, the most commonly used instruments include piezometers, tensiometers, heat dissipation sensors, dielectric sensors, and TCP. In the laboratory, methods include soil water retention, suction plates, pressure plates apparatus, dew point method, and freezing apparatus (Bittelli, 2010).
This protocol paper will provide a step-by-step guide for using PSY1 and Teros 21 sensors for in situ, continuous measurements of Ψleaf (including pressure potential and osmotic potential) and Ψsoil (soil matric potential), respectively, on maize and tomato plants. The PSY1 psychrometer (ICT International, Armidale, Australia) was selected for this study due to its capacity to measure leaf/stem water potential in situ and with a high degree of continuity (at 10-minute intervals). The installation process for crop plants is also straightforward. Teros 21 (Meter group, Washington, United States) is a digital sensor that uses dielectric permittivity changes to estimate matric potential in soil. It works from wet to extremely dry soils, with a detection range of 0 to −100000 kPa and a high precision of 0.1 kPa. Based on these features, we selected Teros 21 for soil water potential measurement in this study. As demonstrated in
Table 1, a physical interpretation and comparability of Teros 21 and PSY1 measurements was established. Although PSY1 measurements are influenced by soil water availability, as reflected by the soil matric potential measured with TEROS 21, the absolute values of leaf water potential and soil matric potential should not be directly equated because they differ in temporal dynamics and magnitude along the soil–plant hydraulic continuum. Instead, the two measurements provide complementary information and should be interpreted together to characterize plant and soil water status.
|
Sensor | Quantity reported | Physical meaning | Remarks |
|---|
| Teros 21 | Soil matric potential | Teros 21 measures the dielectric permittivity of a solid matrix (porous ceramic discs) to determine its water potential. There is hydraulic equilibrium between the ceramic discs and surrounding soil. So, Teros 21 requires good hydraulic contact with the surrounding soil for accurate measurements. | In salty and dry soils, soil osmotic potential becomes non-negligible, and we need to take the sum of osmotic and matric potential to estimate soil total water potential. |
| PSY1 | Leaf/Xylem total water potential | PSY1 measures the vapor pressure in the chamber attached to the water conducting tissue of the plant. It relies on the fact that the liquid phase water in the xylem sets up a vapor pressure equilibrium with the chamber. | It reads both pressure potential and osmotic potential in the measured tissues under thermal and vapor equilibrium between chamber and leaf/xylem, stable temperature, proper installation, no condensation. |
Additionally, we present user-friendly codes for the analysis and cleaning (e.g. remove outliers and irrelevant values) of the collected data in RStudio.
Experimental protocols
Seeds germination and plant growth
Seed resources: Zea mays L. (in this example, B104 inbred maize line from previous study (Ding et al., 2020), referred to as maize later) or S. lycopersicum var. Moneymaker (referred to as tomato later, purchased from the market, “Oh! Green”, Belgium, originated from Vilmorin (product number 784)). The accession number for B104 maize is “PI 594047” from the USDA National Plant Germplasm System. The plant passport for tomato seeds is “A Solanum lycopersicum L. B FR-RH00867”.
Timing: maize, four weeks; tomato, six weeks.
1. Sterilization and germination of seeds
a. Prepare 50 mL of 1/5-strength bleach solution by mixing 10 mL of commercially available bleach (LODA, Bleach 15°, 1815B) with 40 mL demineralized water in a 50 mL falcon tube.
b. Add maize or tomato seeds to the bleach solution for 5 min. Discard the solution and wash five times with demineralized water.
Note: To avoid losing the seeds, especially for tomato seeds, a nylon mesh may be used to cover the falcon tube when discarding the bleach solution or water.
c. In a Petri dish, prepare a “Sandwich” consisting of two ‘layers’ of absorbent paper saturated with water, one on the top and bottom respectively (
Figure 1C–G). Place the seeds with tweezers on the bottom layer and cover them with the other layer of paper, to form the “Sandwich”. Close and wrap the Petri dish with aluminum foil and let it stand vertically at 25~30°C in a climate chamber, growth chamber or oven. Typically, the seeds will germinate after 48 h, at 25~30°C for both maize and tomato. If maize seeds were to be kept in these conditions for more than 48 h, the roots would risk being too long making them difficult to transfer to the soil media in the next step. Instead of using the “Sandwich” technique, the seeds may be directly sown in the soil after the sterilization for germination in greenhouse or growth chamber according to the protocol for transplanting (
Figure 2A–C).
