Pub Date : 2021-12-04DOI: 10.1093/insilicoplants/diab037
N. Gaudio, G. Louarn, R. Barillot, Clémentine Meunier, Rémi Vezy, M. Launay
Promoting plant diversity through crop mixtures is a mainstay of the agroecological transition. Modelling this transition requires considering both plant-plant interactions and plants’ interactions with abiotic and biotic environments. Modelling crop mixtures enables designing ways to use plant diversity to provide ecosystem services, as long as they include crop management as input. A single modelling approach is not sufficient, however, and complementarities between models may be critical to consider the multiple processes and system components involved at different and relevant spatial and temporal scales. In this article, we present different modelling solutions implemented in a variety of examples to upscale models from local interactions to ecosystem services. We highlight that modelling solutions (i.e. coupling, metamodelling, inverse or hybrid modelling) are built according to modelling objectives (e.g. understand the relative contributions of primary ecological processes to crop mixtures, quantify impacts of the environment and agricultural practices, assess the resulting ecosystem services) rather than to the scales of integration. Many outcomes of multispecies agroecosystems remain to be explored, both experimentally and through the heuristic use of modelling. Combining models to address plant diversity and predict ecosystem services at different scales remains rare but is critical to support the spatial and temporal prediction of the many systems that could be designed.
{"title":"Exploring complementarities between modelling approaches that enable upscaling from plant community functioning to ecosystem services as a way to support agroecological transition","authors":"N. Gaudio, G. Louarn, R. Barillot, Clémentine Meunier, Rémi Vezy, M. Launay","doi":"10.1093/insilicoplants/diab037","DOIUrl":"https://doi.org/10.1093/insilicoplants/diab037","url":null,"abstract":"\u0000 Promoting plant diversity through crop mixtures is a mainstay of the agroecological transition. Modelling this transition requires considering both plant-plant interactions and plants’ interactions with abiotic and biotic environments. Modelling crop mixtures enables designing ways to use plant diversity to provide ecosystem services, as long as they include crop management as input. A single modelling approach is not sufficient, however, and complementarities between models may be critical to consider the multiple processes and system components involved at different and relevant spatial and temporal scales. In this article, we present different modelling solutions implemented in a variety of examples to upscale models from local interactions to ecosystem services. We highlight that modelling solutions (i.e. coupling, metamodelling, inverse or hybrid modelling) are built according to modelling objectives (e.g. understand the relative contributions of primary ecological processes to crop mixtures, quantify impacts of the environment and agricultural practices, assess the resulting ecosystem services) rather than to the scales of integration. Many outcomes of multispecies agroecosystems remain to be explored, both experimentally and through the heuristic use of modelling. Combining models to address plant diversity and predict ecosystem services at different scales remains rare but is critical to support the spatial and temporal prediction of the many systems that could be designed.","PeriodicalId":36138,"journal":{"name":"in silico Plants","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42968471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-29DOI: 10.1093/insilicoplants/diab036
A. Masson, Y. Caraglio, E. Nicolini, P. Borianne, J. Barczi
Tree structural and biomass growth studies mainly focus on the shoot compartment. Tree roots usually have to be taken apart due to the difficulties involved in measuring and observing this compartment, particularly root growth. In the context of climate change, the study of tree structural plasticity has become crucial and both shoot and root systems need to be considered simultaneously as they play a joint role in adapting traits to climate change (water availability for roots and light or carbon availability for shoots). We developed a botanically accurate whole-plant model and its simulator (RoCoCau) with a linkable external module (TOY) to represent shoot and root compartment dependencies and hence tree structural plasticity in different air and soil environments. This paper describes a new deep neural network calibration trained on simulated datasets computed from a set of more than 360 000 random TOY parameter values and random climate values. These datasets were used for training and for validation. For this purpose, we chose Voxnet, a convolutional neural network designed to classify 3D objects represented as a voxelized scene. We recommend further improvements for Voxnet inputs, outputs, and training. We were able to teach the network to predict the value of environment data well (mean error < 2%), and to predict the value of TOY parameters for plants under water stress conditions (mean error < 5% for all parameters), and for any environmental growing conditions (mean error < 20%).
