Modeling Impacts of Changing Environmental Conditions on Plant Growth
A topical collection in Plants (ISSN 2223-7747). This collection belongs to the section "Plant Modeling".
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Editor
Dr. Dominik Schmidt
Dr. Dominik Schmidt
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Collection Editor
Department of Modeling and Systems Analysis, Hochschule Geisenheim University, Von-Lade-Str. 1, 65366 Geisenheim, Germany
Interests: modeling, applied statistics, virtual plants, data science, optimization
Topical Collection Information
Dear Colleagues,
Mathematical models allow addressing complex real world phenomena by simplification. Model building is a constant back and forth of assuming, assessing and adjusting modeling concepts and input parameters. Bringing together various modeling approaches within the field of plant growth modeling can stimulate and expedite this process.
Predicting effects of changing environmental conditions on plant growth is one of these complex phenomena that models can help to get a grip on. Whether these changes are short- or long-term or whether they occur in a controlled environment or in the field, plants do react.
Modeling and predicting these reactions on different stimuli can increase the biological understanding and open up new strategies on how to react to future challenges in plant growth. Ideally, while demonstrating the use of different modeling techniques, cross-realations between environmental factors might be revealed and mechanisms of plant responses can be adapted.
The Special Issue will explore various modeling approaches to study environmental changes affecting plant growth, including mechanistic and empirical models; from classical methods to machine learning methods.
Dr. Dominik Schmidt
Collection Editor
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Keywords
- modeling
- plant response
- climate change
- drought
- heat waves
- light, nutrition
- plant architecture
- in silico
- interactions
Published Papers (13 papers)
Open AccessArticle
Generic and Specific Models for Volume Estimation in Forest and Savanna Phytophysiognomies in Brazilian Cerrado
by
Yanara Ferreira de Souza, Eder Pereira Miguel, Adriano José Nogueira Lima, Álvaro Nogueira de Souza, Eraldo Aparecido Trondoli Matricardi, Alba Valéria Rezende, Joberto Veloso de Freitas, Hallefy Junio de Souza, Kennedy Nunes Oliveira, Maria de Fátima de Brito Lima and Leonardo Job Biali
Viewed by 717
Abstract
The Cerrado has high plant and vertebrate diversity and is an important biome for conserving species and provisioning ecosystem services. Volume equations in this biome are scarce because of their size and physiognomic diversity. This study was conducted to develop specific volumetric models
[...] Read more.
The Cerrado has high plant and vertebrate diversity and is an important biome for conserving species and provisioning ecosystem services. Volume equations in this biome are scarce because of their size and physiognomic diversity. This study was conducted to develop specific volumetric models for the phytophysiognomies Gallery Forest, Dry Forest, Forest Savannah, and Savannah Woodland, a generic model and a model for Cerrado forest formation. Twelve 10 m × 10 m (100 m²) (National Forest Inventory) plots were used for each phytophysiognomy at different sites (regions) of the Federal District (FD) where trees had a diameter at breast height (DBH; 1.30 m) ≥5 cm in forest formations and a diameter at base height (Db; 0.30 m) ≥5 cm in savanna formations. Their diameters and heights were measured, they were cut and cubed, and the volume of each tree was obtained according to the Smalian methodology. Linear and nonlinear models were adjusted. Criteria for the selection of models were determined using correlation coefficients, the standard error of the estimates, and a graphical analysis of the residues. They were later validated by the chi-square test. The resultant models indicated that fit by specific phytophysiognomy was ideal; however, the generic and forest formation models exhibited similar performance to specific models and could be used in extensive areas of the Cerrado, where they represent a high potential for generalization. To further increase our understanding, similar research is recommended for the development of specific and generic models of the total volume in Cerrado areas.
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Open AccessArticle
Relationship between Cumulative Temperature and Light Intensity and G93 Parameters of Isoprene Emission for the Tropical Tree Ficus septica
by
Hirosuke Oku, Asif Iqbal, Shigeki Oogai, Masashi Inafuku and Ishmael Mutanda
Viewed by 1356
Abstract
The most widely used isoprene emission algorithm, G93 formula, estimates instantaneous leaf-level isoprene emission using the basal emission factor and light and temperature dependency parameters. The G93 parameters have been suggested to show variation depending on past weather conditions, but no study has
[...] Read more.
