Configuration of Low-Cost Miniature Heat Pulse Probes to Monitor Heat Velocity for Sap Flow Assessments in Wheat (Triticum durum L.)

Abstract

Heat velocity (V_h) is a key metric to estimate sap flow which is linked to transpiration rate and is commonly measured using thermocouples implanted in plant stems or tree trunks. However, measuring transpiration rates in the Gramineae family, characterized by thin and hollow stems, is challenging. Commercially available sensors based on the measurement of heat velocity can be unaffordable, especially in developing countries. In this work, a real-time heat pulse flux monitoring system based on the heat ratio approach was configured to estimate heat velocity in wheat (Triticum durum L.). The heat velocity sensors were designed to achieve optimal performance for a stem diameter smaller than 5 mm. Sensor parameterization included the determination of casing thermal properties, stabilization time, and time to achieve maximum heat velocity which occurred 30 s after applying a heat pulse. Heat velocity sensors were able to track plant water transport dynamics during phenological stages with high crop water demand (milk development, dough development, and end of grain filling) reporting maximum V_h values in the order of 0.004 cm s⁻¹ which scale to sap flow rates in the order of 3.0 g h⁻¹ comparing to reports from other methods to assess sap flow in wheat.

1. Introduction

Evapotranspiration (ET) has been used as a proxy for crop water demand and is defined as the water transferred to the atmosphere from wet surfaces, soil evaporation, and from plant transpiration [1]. Plant transpiration (T_w) is the process of transferring liquid water from the soil through the plant vascular system and releasing it into the atmosphere as water vapor through leaf stomata [2].

Under limited water conditions, the potential crop water loss can significantly reduce the rate of actual ET due to stomatal control but compromising CO₂ assimilation which may result in a decrease in agricultural yields and economic losses [2]. Secondly, under high-temperature conditions, transpiration acts as the plant’s cooling system while also increasing the rate of nutrient transport to meet its high demand due to accelerated plant development caused by heat [3].

Future climate predictions indicate that water scarcity and environmental temperatures will increase [4]. Consequently, it is essential to ensure that cereals grown at a large scale are water-use efficient. This involves increasing grain yield while minimizing water losses through T_w, even in unfavorable hydric conditions. However, this requires precise knowledge of the actual crop water demands at each phenological stage based on the assessment of crop water loss via T_w [3,5,6]. Furthermore, since air temperature plays a crucial role in determining stomata opening, plant water losses, and consequently, water use efficiency, it is of great importance to develop and apply monitoring systems capable of measuring both diurnal and nocturnal transpiration rates in wheat [7,8,9].

Currently, there are several methods and techniques to estimate T_w at different spatial and temporal scales. These spatial scales range from leaves, stems, and whole plants to ecosystems and watersheds while time scales range from minutes, hours, and days to seasons and years. Among the most common techniques to estimate T_w are gas exchange chamber systems, porometers, soil lysimeters, leaf thermography, sap flow sensors, and micrometeorological methods which include combinations of stable isotopes and flux assessments (i.e., Bowen ratio and the Eddy covariance techniques). All these approaches have advantages and disadvantages, including challenges in automation, installation, field portability, temporal resolution, disturbance of plant microclimate, operation complexity, and cost [10,11,12,13].

At the plant scale, sap flow techniques are one of the most suitable technologies due to their automation capabilities and real-time measurements, and represent an integration of water flux, mineral salts, and nutrients (sap) through the xylem to transport them to the entire plant [14,15]. Because 99% of sap is water, the quantification of transpiration by sap flow analysis has been widely documented in the literature for different species [10,16,17]. The implementation of automated technology, such as a sap flow monitoring system, can aid in determining the precise water requirements of crops and provide continuous information on water use by assessing T_w.

Nowadays, the methods for calculating sap flow are based on thermodynamic principles that use heat as an indicator of sap movement in xylem tissue [18,19,20]. For this reason, such methods are classified into three groups: (a) heat dissipation, (b) heat balance, and (c) heat pulse [10,18]. The selection of the appropriate method highly depends on the type of plant, the objective of the measurements, the actual sap flow rate, and the advantages and disadvantages of each method [17]. However, all these approaches are useful for the continuous assessment of T_w, as they sense plant responses to rapid and chronic environmental changes, irrigation regimes, and nutrient treatments in crops [21].