Figure 1. Sterilization and germination of maize seeds.
A, Prepare maize seeds. B, Sterilize seeds. C, Prepare the “Sandwich” germination system. D, Saturate the paper with demineralized water. E, Place seeds on the paper. F, Assemble the “Sandwich”. G, Side view of the “Sandwich”. H, Wrap the “Sandwich” with aluminum foil for dark conditions. I and J, Germinate the seeds at 25~30°C in a growth chamber.
Figure 2. Transplanting and repotting processes.
A-F, maize. A, prepare small pots filled with soil. B, transfer the germinated seeds into the pot. C-D
, water the plants and grow them in greenhouse. E, transfer the maize seedlings to larger pots (diameter: 15 cm, height: 15 cm) after two weeks. F, grow plants in greenhouse. G-L
, tomato. G, tomato seeds after two days germination at 27°C. H, prepare a big tray and fill it will soil. I, cover the tray with glass to keep moisture of the soil. J, remove the glass after 3–4 days. K, re-pot the seedling into a larger pot (diameter: 6 cm*6 cm*6 cm [L*W*H]) after 2 weeks. L, re-pot the seedling into a larger pot (diameter: 15 cm, height: 15 cm) after 2 weeks.
2. Transplanting, repotting and growing the plants in greenhouse
The plants were grown in the greenhouse of SEFY at UCLouvain (https://www.uclouvain.be/en/technology-platforms/plant-cultivation-facilities-sefy
). During the experiment periods, the humidity was 50%~70%; the temperature was 21–26°C; and the artificial light intensity was 160~170 μmol.m−2.s−1 at table level. For more information about the greenhouse, please visit the SEFY website.
Maize
a. Prepare pots (e.g. 6 × 6 × 6 cm [L× W× H] with drainage holes at the bottom) and fill them with soil. This experiment used seedling & cuttings potting soil (https://dcm-info.be/fr/pro, DCM, product 1004525), ensuring good water distribution, drainage and allowing the soil to retain its aerated structure (
Figure 2A).
b. If the “Sandwich” technique was used, dig a hole in the soil according to the length of the maize roots and transfer the germinated seeds into the soil (one seed in each pot) (
Figure 2B). Cover the seeds with ~1 cm soil and try to delicately cover the coleoptile (i.e. emerging organ that will give rise to the shoot).
In the case of direct sowing, seeds are placed at a depth of approximately 1 cm in the soil.
c. Place the pots in a tray and add tap water/rainwater to the tray to allow for water uptake by capillary action (
Figure 2C–D). In this study, rainwater was utilized, as it is employed in the greenhouse facility. Water the plants regularly to keep the soil moist by the same method.
d. After two weeks, repot the plants into a larger pot (diameter: 15 cm, height: 15 cm) with a new type of potting soil (for example: https://dcm-info.be/fr/pro, product 1002381) (
Figure 2–F). This type of soil should have a high-water holding capacity. Keep watering regularly, around two to three times a week. At each time, we stopped watering until water drained from the bottom of pots for control treatment. For stress treatment, plants were stopped watering and rewatered according to the experiments. Note: At this step, Teros 21 sensors were installed in the pots to monitor soil matric potential (Please refer to the Ψsoil measurement protocol).
e. After another two weeks, the plants are ready for the installation of PSY-1 leaf psychrometers, detailed in a subsequent section.
