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Plants
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Plant Stress Physiology Modelling
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Plant Stress Physiology Modelling

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Modeling".

Deadline for manuscript submissions: closed (31 August 2020) | Viewed by 16679

Special Issue Editor

Prof. Dr. William L. Bauerle

E-Mail Website
Guest Editor
Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO 80523, USA
Interests: plant ecophysiology; stress physiology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Multiple environmental factors simultaneously influence plant growth and development. Plant responses to multiple stimuli are seldom uniform throughout the life of a plant. Because a multitude of factors and interactions are closely interwoven and plants are integrated biological entities, plant stress physiological modelling offers a means of understanding and predicting plant dynamic metabolic regulation.

Despite our current understanding of the concomitant responses, there are still open questions and challenges. For example, we lack the ability to adequately predict the impact of fluctuating stress exposure on plant performance. Moreover, we need to understand the environmental impact of discontinuous stress exposure on plant performance over the time frame of a plant’s life cycle. Mathematic biological approaches are needed to examine long‐term abiotic stress constraint in plants. Therefore, in this Special Issue, articles that focus on modeling physiological responses to fluctuating and/or discontinuous plant stress are welcome. Stress response assessments that are integrated over a plant’s life cycle are of special interest to understand the whole‐plant stress response mechanism.

Original research papers, perspectives, hypotheses, opinions, reviews, modeling approaches, and methods that focus on plant stress physiology modelling are welcome, describing dynamic physiological stress response modelling in model plants, crop plants, and tree species.

Prof. Dr. William L. Bauerle
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Plants is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climate variability
  • dynamic stress
  • fluctuating response
  • mechanistic
  • modelling
  • intermittent stress
  • process
  • seasonality

Published Papers (4 papers)

