Energy and Exergy Analyses Applied to a Crop Plant System

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This article calculates exergy in plant crops and examines the impact of plant surface temperature on exergy values. The study is of potential interest due to its attempt to link thermodynamic principles with crop processes using exergy. However, I have significant reservations about the current version, primarily due to the limited thermodynamic analysis and the weak connections made between crop-specific factors and energy flows. Therefore, I recommend that the paper not be accepted in its current form. Below are the main reasons for this assessment:

1. When introducing exergy, which incorporates both the first and second laws of thermodynamics, certain ambiguities arise. It may be helpful to also introduce the concept of free energy, which similarly involves these thermodynamic principles. A clear distinction between these concepts is necessary, and the authors should explain why exergy, rather than free energy, is the preferred focus. Additionally, the introduction appears to suggest an analysis of exergy destruction (related to irreversible energy dissipation through entropy production), which differs fundamentally from exergy decrease via reversible entropy changes. The confusion is further compounded when the proposed model excludes entropy production.

2. Although the system boundaries are defined, important factors, such as the proportion of area covered by plants and the percentage of plant surface area capturing and reflecting solar radiation, are not included. Since some radiation impacts the soil directly, and not all leaves receive sunlight uniformly, Equation (1), for example, should account for both soil and plant components in terms of reflected and emitted radiation.

3. The authors should clarify why the system’s model does not include heat generated by chemical reactions. For example, the reaction heat of glucose formation from CO2​ and water would be a relevant factor. In living organisms, metabolic processes are a primary heat source for temperature regulation. Furthermore, chemical reactions contribute significantly to entropy production, often the largest source, and provide a direct measure of exergy loss in matter transformation processes.

4. Justification for Model Selection in Section 4.2.1: The rationale for selecting model 1, as opposed to models 2 or 3, should be provided, as the choice appears unexplained.

5. To aid readers, each term in the eqs. 7-17 could benefit from further explanation.

6. Since solar radiation (and corresponding exergy input) is the dominant energy term, the discussion and conclusions largely reaffirm expected outcomes tied to surface temperature. The analysis is also incomplete because solar input should be divided between plant and soil components. The authors could explore exergy sensitivity to additional, potentially controllable parameters.

7. Is it appropriate to simplify a crop plant system using a black box model to identify the dominant flows and parameters affecting crop performance? If the goal is to identify key parameters, it may be more effective to conduct a sensitivity analysis with a more detailed model to capture the system's complexities accurately.

In summary, from a thermodynamic perspective, the paper demonstrates technical calculations but does not fully convey the concepts, particularly in distinguishing system components, boundaries, and processes like biomass-producing reactions. From a crop physiology standpoint, critical parameters—such as the canopy or leaf cover fraction—are not mentioned, and important metrics like the surface area-to-weight ratio are omitted. Even under a simplified, black-box approach, the thermodynamic system remains inadequately defined, leading to limited results and conclusions.

Author Response

Reviewer 1

This article calculates exergy in plant crops and examines the impact of plant surface temperature on exergy values. The study is of potential interest due to its attempt to link thermodynamic principles with crop processes using exergy. However, I have significant reservations about the current version, primarily due to the limited thermodynamic analysis and the weak connections made between crop-specific factors and energy flows. Therefore, I recommend that the paper not be accepted in its current form. Below are the main reasons for this assessment:

1. When introducing exergy, which incorporates both the first and second laws of thermodynamics, certain ambiguities arise. It may be helpful to also introduce the concept of free energy, which similarly involves these thermodynamic principles. A clear distinction between these concepts is necessary, and the authors should explain why exergy, rather than free energy, is the preferred focus. Additionally, the introduction appears to suggest an analysis of exergy destruction (related to irreversible energy dissipation through entropy production), which differs fundamentally from exergy decrease via reversible entropy changes. The confusion is further compounded when the proposed model excludes entropy production.

Thank you for your comment, given that exergy is an important thermodynamic concept, it is useful to briefly address some of the more common questions asked by ecologists and biologists concerning the use of exergy in the analysis of ecosystems, including crop plant systems.

The primary distinction between exergy and Gibbs free energy lies in their reference frameworks: exergy quantifies the amount of work an energy carrier can perform relative to its surroundings, rather than describing an isobaric process between the energy carrier and a reference state. However, exergy represents the theoretical maximum work potential within a given environment, rather than the actual work achievable with existing technology. Please note that this paragraph has been added in the introduction section.

1) Why no direct consideration of entropy production in the exergy analysis?

Entropy production is an implicit part of exergy destruction through the Guoyu-Stodola Theorem as follows:

Where is the exergy destruction, is the environment temperature, and is the entropy production. Exergy is preferred over entropy because it is easier to relate as it has the same units of work, (e.g., kJ), compared to units of entropy (e.g., kJ/K). For example, exergy can be considered the ability to lift a weight. Exergy is also fundamental to the exergy destruction principle for ecosystems, and it has a well-defined maximum whereas entropy production does not have a well-defined maximum value. Furthermore, exergy measures the work potential of gradients, entropy does not, and free energy differences do not except in special circumstances, that gradient concerns the environment.

2) How do exergy destruction and entropy production differ and how are they similar?

Entropy is a thermodynamic property; however, exergy is not a thermodynamic property, it is a pseudo-thermodynamic property, acting like a thermodynamic property only when the environment temperature and pressure are constant.  Similarly, entropy production and exergy destruction differ depending on the environment, specifically the environment temperature as revealed by the Guoyu-Stodola Theorem (Equation 1) above. Entropy production and exergy destruction are similar in that they both provide a measure of thermodynamic irreversibilities.