The most widely used isoprene emission algorithm, G93 formula, estimates instantaneous leaf-level isoprene emission using the basal emission factor and light and temperature dependency parameters. The G93 parameters have been suggested to show variation depending on past weather conditions, but no study has closely examined the relationship between past meteorological data and the algorithm parameters. Here, to examine the influence of the past weather on these parameters, we monitored weather conditions, G93 parameters, isoprene synthase transcripts and protein levels, and MEP pathway metabolites in the tropical tree
Ficus septica for 12 days and analyzed their relationship with cumulative temperature and light intensity. Plants were illuminated with varying (ascending and descending) light regimes, and our previously developed Ping-Pong optimization method was used to parameterize G93. The cumulative temperature of the past 5 and 7 days positively correlated with
CT2 and α, respectively, while the cumulative light intensity of the past 10 days showed the highest negative correlation with α. Concentrations of MEP pathway metabolites and
IspS gene expression increased with increasing cumulative temperature. At best, the cumulative temperature of the past 2 days positively correlated with the MEP pathway metabolites and
IspS gene expression, while these factors showed a biphasic positive and negative correlation with cumulative light intensity. Optimized G93 captured well the temperature and light dependency of isoprene emission at the beginning of the experiment; however, its performance significantly decreased for the latter stages of the experimental duration, especially for the descending phase. This was successfully improved through separate optimization of the ascending and descending phases, emphasizing the importance of the optimization of formula parameters and model improvement. These results have important implications for the improvement of isoprene emission algorithms, particularly under the predicted increase in future global temperatures.
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Open AccessArticle
AMMI and GGE Biplot Analyses for Mega-Environment Identification and Selection of Some High-Yielding Oat (Avena sativa L.) Genotypes for Multiple Environments
by
Kibreab Yosefe Wodebo, Taye Tolemariam, Solomon Demeke, Weyessa Garedew, Tessema Tesfaye, Muluken Zeleke, Deribe Gemiyu, Worku Bedeke, Jane Wamatu and Mamta Sharma
Cited by 11 | Viewed by 2168
Abstract
This paper reports an evaluation of eleven oat genotypes in four environments for two consecutive years to identify high-biomass-yielding, stable, and broadly adapted genotypes in selected parts of Ethiopia. Genotypes were planted and evaluated with a randomized complete block design, which was repeated
[...] Read more.
This paper reports an evaluation of eleven oat genotypes in four environments for two consecutive years to identify high-biomass-yielding, stable, and broadly adapted genotypes in selected parts of Ethiopia. Genotypes were planted and evaluated with a randomized complete block design, which was repeated three times. The additive main effect and multiplicative interaction analysis of variances revealed that the environment, genotype, and genotype–environment interaction had a significant (
p ≤ 0.001) influence on the biomass yield in the dry matter base (t ha
−1). The interaction of the first and second principal component analysis accounted for 73.43% and 14.97% of the genotype according to the environment interaction sum of squares, respectively. G6 and G5 were the most stable and widely adapted genotypes and were selected as superior genotypes. The genotype-by-environment interaction showed a 49.46% contribution to the total treatment of sum-of-squares variation, while genotype and environment effects explained 34.94% and 15.60%, respectively. The highest mean yield was obtained from G6 (12.52 kg/ha), and the lowest mean yield was obtained from G7 (8.65 kg/ha). According to the additive main effect and multiplicative interaction biplot, G6 and G5 were high-yielding genotypes, whereas G7 was a low-yielding genotype. Furthermore, according to the genotype and genotype–environment interaction biplot, G6 was the winning genotype in all environments. However, G7 was a low-yielding genotype in all environments. Finally, G6 was an ideal genotype with a higher mean yield and relatively good stability. However, G7 was a poor-yielding and unstable genotype. The genotype, environment, and genotype x environment interaction had extremely important effects on the biomass yield of oats. The findings of the graphic stability methods (additive main effect and multiplicative interaction and the genotype and genotype–environment interaction) for identifying high-yielding and stable oat genotypes were very similar.
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Open AccessArticle
Theoretical Analyses of Turgor Pressure during Stress Relaxation and Water Uptake, and after Changes in Expansive Growth Rate When Water Uptake Is Normal and Reduced
by
Joseph K. E. Ortega
Cited by 2 | Viewed by 5237
Abstract
Turgor pressure provides the force needed to stress and deform the cell walls of plants, algae, and fungi during expansive growth. However, turgor pressure plays another subtle but equally important role in expansive growth of walled cells: it connects the two biophysical processes
[...] Read more.