Most sap flow methods have historically been implemented only on trees and plants with woody stems larger than 30 mm in diameter. However, the continuous measurements of sap velocity are essential for evaluating water transport in grasses (Poaceae or Gramineae family) such as wheat, which is one of the main cereals produced in the world for food security [22]. It is important to remark that the heat balance method has been previously attempted to be used in wheat plants [23,24,25,26] and other grasses [27], while the heat pulse method has been implemented in other herbaceous plants [19,28,29,30].

Important efforts have been made to improve the implementation of the heat pulse method on smaller plants without the insertion of probes [31]. One big improvement was the use of miniaturized external heat pulse sensors that are able to measure heat flow velocity for sap flow calculations. This method is based on the heat ratio approach [32] and does not require the insertion of probes. It also allows the measurement of low and bidirectional fluxes that cannot be measured by other heat pulse methods [15,31,33]. Furthermore, commercial or scientific-grade sap velocity/flow probes are more expensive per sensor unit (≥USD 1000) [34] compared to the low-cost miniaturized external heat pulse probes. Therefore, these sensors are an excellent tool for assessing water transport in non-woody plants such as those found in the Poaceae family which produce the majority of the cereals worldwide [22]. The objective of this study was to adapt an external heat pulse probe to assess sap heat velocity in wheat plants by using the heat ratio approach [33] by implementing an array of low-cost sap velocity sensors under controlled conditions. We hypothesize that miniature heat pulse probes based on the heat pulse method are capable of continuously measuring heat velocities (V_h) in the non-woody stems of wheat plants.

2. Materials and Methods

2.1. Study Site

Both the assembly of the sensors and the evaluation of their performance were carried out at the Sonora Institute of Technology (ITSON) in the southern region of the Mexican state of Sonora (Figure 1).

2.2. Heat Pulse Method to Estimate Heat Velocity

The heat ratio approach proposed by [32] was used to estimate heat velocity (V_h). This method relies on the temperature ratio measured by two thermocouples separated by a known equal distance (x) from a resistor that emits heat pulses as shown in the following equation:

$${\mathrm{V}}_h={\displaystyle \frac{k}{x}}ln\left({\displaystyle \frac{\delta T_d}{\delta T_u}}\right),$$

(1)

where V_h is the heat velocity in cm s⁻¹; x indicates the distance, in centimeters, between the heater and the thermocouples; δT_d is the change in temperature (in °C) measured by the upper thermocouple (downstream); δT_u is the change in temperature measured by the lower thermocouple (upstream-closest to the plant base); and k is the thermal diffusivity (cm² s⁻¹) estimated with the approach proposed by [33]:

$$k={\displaystyle \frac{x^2}{{4t}_m}},$$

(2)

where t_m is the time (in seconds) it takes to reach the maximum temperature in both thermocouples after the emission of a heat pulse under no-flux conditions [32]. In order to obtain null-flux conditions, it was required to obtain measurements during nighttime on cut stems). In this particular case, thermal diffusivity (k) is a physical property that expresses the rate of heat transfer between the polylactic acid casing and the plant stem.

When the ratio δT_d/δT_u is equal to one, then heat velocity is zero (ln [1] = 0). Conversely, when the ratio δT_d/δT_u is different from 1, then a heat flux is present. When the ratio δT_d/δT_u is greater than 1, then the heat flux goes towards the leaves while δT_d/δT_u less than 1, then the heat flux goes towards roots [15].

2.3. Experimental Design and Sensor Installation

The heat velocity sensor consists of three main components: a heater, a pair of thermocouples, and an external casing that protects and holds both the heater and the thermocouples. The casing was a rectangular-shaped block (18 mm long, 7 mm wide, and 3.5 mm high) of polylactic acid (PLA) produced in a 3D printer (Creality Ender 3). The casing has six perforations of 0.9 mm in diameter, allowing for the secure placement of both the heater and thermocouple wires (Figure 2A,B). Code for printing the casing is deposited in Supplementary Materials.