3) Why do we use exergy rather than free energy?

Gibb’s free energy (G = U +T×S)  could be used in special circumstances as a replacement for exergy, but only when the environmental conditions (i.e., temperature and pressure) are constant. In fact, Gibbs free energy is the amount of available work for an isothermal and isobaric process. Exergy is more of a measurement of the total work available until a system reaches an equilibrium state with its surroundings. We can't replace one with the other, but they are similar in concept. In addition, the amount of exergy is not dependent on whether it’s an isothermal or isobaric process. It could be any type of process, and it will still have the same amount of exergy. However, the same idea cannot be applied to the Gibbs free energy.

A paragraph has been added to the introduction section that reads as follows:

[The main difference between exergy and Gibbs free energy lies in their reference frameworks; exergy quantifies the amount of work an energy carrier can perform relative to its surroundings, rather than describing an isobaric process between the energy carrier and a reference state. Gibbs free energy represent the maximum work that a system can perform under constant temperature and pressure conditions, which has wide applications in Engineering to investigate chemical reaction and phase change related problems. Exergy represents the theoretical maximum work potential within a given environment, rather than the actual work achievable with existing technology.]

In order to make it clearer for the reader why exergy has been selected the following  paragraphs have been added to the introduction section in the revised paper:

[Entropy production is an implicit form for exergy analysis through the Guoyu-Stodola Theorem ()  Where is the exergy destruction, is the environment temperature, and is the entropy production. Exergy is used over energy and entropy due to its three main properties; context sensitive, universal, and not conserved. First, exergy is a context-sensitive because it is formulated to a reference environment.  In addition, when a system is under a thermodynamic equilibrium with its surroundings, it will have zero exergy (Dincer et al., 2008). Second, exergy is a universal property where all thermodynamic systems are compared based on their exergy content. Third, exergy is not conserved unlike energy, exergy can not be created or conserved but only destroyed during a reversible process . Due to exergy properties, exergy is used as a decision-making and optimization tool in many engineering applications such as: power plant design and operation specifications . In addition, exergy found a place in non-engineering disciplines such as: ecology , life cycle assessment, resource accounting, biology, sustainability and as a health assessment tool of an ecosystem . Exergy is preferred over entropy because it has the same units of work, (e.g., kJ), compared to the units of entropy (e.g., kJ/K). For example, exergy can be considered the ability to lift a weight. Exergy is fundamental to the exergy destruction principle for ecosystems, and it has a well-defined maximum compared to entropy production which does not have a well-defined maximum value. ]

Please note that all references are in the revised paper.

Another paragraph has been added to the introduction section:

[In the context of non-equilibrium thermodynamics for complex systems, such as crop-plant systems or ecosystems, exergy serves as a measure of the deviation between the system and its environment from thermodynamic equilibrium, driven by an externally applied gradient, such as temperature or pressure. Consequently, both the system and its environment must be well defined. Exergy is a valuable tool for analyzing non-equilibrium thermodynamic systems; higher exergy indicates a greater deviation from the equilibrium state.]

Energy dissipation is simply one mechanism of "energy degradation".  Technically energy dissipation is not a fundamental entropy production mechanism, as it can consist of two fundamental components, free expansion possible plus finite delta-T possible, depending on the initial temperature and pressure of the system (i.e., thermal gradient/temperature, and pressure gradient/buoyancy).

Another paragraph has been added to the introduction section

[Ecosystems are complex, non-equilibrium, self-organizing, dissipative thermodynamic systems that are open to energy and mass flows, maintaining their organization and structure through continuous energy dissipation. As ecosystems evolve and mature, their total energy dissipation and utilization of available exergy increase, thereby developing more complex structures with greater diversity. This development allows ecosystems to adapt to their environment while enhancing their capacity to capture and utilize solar exergy from the incoming solar radiation to sustain their organization. The greater the exergy being captured, the stronger the ecosystem’s ability to support organizational processes. Consequently, the progression of ecosystem development is quantified by its rate of exergy utilization. Exergy unlike entropy gives an indication of how far from equilibrium the system is, how large the gradients are, and the potential for the system to do something useful .

2. Although the system boundaries are defined, important factors, such as the proportion of area covered by plants and the percentage of plant surface area capturing and reflecting solar radiation, are not included. Since some radiation impacts the soil directly, and not all leaves receive sunlight uniformly, Equation (1), for example, should account for both soil and plant components in terms of reflected and emitted radiation.

Thank you for your comment.  Crop surface temperatures were measured under both greenhouse and field conditions. In the greenhouse experiments, leaf surface temperature has been measured as a proxy for canopy temperature because the work investigated early growth stages (e.g., V2 stage) where canopy temperature (defined as the spatial average temperature of a grouping of multiple plants + soil) would be dominated by soil temperature, which significantly increases the noise-to-signal ratio when studying the temperature differences between stressed and less stressed crop plants. In contrast, surface temperature differences predicted by the exergy destruction principle (EDP) should be dominated by development/growth which is concentrated in early growth stage corn plants. In order to compare crop plants supplied with different nitrogen rates using the EDP, the environment needs to be the same between systems. That is, by looking at canopy temperature, nitrogen availability is internalized inside a “black box”, thus enabling an EDP consistent comparison between crops supplied with different nitrogen rates. Furthermore, the soil heat conduction was considered in the exergy balance. Please refer to  section 2.4.4 titled as Exergy associated with soil conduction heat flux, which was found to be negligible compared to solar exergy.

3. The authors should clarify why the system’s model does not include heat generated by chemical reactions. For example, the reaction heat of glucose formation from CO2​ and water would be a relevant factor. In living organisms, metabolic processes are a primary heat source for temperature regulation. Furthermore, chemical reactions contribute significantly to entropy production, often the largest source, and provide a direct measure of exergy loss in matter transformation processes.