Turgor pressure provides the force needed to stress and deform the cell walls of plants, algae, and fungi during expansive growth. However, turgor pressure plays another subtle but equally important role in expansive growth of walled cells: it connects the two biophysical processes of water uptake and wall deformation to ensure that the volumetric rates of water uptake and enlargement of the cell wall chamber are equal. In this study, the role of turgor pressure as a ‘connector’ is investigated analytically by employing validated and established biophysical equations. The objective is to determine the effect of ‘wall loosening’ on the magnitude of turgor pressure. It is known that an increase or decrease in turgor pressure and/or wall loosening rate increases or decreases the expansive growth rate, respectively. Interestingly, it is shown that an increase in the wall loosening rate decreases the turgor pressure slightly, thus reducing the effect of wall loosening on increasing the expansive growth rate. Other analyses reveal that reducing the rate of water uptake results in a larger decrease in turgor pressure with the same increase in wall loosening rate, which further reduces the effect of wall loosening on increasing the expansive growth rate.
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Open AccessArticle
Modeling for Predicting the Potential Geographical Distribution of Three Ephedra Herbs in China
by
Longfei Guo, Yu Gao, Ping He, Yuan He and Fanyun Meng
Cited by 10 | Viewed by 2117
Abstract
Ephedra species are beneficial for environmental protection in desert and grassland ecosystems. They have high ecological, medicinal, and economic value. To strengthen the protection of the sustainable development of
Ephedra, we used occurrence records of
Ephedra sinica Stapf.,
Ephedra intermedia Schrenk et
[...] Read more.
Ephedra species are beneficial for environmental protection in desert and grassland ecosystems. They have high ecological, medicinal, and economic value. To strengthen the protection of the sustainable development of
Ephedra, we used occurrence records of
Ephedra sinica Stapf.,
Ephedra intermedia Schrenk et C.A. Mey., and
Ephedra equisetina Bge., combined with climate, soil, and topographic factors to simulate the suitable habitat of three
Ephedra based on ensemble models on the Biomod2 platform. The results of the models were tested using AUC, TSS, and kappa coefficients. The results demonstrated that the ensemble model was able to accurately predict the potential distributions of
E. sinica,
E. intermedia, and
E. equisetina. Eastern and central Inner Mongolia, middle and eastern Gansu, and northeastern Xinjiang were the optimum regions for the growth of
E. sinica,
E. intermedia, and
E. equisetina, respectively. Additionally, several key environmental factors had a significant influence on the suitable habitats of the three
Ephedra. The key factors affecting the distribution of
E. sinica,
E. intermedia, and
E. equisetina were annual average precipitation, altitude, and vapor pressure, respectively. In conclusion, the results showed that the suitable ranges of the three
Ephedra were mainly in Northwest China and that topography and climate were the primary influencing factors.
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Open AccessArticle
Crop Model Parameterisation of Three Important Pearl Millet Varieties for Improved Water Use and Yield Estimation
by
Petrus A. Ausiku, John G. Annandale, Joachim Martin Steyn and Andrew J. Sanewe
Cited by 2 | Viewed by 3526
Abstract
Pearl millet is an important crop for food security in Asia and Africa’s arid and semi-arid regions. It is widely grown as a staple cereal grain for human consumption and livestock fodder. Mechanistic crop growth and water balance models are useful to forecast
[...] Read more.
Pearl millet is an important crop for food security in Asia and Africa’s arid and semi-arid regions. It is widely grown as a staple cereal grain for human consumption and livestock fodder. Mechanistic crop growth and water balance models are useful to forecast crop production and water use. However, very few studies have been devoted to the development of the model parameters needed for such simulations for pearl millet. The objectives of the study were to determine crop-specific model parameters for each of three pearl millet varieties (landrace, hybrid, and improved), as well as to calibrate and validate the Soil Water Balance (SWB) model for predicting pearl millet production and water use based on weather data. The SWB was chosen because it is widely used in southern Africa; however, the developed parameters should benefit other models as well. The presented crop-specific parameter values were derived from field observations and literature. Varieties with different phenology, maturity dates and tillering habits were grown under well-watered and well-fertilised conditions for calibration purposes. The calibrated model was used to predict biomass production, grain yield and crop water use. The hybrid’s water use efficiency was higher than that of the landrace and improved variety.