Tomato
a. Prepare a plastic tray (e.g. 38 × 25 × 6 cm [L× W× H]) with drainage holes at the bottom, and fill it with a seedling & cuttings potting soil (
Figure 2H).
b. Transfer the germinated seeds (
Figure 2G) to the top of the soil (plant spacing ~3–4 cm, row spacing ~3–4 cm) and cover the seeds with ~0.5 cm of soil.
c. Water the soil until water drainage is seen from the bottom of the tray and cover the tray with glass to reduce the evaporation (remove it after one week) (
Figure 2I–J).
d. After two weeks, repot each plant into a larger pot (e.g. 6 × 6 × 6 cm (L× W× H) with seedling & cuttings potting soil (
Figure 2K). Keep watering regularly, around two to three times a week.
e. After two weeks, repot the plants into a larger pot (diameter: 15 cm, height: 15 cm) with potting soil (https://dcm-info.be/fr/pro, DCM, product 1002381) (
Figure 2L). Keep watering regularly, around two to three times a week. Note: At this step, Teros 21 sensors were installed in the pots to monitor soil water conditions (Please refer to the Ψsoil measurement protocol). Note: Repotting should be performed as appropriate for the experimental objectives and plant growth stage. Experiments investigating root architecture or other root traits may require different establishment protocols to minimize disturbance.
f. After another two weeks, the plants are ready for the installation of PSY-1 leaf psychrometers, detailed in the next section.
Soil and leaf water potential measurements
1. Soil water potential (Ψ
soil
)
Timing: 30~60 minutes for the installation. The duration of the measurements will depend on the experiments.
Teros 21 is factory calibrated at 0 kPa, 0~−100 kPa (four points) and −100000 kPa. When soil matric potential < −100 kPa, Teros 21 relies on the linear relationship between the logarithm of water content and the logarithm of water potential. No calibration will be needed prior to use. However, additional considering will be required to use Teros 21 when, 1) measuring in frozen soils; 2) measuring in high salinity; 3) temperature sensitivity at matric potential less than about −500 kPa.
a. Prepare the materials (
Figure 3A): Data logger (CR800, Campbell Scientific, Logan, Utah, United states), Teros 21 (Meter group, Washington, United States), RS232_USB cable, 12 V battery (Y7–12, Yuasa), isolation box.
b. Transfer the plant to the pot (
Figure 3B), as explained in the protocol for transplanting and repotting (maize, step “d”; tomato, step “e”).
c. To favor the contact between the sensor and the soil, cover Teros 21 with moist soil by gently pressing soil around the sensor (
Figure 3C-D).
d. Make a hole in the soil, put the sensor in the pot (away from the pot wall and install horizontally) and fill the pot with soil (
Figure 3E-F). Keep the plants in the greenhouse for further growth before the installation of PSY1 (see the protocols for the installation of PSY1).
e. Connect the Teros 21 sensors with a CR800 in an isolation box (
Figure 3G-L). In this study, we used “C1” and “C3” ports from SDM channel (
Figure 4). In each port, it is possible to connect a maximum of 10 Teros 21 sensors with different addresses. Splitter were used for multiple connections of Teros 21 to one port (
Figure 3I and K).
Note: To check and change the address number for each sensor, connect an individual Teros 21 sensor to CR800 (
Figure 5), then follow the protocol from Campbell Scientific (https://s.campbellsci.com/documents/us/technical-papers/sdi12-troubleshooting.pdf).
f. On a computer, write a program for the data logger with a programming tool (in this study, “CRBasic Editor” from Campbell Scientific was used, https://help.campbellsci.com/crbasic/cr1000x/). CR800 needs a program to send an operation to the Teros 21, read the SDI-12 bus communication protocol received by the Teros 21, and store the data. In this program, key information that will be sent and received by the SDI-12 signal, needs to be specified, i.e. (1) the address of each Teros 21; (2) the data transporting port (“C1” or “C3”); (3) the creation of dataset files to store the recorded soil matric potential and temperature, as well as the voltage of the battery for power supply; (4) the time interval for the data recording.