Thank you for your comment, the selected system boundary doesn’t account for the metabolic process, where it assumes that all the internal processes that happened inside the crop plant system are irrelevant, but the focus is what’s happening at the boundary input and output.

A paragraph has been added to the revised paper to emphasize the importance of internal plant mechanisms consideration for future work studies to investigate their direct effect on crop stress, which read as follows

[Future considerations could be expanded to include the calculation of cumulative exergy for crop yield production and the exergy related to soil and plant interaction. In addition, different internal mechanisms (e.g., evapotranspiration, respiration,..etc) will be explored to investigate their direct effect on crop stress. Future work will also include testing the current model with different crop types under various climatic conditions]

Please note that the relevant plant system is not an individual corn plant, but a crop of plants. With the crop plant system selected, the nitrogen rate is an internal variable for the black box assumption, the same as a difference in DNA/genes between corn hybrids as reported in Feng, et al., which is an internal variable to the crop plant system. The key to the crop of plants viewpoint is that what should be measured is the crop surface temperature. Therefore, understanding the internal mechanisms is not part of applying the exergy destruction principle (EDP) thermodynamics once a system boundary has been identified.

4. Justification for Model Selection in Section 4.2.1: The rationale for selecting model 1, as opposed to models 2 or 3, should be provided, as the choice appears unexplained.

Thank you for your comment. There are three main solar exergy models as follows:

Model 1: Finite area and zero entropy production (the chosen model) because of analogy with Carnot engine (i.e., zero entropy production Carnot heat engine assumption)

Model 2: Finite area and non-zero entropy production: This model uses T optimum, which is more difficult to determine, regardless of any trend (i.e., an increasing or decreasing trend). For finite area-zero entropy production, it will be the same conclusions for solar exergy calculations.

Model 3: Infinite area – zero entropy production: It will not be applicable for crop plant systems as it does not have an infinite area.

The following sentence has been added to the exergy associated with solar exergy section on

[This model represents a real system that has a finite area, and the zero entropy production assumption is consistent with the zero entropy production Carnot engine assumption]

5. To aid readers, each term in the eqs. 7-17 could benefit from further explanation.

Thank you for your comment. It has been modified and further explanation is now added. Now all symbols and abbreviations that appear in the equations are well-defined.  

6. Since solar radiation (and corresponding exergy input) is the dominant energy term, the discussion and conclusions largely reaffirm expected outcomes tied to surface temperature. The analysis is also incomplete because solar input should be divided between plant and soil components. The authors could explore exergy sensitivity to additional, potentially controllable parameters.

Thank you for your comment. A sensitivity analysis was conducted and a paragraph has been added to the introduction section that reads as follows:

[Sensitivity analyses were performed to examine the effect of various input variables on the output (i.e., crop surface temperature). The findings indicated that the non-stress related variables such as variation in solar irradiance, air temperature (Tair), soil temperature (Tsoil), vapor pressure deficit (VPD), soil moisture (Soilmoist), humidity (RH), wind speed (V), time of the day (t), cloud cover(CC), crop genetics, leaf angle, leaf emissivity, and sensor view angle need to be further controlled, or compensated through conditional sampling to improve confidence in the results while investigating the relationship between crop stress and crop surface temperature under variable conditions.]

Also, please refer to the new section that has been added to the introduction section that is titled [Crop surface temperature measurement considerations]

7. Is it appropriate to simplify a crop plant system using a black box model to identify the dominant flows and parameters affecting crop performance? If the goal is to identify key parameters, it may be more effective to conduct a sensitivity analysis with a more detailed model to capture the system's complexities accurately.

Thank you for your comment. The entire point of the exergy destruction principle is to get away from having to consider internal complexities and assume the complex ecological thermodynamic system adjustment according to stress.  However, it would be interesting to know the internal mechanisms in order to explain ‘how’ plants adjust to biotic or abiotic stress, but it is not at all required for the exergy destruction principal hypothesis.  Future work will include the investigation of different mechanisms to look inside the system for more explanations.

In summary, from a thermodynamic perspective, the paper demonstrates technical calculations but does not fully convey the concepts, particularly in distinguishing system components, boundaries, and processes like biomass-producing reactions. From a crop physiology standpoint, critical parameters—such as the canopy or leaf cover fraction—are not mentioned, and important metrics like the surface area-to-weight ratio are omitted. Even under a simplified, black-box approach, the thermodynamic system remains inadequately defined, leading to limited results and conclusions.

Thank you for your comment. Many paragraphs have been added to the introduction section to make it clearer for the reader to follow up on the exergy destruction principle and why it is chosen and how it is applied to crop plant system. The proposed model and conclusion are based on a set of assumptions including soil and environment temperature and the base assumption is taken for corn crop grown in Ontario, Canada under variable field conditions.

The canopy to leaf fraction ratio is important but not relevant to the exergy-destruction principle (EDP), which is inside the black box.  Also surface area-to-weight ratio is inside the black box so it is also irrelevant to EDP.  Leaf fraction ratio and surface area-to-weight ratio may very well be critical parameters to describe how the system changes to follow the exergy destruction principle,  but in order to find the exergy-controlling mechanisms or parameters inside the system is beyond the scope of this paper and are not required to test the exergy destruction principle.  All we are looking for with the exergy destruction principle is the relative rates of exergy between ecosystems, and these rates are a function of the ecosystem surface temperature only without needing to know how the ecosystem surface temperature is generated.  It is true, that to be most accurate in the quantification of the exergy destruction one would measure the temperature topographic profile across an ecosystem (which, for example, would be affected by the leaf fraction ratio) and then integrate over this profile to obtain a value for the exergy destruction, however, this is not required to extract exergy destruction trends which is what the exergy destruction principle concerns.  All that is needed for the ecosystem to see trends is to measure the total energy emitted which would provide an effective or average surface temperature to quantify exergy destruction for the exergy destruction principle.  For a given ecosystem one expects an optimum pixel size for averaging the thermal energy emitted or temperature of the ecosystem as the goal to maximize spatial resolution is balanced to minimize sample fluctuation or variance.