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Open AccessArticle
Towards a Stochastic Model to Simulate Grapevine Architecture: A Case Study on Digitized Riesling Vines Considering Effects of Elevated CO2
by
Dominik Schmidt, Katrin Kahlen, Christopher Bahr and Matthias Friedel
Cited by 2 | Viewed by 2346
Abstract
Modeling plant growth, in particular with functional-structural plant models, can provide tools to study impacts of changing environments in silico. Simulation studies can be used as pilot studies for reducing the on-field experimental effort when predictive capabilities are given. Robust model calibration leads
[...] Read more.
Modeling plant growth, in particular with functional-structural plant models, can provide tools to study impacts of changing environments in silico. Simulation studies can be used as pilot studies for reducing the on-field experimental effort when predictive capabilities are given. Robust model calibration leads to less fragile predictions, while introducing uncertainties in predictions allows accounting for natural variability, resulting in stochastic plant growth models. In this study, stochastic model components that can be implemented into the functional-structural plant model Virtual Riesling are developed relying on Bayesian model calibration with the goal to enhance the model towards a fully stochastic model. In this first step, model development targeting phenology, in particular budburst variability, phytomer development rate and internode growth are presented in detail. Multi-objective optimization is applied to estimate a single set of cardinal temperatures, which is used in phenology and growth modeling based on a development days approach. Measurements from two seasons of grapevines grown in a vineyard with free-air carbon dioxide enrichment (FACE) are used; thus, model building and selection are coupled with an investigation as to whether including effects of elevated CO
conditions to be expected in 2050 would improve the models. The results show how natural variability complicates the detection of possible treatment effects, but demonstrate that Bayesian calibration in combination with mixed models can realistically recover natural shoot growth variability in predictions. We expect these and further stochastic model extensions to result in more realistic virtual plant simulations to study effects, which are used to conduct in silico studies of canopy microclimate and its effects on grape health and quality.
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Open AccessArticle
Predicting the Potential Suitable Climate for Coconut (Cocos nucifera L.) Cultivation in India under Climate Change Scenarios Using the MaxEnt Model
by
Kukkehalli Balachandra Hebbar, Pulloott Sukumar Abhin, Veliyathukudy Sanjo Jose, Poonchalikundil Neethu, Arya Santhosh, Sandip Shil and P. V. Vara Prasad
Cited by 23 | Viewed by 7126
Abstract
Climate change and climate variability are projected to alter the geographic suitability of lands for crop cultivation. Early awareness of the future climate of the current cultivation areas for a perennial tree crop like coconut is needed for its adaptation and sustainable cultivation
[...] Read more.
Climate change and climate variability are projected to alter the geographic suitability of lands for crop cultivation. Early awareness of the future climate of the current cultivation areas for a perennial tree crop like coconut is needed for its adaptation and sustainable cultivation in vulnerable areas. We analyzed coconut’s vulnerability to climate change in India, based on climate projections for the 2050s and the 2070s under two Representative Concentration Pathways (RCPs): 4.5 and 8.5. Based on the current cultivation regions and climate change predictions from seven ensembles of Global Circulation Models, we predict changes in relative climatic suitability for coconut cultivation using the MaxEnt model. Bioclimatic variables Bio 4 (temperature seasonality, 34.4%) and Bio 7 (temperature annual range, 28.7%) together contribute 63.1%, which along with Bio 15 (precipitation seasonality, 8.6%) determined 71.7% of the climate suitability for coconuts in India. The model projected that some current coconut cultivation producing areas will become unsuitable (plains of South interior Karnataka and Tamil Nadu) requiring crop change, while other areas will require adaptations in genotypic or agronomic management (east coast and the south interior plains), and yet in others, the climatic suitability for growing coconut will increase (west coast). The findings suggest the need for adaptation strategies so as to ensure sustainable cultivation of coconut at least in presently cultivated areas.
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Open AccessArticle
Biophysical Equations and Pressure Probe Experiments to Determine Altered Growth Processes after Changes in Environment, Development, and Mutations
by
Joseph K. E. Ortega
Cited by 1 | Viewed by 2332
Abstract
Expansive growth is a culmination of many biological processes. It is fundamental to volume growth, development, morphogenesis, sensory responses, and environmental responses of plants, fungi, and algae. Expansive growth of walled cells and plant tissue can be accurately described by a set of
[...] Read more.