An example of the program was deposited on Zenodo (https://doi.org/10.5281/zenodo.17158115), with the document name of “Program-CR800”). Before starting, install the software of “Device Configuration Utility” and “PC400” from Campbell Scientific (https://www.campbellsci.com/devconfig; https://www.campbellsci.com/pc400). “CRBasic Editor” is integrated inside PC400. For more details about the programming, please refer to https://www.campbellsci.eu/videos/datalogger-programming?slid=101#slide=99.
g. Flash the program to the CR800. Firstly, connect CR800 with power supply (either a 12 V battery or a 12 V adapter socket directly plugged from the wall (220–240 V)). Then, connect CR800 with computer by RS232_USB cable. In this study, “Device Configuration Utility” was used to interact with CR800, which includes sending the program, identifying Teros 21 address, and downloading the data.
Note: For more details of how to use “Device Configuration Utility”, please refer to the protocols from Campbell Scientific (
https://www.campbellsci.com/devconfig
).
h. During the next day or after few hours of the installation, download the data from CR800 with “Device Configuration Utility” software to validate if all the sensors are working properly.
Note: For more details of how to use Teros 21, please also read the user manual from meter group (
https://metergroup.com/products/teros-21/teros-21-support/
).
Figure 3. Installation of Teros21 in the pots.
A, Materials for the installation of Teros 21. B-F, the installation of Teros 21 during repotting at section 2 (maize, steps d; tomato, steps e.) G-L, the connection between Teros 21 and data logger CR800.
Figure 4. The data transporting ports between Teros21 and CR800.
Figure 5. The connection of Teros21 and CR800 for checking and changing the address of the sensor.
2. Leaf water potential (Ψ
leaf)
Duration: ~5 minutes per installation. The duration of the measures will depend on the experiments. However,one installation could generate reliable data for one to two weeks for maize and tomato. After this period, the installed area of the leaf will be in senescence and non-functional for water transport, so a new installation will be required to change the position on the leaves. An additional explicative video for the psychrometer installation on leaves is available on Zenodo (Degand et al., 2025).
Note: PSY1 must be calibrated prior to first use or before installing in a new condition to guarantee accurate results. It is recommended to calibrate the instrument at or near the temperature at which it will normally be used. The calibration includes making measurements with calibration solutions of 0.1 M, 0.2 M, 0.3 M, 0.4 M,0.5 M, 1 M, 1.2 M NaCl on paper disk loaded to lid, to plot the data, generating a slope and an intercept that can be stored to calculate corrected water potentials in the ICT international software. After calibration, a good practice is to test that calibration with a 1 M NaCl solution that should give a value around −4.64 MPa after equilibration time (30 min to 2 hours). For other details of calibration, please check the manual from ICT international (https://ictinternational.com/wp-content/uploads/2023/08/PSY1-Manual-DOC-00087v2.pdf).
a. Prepare the materials (
Figure 6A): PSY1-leaf psychrometer (head and data logger, ICT international, Armidale, Australia), leaf clamps (PSY1-Leaf Psychrometer Clamps, ICT international, Armidale, Australia), retort stand, grease (Bardahl 1688 Silicone Grease, Bardahl, France), sandpaper (P400, grit size ~35 μm), demineralized water, precision wipes (Kimberly-Clark).
b. Choose newly expanded leaf for maize and fully expanded leaf for tomato (blue arrows in
Figure 6B).
c. Set up the retort stand (with the leaf chamber attached) beside the selected leaf. The leaf should be able to rest freely inside the leaf chamber without being bent.
d. Put the selected leaf inside the leaf clamp and use a marker pen to mark the position on each side of the leaf (
Figure 6C).
e. Remove the leaf from the chamber, take a piece of sandpaper (~1 cm2), lightly wet the sandpaper with a few drops of demineralized water for lubrication, and use the sandpaper to abrade the marked region on the abaxial side of the leaf (
Figure 6D). This abrasion will remove the cuticle on the surface of the leaf, in turn reducing cuticle resistance and improving water vapor diffusion in leaves. By removing cuticles, it will also reduce the equilibration time of leaf and psychrometer chamber. Ideally, the abrasion should just remove the cuticles without damaging the epidermal cells. It is recommended by the training from ICT international company to use a grit size of P400 for thick cuticles, such as citrus, a grit size of P600 for grasses, and a grit size of P800 for thin cuticles, such as beans.
f. Clean the abrasion region with demineralized water and dry it with tissue paper. Put the leaf back into the leaf clamp.
g. Take one PSY1-leaf psychrometer and put silicone grease around the edge of the cylindrical face. Spread the grease to have a ~0.5 mm layer of grease. This can be done either with a finger, or by placing the psychrometer lid back onto the chamber and turning slightly (remove lid after this action).
h. Put the psychrometer into the leaf clamp and fix it with the screw (
Figure 6E).