The heater consisted of a thick film resistor with a nominal power of 250 mW and a resistance of 47 Ω (Vishay, model CRCW120647R0FKEB, Mouser Electronics, Mansfield, TX, USA) soldered to two 0.13 mm diameter PFA-insulated copper wires (TFCP-005 and TFCC-005, Omega Engineering, Monterrey, Mexico). The heater was leveled and placed horizontally in the middle of the rectangular-shaped casing (PLA-block). Subsequently, the resistor was attached and fixed using cyanoacrylate glue. Two 0.13 mm diameter type-T thermocouples (copper-constantan) with PFA insulated were placed 0.6 cm above and below the heater and then attached with cyanoacrylate glue.

The heat velocity sensor was attached to the plant stem by wrapping it with parafilm^® to ensure good contact. In order to insulate the probe from external temperature fluctuations, thermal insulation was enhanced by wrapping the parafilm^® with an additional layer of polyethylene plastic, bubble wrap, and aluminum foil (Figure 3). The heater of each gauge was plugged into a heat pulse control panel which consisted of an array of 120 Ω resistors connected in a series. The heat pulse control panel was triggered by the 12 V switch-controlled port of a datalogger (CR1000X, Campbell Scientific, Logan, UT, USA) in order to generate a 6 s/0.22 W heat pulse every ten minutes (Figure 2C). This latter heat pulse duration and power was previously selected since it did not cause damage or burns to the wheat stem. A photovoltaic system (20 W solar panel, charge controller, and rechargeable battery) was used to provide load to the datalogger.

In order to record simultaneous temperature readings from several sensors, the system was enhanced with a multiplexer (AM16/32, Campbell Scientific, Logan, UT, USA) which was coupled to the datalogger. The system was programmed to emit a heat pulse every 10 min and record the temperature measured by the thermocouples located above and below the heater for 200 s after each heat pulse was emitted.

A total of fourteen heat velocity sensors were deployed on individual wheat plants placed in plastic grow bags (30 cm width × 35 cm height) containing a substrate consisting of regular soil (coarse sandy clay, low in organic matter and slightly alkaline, PH 8) and commercial peat moss in a proportion of 1:1 [35] (Figure 4). The complete wheat development cycle was carried out within the greenhouse of the university campus under optimal irrigation (no stress conditions), fertilization, and proper pest control management. The seed planting date was 18 December 2022 while plant emergence occurred on 23 December 2022. The wheat cultivar used in this experiment was CIRNO C2008, which is the most planted wheat variety by farmers in the Yaqui Valley of Northwestern Mexico [36]. The heat velocity sensors were installed on the main stem (<5 mm diameter), close to the first node, two days after heading, and continuous measurements were carried out in three periods of six days during milk development (Z7.0), dough development, and (Z8.0) end of grain filling or beginning of ripening (Z9.0). Plant phenological stages were recorded using the Zadoks decimal scale [37]; the 14 experimental plants reached each stage within ±1 day of difference. Optimal irrigation conditions were maintained across the whole experimental period by adding an equal amount of water to all the plants every two or three days at maximum depending on the environmental conditions.

Because stem temperature measurements were taken by thermocouples, effective insulation was required in order to decrease the effect of external factors (such as temperature, radiation, and humidity) that helped to improve measurement quality and sensor lifetime. For this reason, an insulation “capsule” made of different layers of Parafilm^®, polyurethane sheets, bubble wrap, and aluminum foil was used to cover the heat velocity sensors (Figure 3).

2.4. Data Collection and Analysis

All the heat velocity sensors were connected to a data logger (CR1000X, Campbell Scientific, Logan, UT, USA) to execute a routine of instructions that included heat pulse triggering at 10 min intervals, recording raw temperature data, and data storing at 200 s intervals after the heat pulse was emitted. A stabilization period between 20 and 40 s after having reached the maximum value was established. Temperature differentials (δT_d and δT_u) were calculated by extracting the value of the initial temperature (when the heat pulse is ignited) to all the temperature values registered during the stabilization period; then, the results were averaged (terms in parentheses in Equation (1)) to calculate heat velocity (V_h).

Within this stabilization period, the time that takes to reach the maximum temperature (t_m) was identified in fresh but cut stems (no flow) to subsequently calculate thermal diffusivity (k) (Equation (2)). Data were downloaded daily and later processed in Matlab (R2019a version 9.6) to estimate all the components of Equation (1).