Reviewer 2 Report

Comments and Suggestions for Authors

The main question addressed by this paper is how energy and exergy analysis can be applied to crop plant systems to assess energy and exergy flows and identify the dominant factors, such as temperature, that influence plant development. The study tests the hypothesis that plant stress can be detected by monitoring the crop surface temperature, using the Exergy Destruction Principle (EDP) to link temperature changes to stress levels.

The study is original and relevant in the fields of agricultural engineering and thermodynamics, as it seeks to quantitatively determine the relationship between thermodynamic principles and plant health. Specifically, the study addresses a significant gap in the field by proposing an exergy-based approach for monitoring plant stress, which could improve precision agriculture practices by providing a non-invasive way to detect stress before visible signs appear​.
Unlike many studies that focus solely on energy balance in plant systems, this study integrates both energy and exergy analyses, highlighting the importance of exergy (the quality of energy) in agricultural contexts. This adds a unique dimension to the subject area by providing a thermodynamically comprehensive model that can help identify stress factors through temperature readings. The approach differs from traditional methods by using the principle of thermodynamic degradation to predict plant stress, making it a potentially valuable tool for increasing yields and efficiency.

Although the methodology is detailed, some improvements could be beneficial:The study relies on several assumptions, such as constant soil and environmental temperatures, which may not be realistic in different climate conditions. Testing the model in various environments or specifying the conditions under which these assumptions hold would strengthen the methodology; Introducing additional control experiments, such as comparing plants with different levels of irrigation or nutrients under identical conditions, could provide more reliable data on the effects of exergy on stress indicators. This would ensure that observed exergy changes are due to plant stress rather than external variables such as soil or environmental factors.

The conclusions appear consistent with the evidence presented. The results support the hypothesis that mid-day radiation, energy, and exergy flows can determine crop surface temperature and potentially serve as a reliable indicator of plant stress. However, the paper could benefit from a more detailed explanation of the limitations of the findings, particularly where assumptions might limit applicability. Although the main questions are addressed, additional experiments in different climatic conditions or with various crop types would strengthen the generalizations in the conclusions​.
The references are appropriate and include established thermodynamics works and recent studies on energy and exergy analysis in agricultural systems. References to foundational works in thermodynamics lend credibility to the study, while citations of recent research support the relevance of the topic in the context of modern precision agriculture​.
Including well-designed tables and figures is essential for effectively illustrating energy and exergy flows, enhancing the clarity of the study’s results and findings. Tables could summarize key findings, such as energy and exergy balance equations, dominant energy flow terms, and comparisons under different conditions. Each table should be clearly labeled, with specific headings that highlight important metrics like "Energy Contribution by Source" or "Exergy Destruction Rates."

Figures are equally important for visualizing the complex dynamics of energy and exergy flow in a simplified manner. Diagrams that depict the input and output energy flows for the plant system, ideally with arrows showing the direction and magnitude of energy or exergy, would help readers understand the system boundaries and energy transformations discussed in the study. Similarly, line or bar charts comparing exergy contributions from various sources under different conditions (e.g., sunny vs. cloudy days) would vividly illustrate the role of solar radiation in exergy flow, supporting the study’s conclusions.

Including graphical comparisons under different environmental or operational conditions, such as varying irrigation or nutrient levels, would further demonstrate the model’s applicability. These comparisons could be presented as bar charts or scatter plots to reveal trends or anomalies in exergy flows, allowing readers to understand the factors affecting plant stress as described through exergy analysis.

In conclusion, this paper provides an innovative contribution to understanding plant stress through energy and exergy analysis. It could be further strengthened by some methodological improvements, the addition of control experiments, and further testing under varied conditions, highlighting the importance of clearly labeled tables and figures that effectively illustrate energy and exergy flows.

Author Response

The main question addressed by this paper is how energy and exergy analysis can be applied to crop plant systems to assess energy and exergy flows and identify the dominant factors, such as temperature, that influence plant development. The study tests the hypothesis that plant stress can be detected by monitoring the crop surface temperature, using the Exergy Destruction Principle (EDP) to link temperature changes to stress levels.

The study is original and relevant in the fields of agricultural engineering and thermodynamics, as it seeks to quantitatively determine the relationship between thermodynamic principles and plant health. Specifically, the study addresses a significant gap in the field by proposing an exergy-based approach for monitoring plant stress, which could improve precision agriculture practices by providing a non-invasive way to detect stress before visible signs appear​.

Unlike many studies that focus solely on energy balance in plant systems, this study integrates both energy and exergy analyses, highlighting the importance of exergy (the quality of energy) in agricultural contexts. This adds a unique dimension to the subject area by providing a thermodynamically comprehensive model that can help identify stress factors through temperature readings. The approach differs from traditional methods by using the principle of thermodynamic degradation to predict plant stress, making it a potentially valuable tool for increasing yields and efficiency.

Although the methodology is detailed, some improvements could be beneficial:

• The study relies on several assumptions, such as constant soil and environmental temperatures, which may not be realistic in different climate conditions. Testing the model in various environments or specifying the conditions under which these assumptions hold would strengthen the methodology;

Thank you for your comment. We agree it would be useful to test the model in different environments and such is the hope for future work to strengthen the methodology.