Expansive growth is a culmination of many biological processes. It is fundamental to volume growth, development, morphogenesis, sensory responses, and environmental responses of plants, fungi, and algae. Expansive growth of walled cells and plant tissue can be accurately described by a set of three global biophysical equations that model the biophysical processes of water uptake, wall deformation, and turgor pressure. Importantly, these biophysical equations have been validated with the results of pressure probe experiments. Here, a systematic method (scheme) is presented that iterates between analyses with the biophysical equations and experiments conducted with the pressure probe. This iterative scheme is used to determine altered growth processes for four cases; two after changes in the environment, one after a change in development, and another after changes by mutation. It is shown that this iterative scheme can identify which biophysical processes are changed, the magnitude of the changes, and their contribution to the change in expansive growth rate. Dimensionless numbers are employed to determine the magnitude of the changes in the biophysical processes. The biological meaning and implication of the biophysical variables in the biophysical equations are discussed. Further, additional sets of global biophysical equations are presented and discussed.
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Open AccessArticle
Validating a Simple Mechanistic Model That Describes Weather Impact on Pasture Growth
by
Edward B. Rayburn
Cited by 2 | Viewed by 1870
Abstract
Mathematical models have many uses. When input data is limited, simple models are required. This occurs in pasture agriculture when managers typically only have access to temperature and rainfall values. A simple pasture growth model was developed that requires only latitude and daily
[...] Read more.
Mathematical models have many uses. When input data is limited, simple models are required. This occurs in pasture agriculture when managers typically only have access to temperature and rainfall values. A simple pasture growth model was developed that requires only latitude and daily maximum and minimum temperature and rainfall. The accuracy of the model was validated using ten site-years of measured pasture growth at a site under continuous stocking where management controlled the height of grazing (HOG) and a site under rotational stocking at a West Virginia University farm (WVU). Relative forage growth, expressed as a fraction of maximum growth observed at the sites, was reasonably accurate. At the HOG site constant bias in relative growth was not different from zero. There was a year effect due to the weather station used for predicting growth at HOG being 1.8 km from the pasture. However, the error was only about 10-percent. At the WVU site constant bias for relative growth was not different from zero and year effect was eliminated when adjusted for nitrogen status of the treatments. This simple model described relative pasture growth within 10-percent of average for a given site, environment, and management using only daily weather inputs that are readily available. Using predictions of climate change impact on temperature and rainfall frequency and intensity this model can be used to predict the impact on pasture growth.
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Open AccessArticle
The Potential of Deep Roots to Mitigate Impacts of Heatwaves and Declining Rainfall on Pastures in Southeast Australia
by
Rachelle Meyer, Alexandria Sinnett, Ruchika Perera, Brendan Cullen, Bill Malcolm and Richard J. Eckard
Cited by 3 | Viewed by 2586
Abstract
Declines in growing-season rainfall and increases in the frequency of heatwaves in southern Australia necessitate effective adaptation. The Sustainable Grazing Systems Pasture Model (SGS) was used to model the growth of three pasture species differing in root depth and root distribution under three
[...] Read more.
Declines in growing-season rainfall and increases in the frequency of heatwaves in southern Australia necessitate effective adaptation. The Sustainable Grazing Systems Pasture Model (SGS) was used to model the growth of three pasture species differing in root depth and root distribution under three different climate scenarios at two sites. The modelled metabolisable energy intake (in MJ) was used in a partial discounted net cash flow budget. Both the biophysical and economic modelling suggest that deep roots were advantageous in all climate scenarios at the long growing season site but provided no to little advantage at the short growing season site, likely due to the deep-rooted species drying out the soil profile earlier. In scenarios including climate change, the DM production of the deep-rooted species at the long growing season site averaged 386 kg/ha/year more than the more shallow-rooted species, while at the site with a shorter growing season it averaged 205 kg/ha/year less than the shallower-rooted species. The timing of the extra growth and pasture persistence strongly influenced the extent of the benefit. At the short growing season site other adaptation options such as summer dormancy will likely be necessary.
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Open AccessArticle
Probabilistic Provenance Detection and Management Pathways for Pseudotsuga menziesii (Mirb.) Franco in Italy Using Climatic Analogues
by
Maurizio Marchi and Claudia Cocozza
Cited by 6 | Viewed by 2368
Abstract
The introduction of Douglas-fir [
Pseudotsuga menziesii (Mirb.) Franco] in Europe has been one of the most important and extensive silvicultural experiments since the 1850s. This success was mainly supported by the species’ wide genome and phenotypic plasticity even if the genetic origin
[...] Read more.