Note: In this study, the psychrometer was used in the greenhouse, with no thermal insulation around the leaf clamp. In a separate experiment, it was found that the measurements of PSY1-leaf showed similar water potential values between insulated and non-insulated treatments in the greenhouse. However, limiting temperature gradients and maintaining constant instrument temperature are two highly desirable factors in the reliability of the measurements. In the field, insulating the chamber creates a thermal buffer zone to avoid rapid temperature change during the measurement. This insulation is not intended to prevent the diurnal temperature change but rather serves as a way to avoid condensation in the chamber, which would compromise the measurement. (For more details of the insulation, please refer to the manual from ICT international, https://ictinternational.com/wp-content/uploads/2023/08/PSY1-Manual-DOC-00087v2.pdf).
i. Connect the data logger of the psychrometer to a computer to configure the settings by following the instructions from ICT international. In this study, data was recorded every 15 minutes, with a cooling time of 10 seconds, waiting time of 6 seconds, warming duration of 0 seconds, waiting time before measurement of 15 seconds, and chamber heating of 0 seconds. However, these settings can be changed according to the experiment by following the instructions from ICT international (see “0” error section).
Note: Installation of the ICT international software is required to connect psychrometers (Combined Instrument Software, ICT international, https://ictinternational.com/product/psy1-psychrometer-for-plant-water-potential/). Please follow the protocols given by ICT international to install the software and connect the PSY1-leaf sensors to a computer.
j. After allowing the leaf to equilibrate (typically between 30 minutes and 2 hours), the next step is to download and review the Ψleaf data. It is also good practice to check the data again about 24 hours after installation to confirm that a normal day–night pattern is observed. To retrieve the Ψleaf data, you can either connect the PSY1 leaf data logger directly to a computer using the dedicated software or remove the memory card from the logger and read it on a computer. If the installation was not done properly, the PSY1 may need to be reinstalled. Signs of improper installation often appear clearly in the data. For example, a typical dataset should show a diurnal pattern, with Ψleaf decreasing during the day as transpiration increases and recovering during the night. If this pattern is absent, or if the data consistently shows values close to “0”, it likely indicates an issue with the installation.
Figure 6. Installation of PSY1-Leaf on maize leaves.
A, Materials needed for the installation. B, leaves selected for the measurement in maize and tomato. C, select the region for the installation. D, leaf after the abrasion with sandpaper. E, fix the head in the leaf clamp.
The “0” recording can be induced due to the abrasion technique, or due to a bending of the thermal couple, which might lead to a loss of contact with the leaf. In this case, check the thermocouple under a microscope and adjust the position if necessary, by following the protocols from ICT international (https://www.youtube.com/watch?v=kNsZnSYDBPE&list=PL4F3FBBF0881B16D7&index=16).
Lastly, a common issue when working with psychrometers is condensation. If the sample tissue is cooler than the chamber, water may condense directly on the sample, where it can be absorbed or redistributed. On the other hand, if the chamber is cooler than the sample, condensation may form on the chamber walls, introducing uncertainty and potential errors in the measurements. This problem is often noticeable in the data when there are strong temperature gradients (dT). In most cases, condensation issues can be resolved by cleaning the system and reinstalling the components properly. However, if the problem persists, it may be necessary to adjust certain parameters, such as the cooling time or chamber heating settings. For more details on these adjustments, refer to Chapter 6 (“Settings and Measurement Options”) of the PSY1 Manual DOC-00087v2. If none of these solutions resolve the issue—particularly when measurements remain close to 0 MPa—it is important to recognize a fundamental limitation of the psychrometric method. Near the wet end of the spectrum (around 0 MPa), the energy required to convert water from liquid to vapor is extremely low, which reduces measurement sensitivity and accuracy. This situation is uncommon in potted plants but can occur more frequently in hydroponic systems.