Many assumptions were made including soil and environment temperature in this study as it is mentioned  under base assumption: a case study for Ontario, Canada. These temperature values are based on ground measurements conducted during crop surface temperature measurements using thermocouples and thermal cameras in Ontario, Canada from 2015 to 2019. Future work will include testing the model under different environmental conditions.

• Introducing additional control experiments, such as comparing plants with different levels of irrigation or nutrients under identical conditions, could provide more reliable data on the effects of exergy on stress indicators. This would ensure that observed exergy changes are due to plant stress rather than external variables such as soil or environmental factors.

Thank you for your comment. We intentionally removed irrigation/water from the stress considerations by ensuring that crop plants under study are well watered under both greenhouse and field conditions.  However, even if corn plants were stressed with water in some periods of time, it was effectively uniform across plots, as ensured by the randomized block design of the plots. Therefore, even if water stress did affect the corn surface temperature, it would only shift the temperature and not affect the temperature difference trends induced by the nitrogen differential stressor. This work intended to initially look beyond water stress impacts on crops. Future work would benefit from considering water stress as well.

With regard to nutrients, this was the focus of the paper. Nitrogen was investigated under different rates given its known strong relationship with crop yield.  Different levels of nitrogen rates were applied to corn plants to create a stress nitrogen profile in order to test the hypothesis that states (more developed and less stressed plants will have lower surface temperature during the day compared to less developed/stressed plants). Phosphorus and Potassium studies are planned for future work funding permitting. For the soil, given the focus on nutrients, water content was monitored and soil nutrient levels were measured multiple times.

 For many other environmental variables such as destructive winds, hail, etc., were monitored but not experienced during crop surface temperature data collection. With regards to an ambient temperature variation, which was ‘corrected’ to remove variability impacts due to daily temperature variations (please refer to [Alzaben, H., Fraser, R., & Swanton, C. (2019). An inverse correlation between corn temperature and nitrogen stress: A field case study. Agronomy Journal, 111(6), 3207-3219] in which corrected temperature was identified and explained further). Finally, we thank the reviewer for this question as it is important to control the experiment, and the following text is now added in the introduction section titled as (Crop surface temperature measurement considerations)

Please note that all references are provided in the revised paper.

[1.1. Crop surface temperature measurement considerations

The two hypotheses developed to detect crop stress at early growth stages ] were tested under greenhouse and field conditions. For field experiments, soil nitrate samples to a 30 cm depth were collected multiple times: before planting and after harvesting the field to investigate the residual nitrogen content in the soil from the previous year. The same plots were chosen to examine the level of nitrate variation in the soil. Five cores per plot were taken and mixed. A non-significant difference in soil nitrate was observed among different nitrogen levels within the field before fertilizer application each year, which implies that the amount of nitrogen added in the previous year does not impact the year after. For greenhouse experiments, soil nitrate was measured using a colorimeter (smart 3 soil, LaMott, MD, USA), in which soil nitrate content increases with nitrogen rate supply.

In regard to water content, the volumetric water content (i.e., the ratio of the water volume to the soil volume) was measured across various plots within the field using an EC5 soil moisture sensor (Decagon Devices, Inc., Pullman, WA, USA), which was installed at a depth of 10 cm below the ground surface. Corn plants were monitored for water stress conditions throughout the growing seasons of 2016, 2017, 2018, and 2019, with concurrent measurements of soil volumetric water content and precipitation rates [6,7]. As an example, in 2018, the volumetric water content for plots receiving 0 and 188 kg N ha⁻¹ was 18.46% ± 0.058 and 16.33% ± 0.038 (m³ m⁻³), respectively, based on 10-day averages across four plots per nitrogen rate (Personal communication, R. Eerpina). These values fall within the field capacity range of 22% to 28% for silt clay loam soil [L. F. Ratliff, J. T. Ritchie, and D. K. Cassel, “Field-measured limits of soil water availability as related to laboratory-measured properties 1,” Soil Science Society of America Journal, vol. 47, no. 4, pp. 770–775, 1983]. Additionally, the absence of visible wilting in the plants suggests that corn plants did not experience significant water stress.

The measured crop surface temperatures were corrected for meteorological conditions on different days, in which variations in air temperature affect the sensitivity of crop surface temperature measurements. The following equation was used for the correction

Where T_c is the canopy temperature (°C), T_a is air temperature (°C), T_{a_mean} is the mean air temperature (°C).

It was observed that corn surface temperature decreased with increasing nitrogen application rates. A consistent but statistically significant (p-value < 0.05) negative correlation was identified between crop surface temperature and applied nitrogen rate. However, surface temperature measurements exhibited variability due to external and weather-dependent factors influencing crop surface temperature. Figure 1 below summarizes the mean surface temperature as affected by the nitrogen application rate for June and July 2017. The regression analysis consistently identified a negative slope.

Figure 1. The mean leaf surface temperature as affected by nitrogen application rate is shown for (a) June 2017 and (b) July 2017. Each data point represents the daily average of 12 temperature measurements, derived from three measurements per replication among four replications for each nitrogen rate [adapted from 47].

• The conclusions appear consistent with the evidence presented. The results support the hypothesis that mid-day radiation, energy, and exergy flows can determine crop surface temperature and potentially serve as a reliable indicator of plant stress. However, the paper could benefit from a more detailed explanation of the limitations of the findings, particularly where assumptions might limit applicability.