The introduction of Douglas-fir [
Pseudotsuga menziesii (Mirb.) Franco] in Europe has been one of the most important and extensive silvicultural experiments since the 1850s. This success was mainly supported by the species’ wide genome and phenotypic plasticity even if the genetic origin of seeds used for plantations is nowadays often unknown. This is especially true for all the stands planted before the IUFRO experimentation in the 1960s. In this paper, a methodology to estimate the Douglas-fir provenances currently growing in Italy is proposed. The raw data from the last Italian National Forest Inventory were combined with literature information to obtain the current spatial distribution of the species in the country representing its successful introduction. Afterwards, a random forest classification model was run using downscaled climatic data as predictors and the classification scheme adopted in previous research studies in the Pacific North West of America. The analysis highlighted good matching between the native and the introduction range in Italy. Coastal provenances from British Columbia and the dry coast of Washington were detected as the most likely seed sources, covering 63.4% and 33.8% of the current distribution of the species in the country, respectively. Interior provenances and those from the dry coast of Oregon were also represented but limited to very few cases. The extension of the model on future scenarios predicted a gradual shift in suitable provenances with the dry coast of Oregon in the mid-term (2050s) and afterwards California (2080s) being highlighted as possible new seed sources. However, only further analysis with genetic markers and molecular methods will be able to confirm the proposed scenarios. A validation of the genotypes currently available in Italy will be mandatory as well as their regeneration processes (i.e., adaptation), which may also diverge from those occurring in the native range due to a different environmental pressure. This new information will also add important knowledge, allowing a refinement of the proposed modeling framework for a better support for forest managers.
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Open AccessArticle
Growth Indicators of Main Species Predict Aboveground Biomass of Population and Community on a Typical Steppe
by
Xiaojuan Huang, Yongjie Liu, Niya Wang, Lan Li, An Hu, Zhen Wang, Shenghua Chang, Xianjiang Chen and Fujiang Hou
Cited by 1 | Viewed by 2313
Abstract
The objective was to explore a fast, accurate, non-destructive, and less disturbance method for predicting the aboveground biomass (AGB) of the typical steppe, by using plant height and canopy diameter of the dominant species,
Stipa bungeana,
Artemisia capillaris, and
Lespedeza davurica
[...] Read more.
The objective was to explore a fast, accurate, non-destructive, and less disturbance method for predicting the aboveground biomass (AGB) of the typical steppe, by using plant height and canopy diameter of the dominant species,
Stipa bungeana,
Artemisia capillaris, and
Lespedeza davurica, data were observed from 165 quadrats during the peak plant growing season, and the product of plant height (PH) and canopy diameter (PC) were calculated for each species. AGB of population were predicted for the same species and other species through using 2/3 of the measured data, and the optimal predictive equation was linear in terms of determination coefficient. The other 1/3 of the data, which was measured from no grazing paddocks or rotational grazing paddocks, was substituted into the predictive equations for validation. Results showed that PC of one dominant species could be used to predict AGB of the same species or other species well. The predicted and measured values were significantly correlative, and most of the predictive accuracy was above 80%, and not affected by managements of grassland, including rotational grazing or no grazing. A combination of 3 to 6 representative species was used to predict AGB of the community, and the predictive equations with PC of six species as an independent variable were the most optimal because explaining 83.5% variation of AGB. The predictive methods cost 1/15, 1/9, and 1/51 of time, labor, and capital as much as the destructive sample method (quadrat sampling method), respectively, and thus improved the efficiency of field study and protecting the fragile study areas, especially the long-term study sites in grassland.
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Planned Papers
The below list represents only planned manuscripts. Some of these
manuscripts have not been received by the Editorial Office yet. Papers
submitted to MDPI journals are subject to peer-review.