Download and check the data regularly (once a day). This regular check will help in tracking the data, and in identifying any issues (as mentioned above) as early as possible.
As a complement to Ψleaf, plant transpiration can be monitored using weighing scales. In this study, whole-plant transpiration was monitored continuously by recording pot weight over the same duration of the psychrometers. The pots were placed on a scale (A&D, EK-15KL, Japan; the resolution is 0.1 g), and the weight was recorded every 15 minutes using the RsWeight program from the Windows Communication Tools (WinCT) package. This software, developed by A&D, collected data via a StarTech USB 16-
or 8-port adapter connected to the scale through an RS232 cable. To minimize soil evaporation, the pots were covered with aluminum foil.
Additionally, destructive measurements of Ψleaf can be taken using a Scholander pressure bomb to compare with the data measured by TCP. However, it is still unclear whether the Scholander pressure bomb measures both Ψ
p and Ψ
o or just the Ψ
p of leaves, while TCP measures both Ψ
p and Ψ
o.
Data analysis
Timing: ~10 minutes.
We made an R quarto document as well as custom functions to load raw measurements files, clean the data files, and make graphs. This R quarto document is available on Zenodo (D’Agostino, 2026). The folder contains a user-friendly notebook to load files in R, custom functions to extract and compile data, and a simple dataset containing data about 4 plants.
Figure 7 shows compiled and cleaned data from the example dataset.
Figure 7. Example of compiled and cleaned data from the R notebook.
Plants were grown in greenhouse as explained in the section of “Seeds germination and plant growth”. Plant 2 and 4 were subjected to well-water (WW) conditions, while plant 1 and 3 were subjected to water-deficit (WD) conditions. Left y-axis indicated Ψleaf and Ψsoil. Right y-axis indicated actual transpiration rate (Tact) recorded by weighing scale.
1) Code setup
Download the repository (D’Agostino, 2026). Extract the content to a local disk. Launch Rstudio. Open the file “Data_Analysis_Main.qmd” located in the repository folder. Ensure all required libraries are installed.
2) Data collection
Collect data from both Teros 21 and PSY1-leaf by connecting the data loggers to a computer with the relevant software mentioned previously. PSY1-leaf will generate a.csv format file and store all the data inside, while CR800 generates a DAT format file. In both cases, copy each individual file to data/raw/LWP/folder. Make sure that each file is named as the ID of the sensor.
3) Encode your metadata
Create a metadata file that contains identifiers for plants and sensors, similar to Plants_ID.csv in data/clean/folder. Make sure that each sensor ID corresponds to the right Plant_ID.
4) Run the code to extract and clean Ψleaf data
The code automatically extracts data from each individual Ψleaf file and integrates it into one unique table that contains Ψleaf data per date and per Plant_ID. The table is saved in the data/raw/folder. Statistical manipulations or data corrections can then be applied as deemed appropriate. A cleaning algorithm has been included in the code that filters data based on: the number of “0” and “NAN” values; incorrect day-night cycle amplitude; the global slope, and the global level (more details are provided in the notebook).
A web version of the notebook is available here: https://theplantwaterpump.github.io/TS_Protocol/
5) Run the code to extract soil water potential and transpiration data
A similar process to the Ψleaf is done for Ψsoil data and weight data within the code. Follow instructions set in the notebook for further detail for these two data types. Additionally, the code includes the computation of transpiration rate, and allows all variables to be plotted together (
Figure 7).
Because this protocol paper is intended to demonstrate PSY1 operation and interpretation, the example dataset is illustrative and not designed for rigorous statistical treatment; users should include sufficient biological replication, typically at least 3–5 replicates where possible depending on the experimental objective and biological variability, together with calibration checks and uncertainty analysis.