A linear mixed model was applied using the package lme4 from Rstudio in order to detect statistical differences between phenological stages and sensors for the heat velocity trait. The sensor was set as a random term and the stage as a fixed term. Significant differences were observed between stages (p < 0.05) but not between sensors (p = 0.6083). The mean heat velocity for the phenological stage 3 (end of grain filling) was significantly lower than the heat velocity recorded during the milk development (stage 1) and dough development (stage 2).

To track the response of heat velocity to environmental factors such as air temperature, relative humidity, vapor pressure deficit (VPD), and photosynthetically active radiation (PAR), complementary sensors were deployed in the experiment. Air temperature and relative humidity were measured using a Campbell HMP45C sensor while PAR was measured with a Licor LI190SB Quantum sensor (Figure 4).

In order to gain insights into the sap flow rates recorded by the heat flux sensors, we compared the mean heat velocities recorded in 12-h periods (day-light) with the actual weight loss recorded in a potted wheat plant in the same period of time (

Table 1. Show hourly integrated heat velocities (V_h) sensed with the probes presented in Figure 2 and the lysimeter-type gravimetric measurements of water loss from potted wheat plants with sealed soils. Fit parameters from a simple regression line were water loss (i.e., sap flow) = 1462.8 × (V_h) − 2.97, with an R² of 0.76.

Day	Heat Velocity	Water Loss
	[cm h−1]	[gr h−1]
1	0.002767	1.250
2	0.002865	1.083
3	0.002637	0.833
4	0.002445	0.417
5	0.002454	0.833
6	0.002348	0.417

). To carry out this calculation, a wheat plant was planted in a 9.5 kg pot that had a plastic cover to avoid soil evaporation. The plant was instrumented with a heat flux sensor (Figure 2) and was then placed at a scale to record weight changes as water transpired over the course of six days. The pot data were converted to hourly intervals and used to build a linear regression equation to fit a line that modeled the mean hourly heat velocities to the grams of water lost per hour (Table 1).

3. Results

The following sections show the main findings. Section 3.1 describes the performance of both the upstream and downstream thermocouples which help to establish a temperature stabilization period. Section 3.2 describes the evolution of heat velocity in different phenological stages which include milk development, dough development, and the end of grain filling, respectively.

3.1. Heat Pulse Stability

In order to obtain heat flux measurements in wheat stems, the system emits a heat pulse for 6 s, equivalent to a total heat power input of 0.22 W [33]. Once the heat pulse is triggered, the system records temperatures using the upper (downstream) and lower thermocouples (upstream) of the sensor. To obtain reliable estimations of change in temperature (δT_d and δT_u), it is necessary to set a stabilization period in temperature readings. As seen in Figure 5, a common trend is observed between the downstream and upstream temperatures. A sudden rising limb is observed when the heat pulse is triggered (time = 0) until a maximum temperature is reached (approximately at time = 20 s). Between the peak temperature value and the beginning of the recession limb (approximately at time = 40 s), a moderately stable temperature period is observed (between 20 and 40 s) where 30 s was established as the midpoint, which is defined as the time to maximum temperature in both thermocouples (t_m) after the emission of the heat pulse (Figure 5). Once t_m was established and following Equation (2), the computed value of thermal diffusivity (k) was 0.003 cm² s⁻¹.

3.2. Variability of Heat Velocity

The averaged heat velocity calculated from fourteen heat pulse probes during the phenological stage of wheat milk grain development, dough development, and end of grain filling is shown in Figure 6. As observed, the heat velocity peaked in the milk grain development stage with values ranging around 0.004 cm s⁻¹ while showing minimal discrepancies among the sensors using the standard deviation as metric and according to the results from the linear mixed model (p = 0.6083). Despite low variability in PAR and VPD during this phenological stage, the highest daily values in these meteorological variables produced peak values in heat velocity. It is evident that environmental conditions exert a notable control on heat velocity during this stage, as the daily trajectory of decrease/increase in PAR and VPD resulted in a decrease/increase in the heat velocity. Based on the regression model produced in Table 1, the range of heat velocities depicted in Figure 6 would produce sap flow rates of up to 3.0 g h⁻¹.