Thank you for your comment, yes, many limitations were discussed in previously published papers related to the relationship between crop surface temperature and crop stress. The following paragraph has been added to the methodology section

[Sensitivity analyses were performed to examine the effect of various input variables on the output (i.e., crop surface temperature). The findings indicated that the non-stress related variables such as variation in solar irradiance, air temperature (T_air), soil temperature (T_soil), vapor pressure deficit (VPD), soil moisture (Soilmoist), humidity (RH), wind speed (V), time of the day (t), cloud cover(CC), crop genetics, leaf angle, leaf emissivity, and sensor view angle need to be further controlled, or compensated through conditional sampling to improve confidence in the results while investigating the relationship between crop stress and crop surface temperature under variable conditions.]

• Although the main questions are addressed, additional experiments in different climatic conditions or with various crop types would strengthen the generalizations in the conclusions​.

Thank you for your comment. We completely agree that further testing of the exergy destruction principle across different crop types and climatic conditions is essential. Future work will include an investigation of various crop types under local climatic conditions. However, we are also open to exploring various climatic conditions if the opportunity arises.

The following paragraph has been added to the conclusions section

[Future considerations could be expanded to include the calculation of cumulative exergy for crop yield production and the exergy related to soil and plant interaction. In addition, different internal mechanisms (e.g., evapotranspiration, respiration,..etc) will be explored to investigate their direct effect on crop stress. Future work will also include testing the current model with different crop types under various climatic conditions.]

• The references are appropriate and include established thermodynamics works and recent studies on energy and exergy analysis in agricultural systems. References to foundational works in thermodynamics lend credibility to the study, while citations of recent research support the relevance of the topic in the context of modern precision agriculture​.
  
  Including well-designed tables and figures is essential for effectively illustrating energy and exergy flows, enhancing the clarity of the study’s results and findings. Tables could summarize key findings, such as energy and exergy balance equations, dominant energy flow terms, and comparisons under different conditions. Each table should be clearly labeled, with specific headings that highlight important metrics like "Energy Contribution by Source" or "Exergy Destruction Rates."

Thank you for your comment, equation description and symbols are now modified in the revised paper. Two tables are presented in this paper. Table 1 summarizes the order of magnitude identification of relevant and negligible terms in the energy balance for a crop plant system at the Elora, ON case study location. Table 2 summarizes the order of magnitude identification of relevant and negligible terms in the exergy balance for a crop plant system at the Elora, ON, case study location. Table 2 presents the main conclusions in this paper and helps the reader to verify that solar exergy dominates all other exergy input and output flow terms shown in Figure 2 and discussed in Equation 7. Now, Figure captions and table headings have been revised.

• Figures are equally important for visualizing the complex dynamics of energy and exergy flow in a simplified manner. Diagrams that depict the input and output energy flows for the plant system, ideally with arrows showing the direction and magnitude of energy or exergy, would help readers understand the system boundaries and energy transformations discussed in the study.

Thank you for your comment, Figure 2 presents energy and mass flow, and it also identifies the crop plant system boundary so the reader can easily follow what energy and mass flows into or out of the system. Figure 3 summarizes the air expansion model that is used for both air and water expansion energy and exergy flows described in this paper.

• Similarly, line or bar charts comparing exergy contributions from various sources under different conditions (e.g., sunny vs. cloudy days) would vividly illustrate the role of solar radiation in exergy flow, supporting the study’s conclusions.

Thank you for your comment, in regard to sunny and cloudy days variation, it has been discussed under the section titled (exergy associated with background radiation). In addition, Figure 4 has been added to compare exergy values under different days (i.e., sunny and cloudy days) based on background temperature.

The following has been added to the revised paper

[Figure 4 below shows the background exergy ratio decreasing with an increasing background temperature. This means cloudy days with higher background temperatures have a lower exergy ratio compared to clear sky conditions.

• Including graphical comparisons under different environmental or operational conditions, such as varying irrigation or nutrient levels, would further demonstrate the model’s applicability. These comparisons could be presented as bar charts or scatter plots to reveal trends or anomalies in exergy flows, allowing readers to understand the factors affecting plant stress as described through exergy analysis.

Thank you for your comment. Figure 1 has been added in the introduction section that highlights the relationship between crop surface temperature and crop stress which also supports the first hypothesis that states stressed crops will exhibit higher surface temperatures during the day compared to less stressed crops, also the regression analysis consistently identified a negative slope.

In conclusion, this paper provides an innovative contribution to understanding plant stress through energy and exergy analysis. It could be further strengthened by some methodological improvements, the addition of control experiments, and further testing under varied conditions, highlighting the importance of clearly labeled tables and figures that effectively illustrate energy and exergy flows.

Reviewer 3 Report

Comments and Suggestions for Authors

I believe that this kind of work is of utmost importance to reveal the energy/exergy balances of our agricultural systems, and as such I find this as an important contribution.

Therefore only a few remarks in the area. The authors should really go through the list of abbreviations very carefully and ensure that they are all explained when used - there seems to be a problem around several of the equations.

I agree that fertilizers should enter such a "model", but then why not also pesticides? Meanwhile, the result would most likely be the same as for the fertilizers. My own research confirms this, but also pointed out that a calculation of cumulative exergy (Cex) or cumulative exergy destruction during the production process is needed to reveal the real environmental loads of this, only if such values are use the exergy comes into play, a mere molecular value as deltaG/H does not reveal this. At present, new fertilizers are more powerful and therefore used in less quantities, and will not contribute significantly to the budget. Besides the importance of pesticides is more a question of quality, whereas fertilizers act directly to enhance quantity - both nutrient deficiency and attacks by various pests are leading to stress.

BTW, how are the exergy value of fertilizer actually calculated. I do not have access to the Beer reference, but usually Szargut and his colleagues are connected to this type of calculations.