Troubleshooting
Heterogeneity of water distribution in the soil
As the soil dries out, there will be heterogeneity of water distribution in the soil. To have more representative Ψsoil measurements in the pot, we recommend to:
(1) Install Teros 21 at different depths and/or the same depth with different horizonal positions.
(2) Avoid watering in one location and instead try to spray the water uniformly over the whole surface of the top layer of the soil. If a large amount of water is required to be given to the plant, try to split the amount into several portions and give it to the plant during the day.
Charging issue for the psychrometer data recording
During this study, difficulties with the psychrometer data were encountered due to the impact of the data logger’s charging process. Fluctuations in the PSY1 data were exhibited when the charging process was initiated or terminated (as shown in
Figure 8). This occurred particularly when the PSY1 data loggers were connected to a power socket simultaneously used by other devices, such as weighing scales. To avoid this issue, an external 12 V battery was used to charge the data loggers.
Figure 8. Example of the charging effects on the data recordings.
Ψleaf is indicated by red line and voltage is indicated by blue line. The charging voltage was 24 V and “0” voltage indicates there was no charging. When voltage changed between “0 V” and “24 V”, Ψleaf started jump.
Data cleaning with an algorithm
The initial dataset from the psychrometer measurements may contain several outliers, missing values (skipped due to low battery), incorrect entries, and aberrant patterns. To resolve this, a data cleaning algorithm was implemented. This algorithm was designed to remove any values that were missing, zero, or otherwise aberrant. Data were considered aberrant when values deviated markedly from the typical day- or night-time distribution and/or were accompanied by abnormal Wet Bulb Depression or dT signals indicative of unreliable psychrometric measurements. It was also programmed to identify and remove inverted day-night cycle patterns, as well as values that were statistically insignificant. The inverted day/night cycle could be due to the charging issue explained above.
Figure 9 shows applications of data cleaning on the example dataset. For more details, please check codes that have been deposited on Zenodo (https://doi.org/10.5281/zenodo.20080750, D’Agostino, 2026).
Figure 9. Example of data cleaning using the algorithm.
Green is kept data and red is discarded data.
Conclusion
In summary, the present protocol is not confined to the descriptive monitoring of Ψsoil and Ψleaf; it also furnishes an experimental framework to relate continuous water-potential measurements to plant hydraulic properties. As previously mentioned, radial water flow can be expressed as a function of the driving force in Ψtot and the corresponding hydraulic conductivity. Accordingly, when Teros 21 measurements of soil matric potential are interpreted in conjunction with PSY1-derived Ψleaf and an independent estimate of water flux, such as whole-plant transpiration obtained gravimetrically, these time series can be used to assess changes in apparent root or whole-plant hydraulic conductance during the processes of drying and rewetting under near-steady-state conditions and with appropriate assumptions. Such an interpretation necessitates explicit assumptions, including hydraulic equilibration at the measurement interface, limited temperature artefacts, and a physically consistent comparison between the water-potential components under consideration. It has been demonstrated that, within the established limits, the combined measurements are not only useful for tracking plant water status over time, but also for identifying phases of hydraulic limitation, soil-root disconnection, and recovery. Consequently, this linkage of the protocol to mechanistic analyses of water transport in the SPAC is more direct.
Ethics and consent
Ethical approval and consent were not required.
Data availability
The datasets and codes to analyze the data have been deposited on Zenodo (https://doi.org/10.5281/zenodo.20080750, D’Agostino (2026)).
Data are available under the terms of the Creative Commons Zero v1.0 Universal.
An additional explicative video for the psychrometer installation on leaves is available on Zenodo (https://doi.org/10.5281/zenodo.17510720, Degand et al. (2025)).
The author(s) declare that this video is released under the Creative Commons CC0 1.0 Universal Public Domain Dedication. This means the video is free of all copyright restrictions and may be copied, modified, distributed, and used without permission, including for commercial purposes.
Data are available under the terms of the Creative Commons Attribution 4.0 International.