Title: Selection of dwarf tomato F2RC3 populations by computational intelligence techniques
Authors: José Magno Queiroz Luz
Affiliation: Universidade Federal de Uberlandia
Abstract: The objective of the work was to estimate genetic divergence and select F3RC1 populations of dwarf tomato by computational intelligence techniques. The experiment was conducted in a greenhouse at the Experimental Vegetable Station of the Federal University of Uberlândia (UFU), Monte Carmelo. A randomized block design with 17 treatments and four replications was used. The genetic material evaluated consisted of thirteen dwarf tomato populations obtained by a backcross and two self-fertilizations, plus both parents (recurrent and donor) and two commercial cultivars. The characteristics evaluated were: average fruit weight, soluble solids content, fruit diameter, fruit length, fruit shape, pulp thickness, number of locules, length between internodes and levels of acyl sugar, β-carotene and lycopene. The data were analyzed by means test and the genetic divergence was measured using the Generalized Mahalanobis Distance using the hierarchical method of Average Link between groups (UPGMA) and through computational intelligence using Kohonen's Self-Organizing Maps (SOUND). Through both methodologies it was possible to confirm the genetic dissimilarity in relation to the donor parent. However, SOM was able to detect differences and organize similarities between populations in a more coherent way, resulting in a greater number of groups. In addition, computational intelligence techniques enable the verification of the weights of each variable in the formation of groups. Among the F3RC1 populations, UFU-SC # 3 and UFU-SC # 5 stood out for agronomic characters and UFU-SC # 10 and UFU-SC # 11 for quality parameters.
Title: Growth Indicators of Dominant Species Predicting the Aboveground Biomass of Population and Community on Typical Steppe
Authors: Fujiang Hou
Affiliation: State Key Laboratory of Grassland Agro‐ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, 730020 China
Abstract: The CH of dominant species as the independent variable to predict the abovemention biomass of other populations and communities, and the accuracy and stability of the prediction model are verified. The results showed that the CH of dominant species can be used to predict the aboveground biomass of this population, other populations and communities, the linear regression model has the best prediction effect. The aboveground biomass population prediction, model of the total relative error RS < 10% and the average relative error absolute value RMA < 30%, as well the forecasting precision were over 75% and showed high accuracy and stability. Prediction of aboveground biomass of typical steppe communities can greatly reduce the labour intensity and improve the labour efficiency.
Title: The determination of expansive growth processes during changing environmental conditions using pressure probe tests and analyses with dimensionless numbers
Authors: Joseph K. E. Ortega
Affiliation: Professor Emeritus, Department of Mechanical Engineering, University of Colorado Denver, Denver, CO 80217-3364, USA
Abstract: Volumetric growth of plants during development, morphogenesis, and sensory responses depends on the expansive growth of individual plant cells. The expansive growth rate of the individual plant cell is a function of the rates of two interrelated and simultaneous processes: net water uptake and wall deformation. Biophysical equations describing the net water uptake (osmotic water uptake minus water loss by transpiration), wall deformation (plastic and elastic deformation), and turgor pressure (that couples the water uptake and wall deformation processes) have been previously derived and validated with experimental results from pressure probe experiments [1, 2]. Dimensionless biophysical equations have been obtained using dimensional analysis. The coefficients of the terms in the dimensionless equations are dimensionless numbers composed of combinations of the biophysical variables in the dimensional biophysical equations. It is noted that the dimensionless numbers describe the magnitude of the individual components of net water uptake rate (osmotic water uptake rate and transpiration rate) and wall deformation rate (plastic and elastic deformation rate) [3, 4]. In this paper, analyses employing dimensionless numbers are conducted to show how the magnitudes of the expansive growth processes during normal growth conditions and after changes in environmental conditions can be determined and compared. It is shown that when the expansive growth rate is altered after changes in environmental conditions, it is possible to determine which of the biophysical processes (water uptake rate, transpiration rate, plastic wall deformation rate, and elastic wall deformation rate) have changed. Importantly, the magnitude of the changes can be determined. Thus it is possible to assess which changes significantly contribute to the change in expansive growth rate and which are extraneous. Also presented in this paper is a review of the pressure probe tests that can used to determine the values (magnitudes) of biophysical variables used in the dimensionless numbers.
References
1. Geitmann, A.; Ortega, J.K.E. Mechanics and modeling of plant cell growth. Trends Plant Sci. 2009, 14, 467–478.
2. Ortega, J.K.E. Plant cell growth in tissue. Plant Physiol. 2010, 154, 1244–1253.
3. Ortega, J.K.E. Dimensionless numbers for plant biology. Trends Plant Sci. 2018, 23, 6–9.
4. Ortega, J. K. E. Dimensionless numbers to analyze expansive growth processes. Plants 2019, 8, 17; doi:10.3390/plants8010017