References tend to be biased/limited. First of all, I do really miss a scientist like D. Pimentel in the list - he was a very thorough analyst of this type of systems with much less technique involved and probably one of the earliest investgators taking up this the energetics of agriculture as a problem - as well as several other mainly European contributors in the area.

Author Response

I believe that this kind of work is of utmost importance to reveal the energy/exergy balances of our agricultural systems, and as such I find this as an important contribution.

• Therefore only a few remarks in the area. The authors should really go through the list of abbreviations very carefully and ensure that they are all explained when used - there seems to be a problem around several of the equations.

Thank you for your comment. The list of abbreviations has been now moved after each equation to make it easier for the reader to follow up on what was used in the equation and how it was defined along with a set of assumptions.

• I agree that fertilizers should enter such a "model", but then why not also pesticides? Meanwhile, the result would most likely be the same as for the fertilizers. My own research confirms this, but also pointed out that a calculation of cumulative exergy (Cex) or cumulative exergy destruction during the production process is needed to reveal the real environmental loads of this, only if such values are use the exergy comes into play, a mere molecular value as deltaG/H does not reveal this. At present, new fertilizers are more powerful and therefore used in less quantities, and will not contribute significantly to the budget. Besides the importance of pesticides is more a question of quality, whereas fertilizers act directly to enhance quantity - both nutrient deficiency and attacks by various pests are leading to stress.

Thank you for your comment. In regards to the herbicides and pesticides, it will also be dominated by solar exergy which has the same concept as discussed with exergy related to fertilizer input.  For the herbicides, the presence of weeds affects the crop stress level.  As an example, for corn plants if we look at surface temperature for the initial system (i.e., corn with weed) it is expected to be lower compared to corn without weed, which is consistent with the hypotheses that more developed, healthier crop system, will have lower surface temperature during the day compared to non-healthy/less developed crop system. It just happens to be a crop system of weeds versus no weeds.  But as the corn plant starts to grow and develop it will affect the surface temperature, the stress on the corn plants appears, and then at some point it dominates.  We predict that if we were to do daily measurements and did not control weeds we would first see the temperature drop in a corn field due to the presence of weeds, but then eventually become elevated due to the stressed corn.

The following paragraph has been added to the exergy associated with fertilizer input section related to herbicide input

[Furthermore, weeds were controlled under field conditions before corn planting using the herbicide Callisto (Mesotrione, Syngenta) at 0.3 L/ha along with Primextra II Magnum (S-metolachlor and atrazine, Syngenta) at 3.5 L/ha. The total herbicides applied over 1 m² surface area is 22.4×10^-5 kg which is less than 0.015 kg (i.e., fertilizer input), thus the exergy related to herbicide input is 5.17×10^-7 GJ, which is negligible compared to solar exergy. ]

• BTW, how are the exergy value of fertilizer actually calculated. I do not have access to the Beer reference, but usually Szargut and his colleagues are connected to this type of calculations.

Thank you for your comment. In regards to the exergy related to fertilizer input as it was mentioned in the paper “The exergy related to fertilizer input is calculated by considering the average solar and background radiation flux in the Elora, ON, location, which is 1325 W/m² [21], estimated over a surface area of 1 m², during a three-month growing season with 10 hours of sunlight per day, using Ammonium Nitrate as the fertilizer. The total solar energy is 4.29 GJ. The total fertilizer applied with an optimal nitrogen rate of 150 kg N/ha over 1 m² surface area, is 0.015 kg. The Gibbs free energy is 2.3 GJ/tonne. The total exergy related to fertilizer input is 3.45×10-5 GJ. Comparing the Gibbs free energy (which is equivalent to the chemical exergy of the substance) to the solar exergy () yields a value of 0.8×10-5, which is negligible in comparison to solar exergy.” Also to make the calculation clearer it has been modified and more information has been added to the revised paper now highlighted in yellow in [the exergy associated with the fertilizer] section.

In addition, to highlight some important work related to exergy in agriculture and ecology field more literature has been added to the introduction section including the work of Szargut and his colleagues and the work of D. Pimentel . The paragraph reads as follows:

[Many researchers made significant contributions in the field of exergy applied to ecological and agricultural systems. Szargut [34] proposed integrating exergy analysis with ecological concepts to investigate the interactions between human activities and natural systems. In addition, cumulative exergy consumption (CExC) of non-renewable natural resources was introduced, which was utilized to assess various energy limitations in the crop production process [35]. It is defined as the total exergy of all resources utilized and consumed throughout the supply chain of the specified product or process [36]. Furthermore, Szargut [37] applied exergy principles to agricultural systems to evaluate the energy efficiency for crop production. His work focused on analyzing the balance between inputs (e.g., sunlight, fertilizers, water) and outputs (e.g., biomass, yield) to identify opportunities for crop yield optimization. Orrego et al., [38] applied exergy analysis for complex systems such as biological systems including exergy destruction in living organisms. It was found that the exergetic efficiency of plant vegetation is notably low [38]. Many researchers adopted Szargut methodology in calculating the physical and chemical exergy for crop plant systems. 