During the wheat phenological stage of dough development, the heat velocity peaked at 0.004 cm s⁻¹. Similarly to the previous phenological stage, the VPD and heat velocity showed low variability, with the exception of PAR, which progressively increased at the end of the observation period. At the beginning of the dough development period, the PAR decreased up to 50% in comparison to the end of the same period. Conversely, VPD peaked at 5.3 kPa at the beginning of this stage and steadily increased throughout this period. Despite these changes in environmental conditions, no significant change in the daily trajectory of heat velocity was observed (Figure 6). At the end of grain filling, the heat velocity reached up to 0.003 cm s⁻¹. A steady and gradual decrease in heat velocity was observed as the grain filling period progressed. During the first three days of this phenological stage, the highest observed VPD value was 4.5 kPa; however, there was no significant change in heat velocity. Unlike the previous phenological periods where high values of PAR and vapor pressure deficit led to peak values of heat velocity, in this last stage, a progressive decrease in heat velocity is observed as the plants matured.

4. Discussion

Determining sap flow rates in herbaceous plants like wheat (Triticum durum L.) is a methodological challenge. However, the development of automated tools for this purpose is crucial to advance the understanding of the eco-physiological response of this primary crop to environmental controls and, providing knowledge to potentially implement smart technology to couple with irrigation systems [38]. The current study utilized external heat pulse sensors with polylactic acid base (PLA) case to obtain real-time heat velocity measurements and establish the basis for a sap flow monitoring system in wheat and applicable to plants with stem diameters smaller than 5 mm. Using this prototype system, peak heat velocity measurements in the range of 0.004 cm s⁻¹ were obtained when optimal irrigation and light conditions were supplied during the three penological stages, demonstrating that as we hypothesized, the method of external heat pulse applied with miniaturized sensors is capable to continuously measure heat velocities (V_h) in graminoid wheat plants.

To our knowledge, this is the first report of using this external heat pulse method to track transpiration dynamics in graminoid plants such as wheat.

In addition, this heat pulse/sap flow monitoring application is a low-cost alternative to obtain real-time measurements on plants with stem diameters smaller than 5 mm with little plant damage [10,15,33] as no probe implantation is required. Unlike other sap flow sensors on the market, whose cost can be over USD 1000 per unit, these low-cost sensors minimize the effect of wounds on plant stems and xylem produced by their installation [34]. Specifically, the cost of the raw materials to develop the heat velocity sensor was very cheap (USD 3) without including the cost of labor and considering that the final cost is actually defined by the lengths of the thermocouple wire needed in a particular installation. Furthermore, the anatomy of the wheat plant presents a challenge for installing sensors and obtaining precise heat velocity/sap flow measurements. This is due to the plant’s hollow stem walls, which are more delicate compared to suberized and woody stems [23,24,38]. Our insulation strategy also seems to be adequate to effectively avoid fluctuations in external air moisture and temperature, soil temperature emission, and direct radiation on the sensor (Figure 5), albeit insulation in field installations may require further attention.

The development of a monitoring system to accurately measure real-time wheat transpiration is a useful tool to advance knowledge on water requirements. Furthermore, the development of such systems facilitates the exploration of plant responses to transient changes in solar radiation, vapor pressure deficit, and soil moisture, as our sensors seem to track, hence, it is possible to implement this type of sensor to conduct climate change studies that focus on wheat responses to climate variability.

An important finding regarding the daily sap flow trends in wheat over the phenological stages that we were able to study is that V_h sensors consistently reported a water transport depression at midday, prior to reaching its maximum value early in the afternoon (Figure 6); this downwards trend in the heat velocity is evident in the overall mean and was accompanied by a noticeable increase in variation (expressed as the standard deviation from 14 sensors) at this time of the day. The lack of statistical differences among sensors suggests that this generalized behavior is a true biological response from the wheat plant. Our sensors were also sensitive to the progressive changes in water transport as plants matured since V_h was significantly lower at the beginning of the ripening phenological stage (Z9.0; [37]).