{"title":"Modelling the functional dependency between root and shoot compartments to predict the impact of the environment on the architecture of the whole plant. Methodology for model fitting on simulated data using Deep Learning techniques","authors":"A. Masson, Y. Caraglio, E. Nicolini, P. Borianne, J. Barczi","doi":"10.1093/insilicoplants/diab036","DOIUrl":"https://doi.org/10.1093/insilicoplants/diab036","url":null,"abstract":"\u0000 Tree structural and biomass growth studies mainly focus on the shoot compartment. Tree roots usually have to be taken apart due to the difficulties involved in measuring and observing this compartment, particularly root growth. In the context of climate change, the study of tree structural plasticity has become crucial and both shoot and root systems need to be considered simultaneously as they play a joint role in adapting traits to climate change (water availability for roots and light or carbon availability for shoots). We developed a botanically accurate whole-plant model and its simulator (RoCoCau) with a linkable external module (TOY) to represent shoot and root compartment dependencies and hence tree structural plasticity in different air and soil environments. This paper describes a new deep neural network calibration trained on simulated datasets computed from a set of more than 360 000 random TOY parameter values and random climate values. These datasets were used for training and for validation. For this purpose, we chose Voxnet, a convolutional neural network designed to classify 3D objects represented as a voxelized scene. We recommend further improvements for Voxnet inputs, outputs, and training. We were able to teach the network to predict the value of environment data well (mean error < 2%), and to predict the value of TOY parameters for plants under water stress conditions (mean error < 5% for all parameters), and for any environmental growing conditions (mean error < 20%).","PeriodicalId":36138,"journal":{"name":"in silico Plants","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42422438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-05DOI: 10.1093/insilicoplants/diab034
Marion Gauthier, R. Barillot, B. Andrieu
Phenotypic plasticity - the ability of one genotype to produce different phenotypes depending on growth conditions - is a core aspect of the interactions between plants and the environment. The model CN-Wheat simulates the functioning of a grass culm and the construction of traits as properties emerging from the feedback loops between morphogenesis, the environmental factors and source–sink activities. The plant is seen as a self-regulated system where leaf growth is driven by carbon and nitrogen metabolism within each leaf and by coordination rules between successive leaves. Here, we investigated the ability of this approach to simulate realistic grass phenotypic plasticity and explored plant behaviour in a wide range of growth conditions.The growth of grass monoculms, with traits similar to a wheat stem, was simulated for highly contrasting conditions of soil nitrogen concentration, incident light and planting density. The monoculms were kept vegetative and produced ~15 mature leaves at the end of the simulations. The model simulated highly contrasting phenotypes. Overall, the simulated trends and the magnitude of responses of leaf and plant traits to growth conditions were consistent with the literature on grass species. These results demonstrate that integrating plant functioning at organ scale can simulate, as an emergent property, the phenotypic plasticity of plants in contrasting light and nitrogen conditions. Besides, simulations of the internal variables of plants gave access to plant trophic status across plant ontogeny and plant environments. In conclusion, this framework is a significant step towards better integration of the genotype-environment interactions.