Furthermore, Pimentel focused on the input–output analysis of agricultural production systems, aimed at demonstrating its ongoing relevance to address complex environmental issues [39] including soil erosion, loss of biodiversity, and biofuel and biomass energy problems. Pimentel and Patzek [40] suggested that living systems can sustain themselves and reproduce if they successfully acquire what they define as "energy input" (exergy within a well-defined system) and eliminate what they classify as "waste" (degraded energy), which was further developed and refined by the Prigogine school of thought [41-43] through the advancement of non-equilibrium thermodynamics. Righetto and Mady [44] performed an exergy analysis of sun–plant interactions in sugarcane cultivation using mathematical models, to estimate plant production and exergy flows while evaluating the photosynthetic efficiency. It was observed that exergy efficiency changes significantly with respect to seasonal changes. Jekayinfa et al., [45] investigated exergy analysis of soybean production in Nigeria. It was found that the exergy-to-energy ratio of certain inputs, such as potassium and phosphorus, exceeds unity. Nikkhah et al., [46] examined the influence of variety selection on the exergy flow within a paddy rice production system, in which nine varieties of rice in Italy, were assessed through the application of the cumulative exergy analysis method. It was found that fossil fuels and chemical fertilizer had the greatest consumption compared to the total energy consumption in all other varieties.]

In the conclusion section the following paragraph has been added for future work

[Future considerations could be expanded to include the calculation of cumulative exergy for crop yield production and the exergy related to soil and plant interaction. In addition, different internal mechanisms (e.g., evapotranspiration, respiration,..etc) will be explored to investigate their direct effect on crop stress. Future work will also include testing the current model with different crop types under various climatic conditions.]

Please refer to the revised paper version as many changes have been conducted including more explanation on the exergy destruction principle applied to complex systems such as crop plant system.

4. References tend to be biased/limited. First of all, I do really miss a scientist like D. Pimentel in the list - he was a very thorough analyst of this type of systems with much less technique involved and probably one of the earliest investigators taking up this the energetics of agriculture as a problem - as well as several other mainly European contributors in the area.

Thank you for your comment. Done, more work has been added to the revised paper.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I sincerely appreciate the effort and meticulous work that the authors have made to respond to my comments in a comprehensive manner. The authors have satisfactorily responded to all my comments/questions and I am pleased to recommend the publication of this article in its present form.

Author Response

I sincerely appreciate the effort and meticulous work that the authors have made to respond to my comments in a comprehensive manner. The authors have satisfactorily responded to all my comments/questions and I am pleased to recommend the publication of this article in its present form.

Response:

Thank you very much. 

Reviewer 2 Report

Comments and Suggestions for Authors

Although the authors have made some progress in improving the content, further revisions are necessary to ensure full compliance with the standards. The keywords are not formatted according to the template requirements. A total of 61 references are listed, but only 49 are cited in the text. The sections "Results" and "Discussion" are combined, but there is no comparison of the obtained results with those from previous studies on the same topic. Additionally, the structure on lines 650 and 651 does not comply with the template requirements.

Author Response

Response:

Thank you for your comments.

• Keywords are now modified based on journal requirements and they are highlighted in yellow in the revised paper.
• Yes 61 references are listed in the reference section and are cited properly based on the journal template in the revised paper text. All the references are highlighted in blue from 1-61.
• Results and discussion sections are now separated, four paragraphs have been added to the discussion section that read as follows:

This study investigates energy, and exergy flows in a crop plant system to identify the dominant flows affecting crop plant health and development. After conducting energy balance, it was found that radiation and transpiration terms dominate all other energy input and output flow terms. For the exergy balance, it was found that solar exergy dominates all exergy input and output flow terms, with the majority of solar exergy either consumed or destroyed by the system through various processes, including photosynthesis and transpiration.

Exergy is utilized as an ecological indicator to evaluate ecosystem development, complexity, and integrity [24,25,26,27,28,29,30,31]. The incoming solar exergy is greater in magnitude compared to the amount of exergy consumed by human activities. The sun provides approximately 13,000 times more exergy compared to what is utilized by humanity [8,20,21]. Solar exergy reaching the Earth's surface sustains life on Earth by driving photosynthesis in crop plant systems, which transforms solar energy into chemical energy [48]. Ecosystems evolve to enhance their capacity to survive in the environment by efficiently utilizing solar exergy from the incoming radiation to sustain their internal organization. The greater the amount of solar exergy an ecosystem captures, the higher its capability to support organizational and survival processes [28,29,30,31]. Consequently, ecosystem development can be assessed by measuring its rate of solar exergy utilization [48,49].

The exergy destruction principle is utilized to explain the relationship between crop surface temperature and crop stress. During the day, the solar exergy input significantly exceeds the exergy output [48,49], in which there is a direct relationship be-tween solar exergy and crop surface temperature as presented in section 2.4.1 where solar exergy can be changed solely by modifying the surface temperature assuming constant solar temperature. It was found that the available solar exergy to a crop plant system is maximized at lower surface temperatures based on the exergy analysis for a crop plant system [48,49], therefore, a crop system's health and development can be assessed using its surface temperature. This study is important to emphasize the sig-nificance of using crop surface temperature as an indicator of crop stress explained by an engineering thermodynamic principle (i.e., the exergy destruction principle).

According to the exergy destruction principle (EDP), more developed and complex ecosystems including a crop plant system exhibit lower surface temperatures during the day compared to less developed ecosystems [30,31, 47,48,49]. Crop plant systems evolve to enhance their efficiency in exergy degradation, as shown by surface temperature measurements, which are consistent with the exergy destruction principal pre-dictions [47,48,49]. Exergy destruction within a crop plant system is determined by the difference between incoming and outgoing exergy flows. The exergy of incoming radiation is the dominant component of these flows. Assuming that a crop plant system receives the same amount of incoming solar energy (i.e., under identical field conditions and environmental parameters), where less stressed and more developed crops will emit energy at a lower exergy level, resulting in a lower surface temperature compared to stressed and less developed crops. Therefore, crop surface temperature can be utilized as a sole measurement for the exergy available to a crop plant system.

• The structure has been modified in Lines 650 and 651.