Miniaturized external cork-based heat pulse sensors have been successfully used on various plants, including Actinidia sp. fruit pedicels, Schefflera arboricola petioles, Pittosporum crassifolium stems, and Fagus sylvatica stems, as reported by [33] in New Zealand. The heat velocity measurements reported by these authors were also in the order of 0.004 cm s⁻¹. Skelton et al. [15] utilized an external silicon-based heat pulse method to measure heat velocity in various types of plants of the South African bushland, including Cannomois congesta, Protea repens, and Erica monsoniana. These latter heat velocity measurements were close to 0.001 cm s⁻¹. The same method was also applied by Wang et al. [39] in shrubland plants like Caragana korshinskii and Salix psammophila in China using a flexible porous polyethylene sheet as the sensor base, with observed heat velocities close to 0.006 cm s⁻¹. In a recent study conducted [19] in Belgium, a polylactic acid (PLA) based sensor was used to measure heat velocity in Ficus benjamina stems and Populus tremula branches where the maximum recorded heat velocities were 0.008 cm s⁻¹. All of the aforementioned research works utilized the external heat pulse method on various plant types and materials with distinct thermal diffusivity (k) properties at the base of the sensor. Although none of these studies were conducted in wheat, the heat velocity ranges reported in our study for wheat are just in between the low end of dryland shrubs and high-latitude trees.

Nowadays, studies on sap flow techniques in wheat plants have been limited and a direct comparison of heat velocities across methods is not possible. However, if we scale our measurements of heat velocities with the gravimetric comparison depicted in Table 1, the maximum values of sap flow rates calculated for our study for wheat were in the order of 3.0 g h⁻¹ falling within the range reported by other studies. For example, sap flow rates have been previously measured using the heat balance method on Triticum aestivum L. cv Yecora rojo [26], reporting fluxes of up to 5.1 g h⁻¹ [26]; more recent studies have reported sap fluxes in Triticum aestivum as well [24], indicating maximum rates in the order of 1.7 g h⁻¹. In winter wheat, fluxes with magnitudes of 0.6 g h⁻¹ were measured using the cultivar Ambello, as documented by Cai et al. [23]. Additionally, flux measurements were performed using the wheat cultivar Karim, with rates in the order of 2.5 g h⁻¹ as reported by [25]. Nevertheless, all of these research studies have been conducted under different climatic conditions and genotypes of wheat plants but the magnitudes of sap flow rates fall within the same order of magnitude.

One limitation of our study is the temporal resolution of our method to convert the heat velocity data (cm s⁻¹) to sap flow (g h⁻¹) in wheat (Table 1). Future advancements to strengthen the validity of the method will require more replication and real-time assessments of water losses with independent methods. To carry this out, attention should be paid to using live wheat stems actively transporting water, which for the case of gramineous species would be complicated to do in pipe/hose systems as it is commonly performed in woody stems where controlled amounts of water are forced to flow across vascular tissues in the lab [32]. Therefore, a lysimeter-type calibration like the one presented here is probably the most reliable approach to calibrate heat velocity sensors in wheat plants.

The application of this technology could represent a tool to approximate the water use efficiencies of crops and aid in partitioning evapotranspiration losses on its soil evaporation and transpiration components, which represent the main water consumption in agriculture [40]. Furthermore, the impact of nighttime increasing temperatures on transpiration could be evaluated, as well as the effect of nighttime evaporative demand on crop productivity [9]. Additionally, accurate sap flow estimation on major crops can assist the validation of remote sensing applications, as transpiration is one of the most challenging variables to measure, and calculating the water balance components at the plot level or at different spatial scales could be highly beneficial. Consequently, the development of automated technology to assist in the accurate measurement of plant transpiration in real time represents a valuable tool for advancing knowledge on water use in herbaceous plants, which represents a significant challenge in global agriculture.

5. Conclusions

We show that the heat pulse method to monitor real-time heat velocity in order to assess water status in wheat plants is feasible. The results show that the heat pulse probes can track transpiration dynamics during the stages of higher water requirements in wheat, such as milk development, dough development, and end of grain filling. Maximum heat velocity during this period reached values as high as 0.004 cm s⁻¹ with similar readings among the fourteen probes tested during the experiment. Therefore, the proposed system represents a low-cost, non-destructive, and easy-to-implement alternative to monitor water status in non-woody, herbaceous crops.