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Research

28 pages, 1554 KiB  
Article
Coupled Gas-Exchange Model for C4 Leaves Comparing Stomatal Conductance Models
by Kyungdahm Yun, Dennis Timlin and Soo-Hyung Kim
Plants 2020, 9(10), 1358; https://doi.org/10.3390/plants9101358 - 14 Oct 2020
Cited by 5 | Viewed by 3374
Abstract
Plant simulation models are abstractions of plant physiological processes that are useful for investigating the responses of plants to changes in the environment. Because photosynthesis and transpiration are fundamental processes that drive plant growth and water relations, a leaf gas-exchange model that couples [...] Read more.
Plant simulation models are abstractions of plant physiological processes that are useful for investigating the responses of plants to changes in the environment. Because photosynthesis and transpiration are fundamental processes that drive plant growth and water relations, a leaf gas-exchange model that couples their interdependent relationship through stomatal control is a prerequisite for explanatory plant simulation models. Here, we present a coupled gas-exchange model for C4 leaves incorporating two widely used stomatal conductance submodels: Ball–Berry and Medlyn models. The output variables of the model includes steady-state values of CO2 assimilation rate, transpiration rate, stomatal conductance, leaf temperature, internal CO2 concentrations, and other leaf gas-exchange attributes in response to light, temperature, CO2, humidity, leaf nitrogen, and leaf water status. We test the model behavior and sensitivity, and discuss its applications and limitations. The model was implemented in Julia programming language using a novel modeling framework. Our testing and analyses indicate that the model behavior is reasonably sensitive and reliable in a wide range of environmental conditions. The behavior of the two model variants differing in stomatal conductance submodels deviated substantially from each other in low humidity conditions. The model was capable of replicating the behavior of transgenic C4 leaves under moderate temperatures as found in the literature. The coupled model, however, underestimated stomatal conductance in very high temperatures. This is likely an inherent limitation of the coupling approaches using Ball–Berry type models in which photosynthesis and stomatal conductance are recursively linked as an input of the other. Full article
(This article belongs to the Special Issue Plant Stress Physiology Modelling)
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14 pages, 1844 KiB  
Article
Leaf Age and Position Effects on Quantum Yield and Photosynthetic Capacity in Hemp Crowns
by William L. Bauerle, Cole McCullough, Megan Iversen and Michael Hazlett
Plants 2020, 9(2), 271; https://doi.org/10.3390/plants9020271 - 19 Feb 2020
Cited by 19 | Viewed by 5855
Abstract
We examined the aging of leaves prior to abscission and the consequences for estimating whole-crown primary production in Cannabis sativa L. (hemp). Leaves at three vertical positions in hemp crowns were examined from initial full leaf expansion until 42 days later. Photosynthetic capacity [...] Read more.
We examined the aging of leaves prior to abscission and the consequences for estimating whole-crown primary production in Cannabis sativa L. (hemp). Leaves at three vertical positions in hemp crowns were examined from initial full leaf expansion until 42 days later. Photosynthetic capacity decreased as leaves aged regardless of crown position, light intensity, or photoperiod. Although leaves remained green, the photosynthetic capacity declined logarithmically to values of 50% and 25% of the maximum 9 and 25 days later, respectively. Plants grown under +450 μmol m−2 s−1 supplemental photosynthetically active radiation or enriched diffuse light responded similarly; there was no evidence that photoperiod or enriched diffuse light modified the gas exchange pattern. At approximately 14 days after full leaf expansion, leaf light levels >500 μmol m−2 s−1 decreased photosynthesis, which resulted in ≥10% lower maximum electron transport rate at ≥ 20 days of growth period. Furthermore, leaves were saturated at lower light levels as leaf age progressed (≤500 μmol m−2 s−1). Incorporating leaf age corrections of photosynthetic physiology is needed when estimating hemp primary production. Full article
(This article belongs to the Special Issue Plant Stress Physiology Modelling)
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20 pages, 2214 KiB  
Article
Using Leaf Temperature to Improve Simulation of Heat and Drought Stresses in a Biophysical Model
by Ruchika S. Perera, Brendan R. Cullen and Richard J. Eckard
Plants 2020, 9(1), 8; https://doi.org/10.3390/plants9010008 - 19 Dec 2019
Cited by 14 | Viewed by 3858
Abstract
Despite evidence that leaf temperatures can differ by several degrees from the air, crop simulation models are generally parameterised with air temperatures. Leaf energy budget is a process-based approach that can be used to link climate and physiological processes of plants, but this [...] Read more.
Despite evidence that leaf temperatures can differ by several degrees from the air, crop simulation models are generally parameterised with air temperatures. Leaf energy budget is a process-based approach that can be used to link climate and physiological processes of plants, but this approach has rarely been used in crop modelling studies. In this study, a controlled environment experiment was used to validate the use of the leaf energy budget approach to calculate leaf temperature for perennial pasture species, and a modelling approach was developed utilising leaf temperature instead of air temperature to achieve a better representation of heat stress impacts on pasture growth in a biophysical model. The controlled environment experiment assessed the impact of two combined seven-day heat (control = 25/15 °C, day/night, moderate = 30/20 °C, day/night, and severe = 35/25 °C, day/night) and drought stresses (with seven-day recovery period between stress periods) on perennial ryegrass (Lolium perenne L.), cocksfoot (Dactylis glomerata L.), tall fescue (Festuca arundinacea Schreb.) and chicory (Cichorium intybus L.). The leaf temperature of each species was modelled by using leaf energy budget equation and validated with measured data. All species showed limited homeothermy with the slope of 0.88 (P < 0.05) suggesting that pasture plants can buffer temperature variations in their growing environment. The DairyMod biophysical model was used to simulate photosynthesis during each treatment, using both air and leaf temperatures, and the patterns were compared with measured data using a response ratio (effect size compared to the well-watered control). The effect size of moderate heat and well-watered treatment was very similar to the measured values (~0.65) when simulated using T leaf, while T air overestimated the consecutive heat stress impacts (0.4 and 0). These results were used to test the heat stress recovery function (Tsum) of perennial ryegrass in DairyMod, finding that recovery after heat stress was well reproduced when parameterized with T sum = 20, while T sum = 50 simulated a long lag phase. Long term pasture growth rate simulations under irrigated conditions in south eastern Australia using leaf temperatures predicted 6–34% and 14–126% higher pasture growth rates, respectively at Ellinbank and Dookie, during late spring and summer months compared to the simulations using air temperatures. This study demonstrated that the simulation of consecutive heat and/or drought stress impacts on pasture production, using DairyMod, can be improved by using leaf temperatures instead of air temperature. Full article
(This article belongs to the Special Issue Plant Stress Physiology Modelling)
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18 pages, 2492 KiB  
Article
Simulation of Phosphorus Chemistry, Uptake and Utilisation by Winter Wheat
by Lianhai Wu, Martin Blackwell, Sarah Dunham, Javier Hernández-Allica and Steve P. McGrath
Plants 2019, 8(10), 404; https://doi.org/10.3390/plants8100404 - 09 Oct 2019
Cited by 12 | Viewed by 2828
Abstract
The phosphorus (P) supply from soils is crucial to crop production. Given the complexity involved in P-cycling, a model that can simulate the major P-cycling processes and link with other nutrients and environmental factors, e.g., soil temperature and moisture, would be a useful [...] Read more.
The phosphorus (P) supply from soils is crucial to crop production. Given the complexity involved in P-cycling, a model that can simulate the major P-cycling processes and link with other nutrients and environmental factors, e.g., soil temperature and moisture, would be a useful tool. The aim of this study was to describe a process-based P module added to the SPACSYS (Soil Plant and Atmosphere Continuum System) model and to evaluate its predictive capability on the dynamics of P content in crops and the impact of soil P status on crop growth. A P-cycling module was developed and linked to other modules included in the SPACSYS model. We used a winter wheat (Triticum aestivum, cv Xi-19) field experiment at Rothamsted Research in Harpenden to calibrate and validate the model. Model performance statistics show that the model simulated aboveground dry matter, P accumulation and soil moisture dynamics reasonably well. Simulated dynamics of soil nitrate and ammonium were close to the observed data when P fertiliser was applied. However, there are large discrepancies in fields without P fertiliser. This study demonstrated that the SPACSYS model was able to investigate the interactions between carbon, nitrogen, P and water in a single process-based model after the tested P module was implemented. Full article
(This article belongs to the Special Issue Plant Stress Physiology Modelling)
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