{"title":"Simulating grass phenotypic plasticity as an emergent property of growth zone responses to carbon and nitrogen metabolites","authors":"Marion Gauthier, R. Barillot, B. Andrieu","doi":"10.1093/insilicoplants/diab034","DOIUrl":"https://doi.org/10.1093/insilicoplants/diab034","url":null,"abstract":"\u0000 Phenotypic plasticity - the ability of one genotype to produce different phenotypes depending on growth conditions - is a core aspect of the interactions between plants and the environment. The model CN-Wheat simulates the functioning of a grass culm and the construction of traits as properties emerging from the feedback loops between morphogenesis, the environmental factors and source–sink activities. The plant is seen as a self-regulated system where leaf growth is driven by carbon and nitrogen metabolism within each leaf and by coordination rules between successive leaves. Here, we investigated the ability of this approach to simulate realistic grass phenotypic plasticity and explored plant behaviour in a wide range of growth conditions.The growth of grass monoculms, with traits similar to a wheat stem, was simulated for highly contrasting conditions of soil nitrogen concentration, incident light and planting density. The monoculms were kept vegetative and produced ~15 mature leaves at the end of the simulations. The model simulated highly contrasting phenotypes. Overall, the simulated trends and the magnitude of responses of leaf and plant traits to growth conditions were consistent with the literature on grass species. These results demonstrate that integrating plant functioning at organ scale can simulate, as an emergent property, the phenotypic plasticity of plants in contrasting light and nitrogen conditions. Besides, simulations of the internal variables of plants gave access to plant trophic status across plant ontogeny and plant environments. In conclusion, this framework is a significant step towards better integration of the genotype-environment interactions.","PeriodicalId":36138,"journal":{"name":"in silico Plants","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46631205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-14DOI: 10.1093/insilicoplants/diab031
Yi-Chen Pao, K. Kahlen, Tsu-Wei Chen, Dirk Wiechers, H. Stützel
One-dimensional light models using the Beer-Lambert equation (BL) with the light extinction coefficient k are simple and robust tools for estimating light interception of homogeneous canopies. Functional-structural plant models (FSPMs) are powerful to capture light-plant interactions in heterogeneous canopies, but they are also more complex due to explicit descriptions of three-dimensional plant architecture and light models. For choosing an appropriate modelling approach, the trade-offs between simplicity and accuracy need to be considered when canopies with spatial heterogeneity are concerned. We compared two light modelling approaches, one following BL and another using ray tracing (RT), based on a framework of a dynamic FSPM of greenhouse cucumber. Resolutions of hourly-step (HS) and daily-step (DS) were applied to simulate light interception, leaf-level photosynthetic acclimation and plant-level dry matter production over growth periods of two to five weeks. Results showed that BL-HS was comparable to RT-HS in predicting shoot dry matter and photosynthetic parameters. The k used in the BL approach was simulated using an empirical relationship between k and leaf area index established with the assistance of RT, which showed variation up to 0.2 in k depending on canopy geometry under the same plant density. When a constant k value was used instead, a difference of 0.2 in k resulted in up to 27% loss in accuracy for shoot dry matter. These results suggested that, with the assistance of RT in k estimation, the simple approach BL-HS provided efficient estimation for long-term processes.
{"title":"How does structure matter? Comparison of canopy photosynthesis using one- and three-dimensional light models: a case study using greenhouse cucumber canopies","authors":"Yi-Chen Pao, K. Kahlen, Tsu-Wei Chen, Dirk Wiechers, H. Stützel","doi":"10.1093/insilicoplants/diab031","DOIUrl":"https://doi.org/10.1093/insilicoplants/diab031","url":null,"abstract":"\u0000 One-dimensional light models using the Beer-Lambert equation (BL) with the light extinction coefficient k are simple and robust tools for estimating light interception of homogeneous canopies. Functional-structural plant models (FSPMs) are powerful to capture light-plant interactions in heterogeneous canopies, but they are also more complex due to explicit descriptions of three-dimensional plant architecture and light models. For choosing an appropriate modelling approach, the trade-offs between simplicity and accuracy need to be considered when canopies with spatial heterogeneity are concerned. We compared two light modelling approaches, one following BL and another using ray tracing (RT), based on a framework of a dynamic FSPM of greenhouse cucumber. Resolutions of hourly-step (HS) and daily-step (DS) were applied to simulate light interception, leaf-level photosynthetic acclimation and plant-level dry matter production over growth periods of two to five weeks. Results showed that BL-HS was comparable to RT-HS in predicting shoot dry matter and photosynthetic parameters. The k used in the BL approach was simulated using an empirical relationship between k and leaf area index established with the assistance of RT, which showed variation up to 0.2 in k depending on canopy geometry under the same plant density. When a constant k value was used instead, a difference of 0.2 in k resulted in up to 27% loss in accuracy for shoot dry matter. These results suggested that, with the assistance of RT in k estimation, the simple approach BL-HS provided efficient estimation for long-term processes.","PeriodicalId":36138,"journal":{"name":"in silico Plants","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48969159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-09DOI: 10.1093/insilicoplants/diab030
D. Holloway, C. Wenzel
The growth regulator auxin plays a central role in the phyllotaxy, shape, and venation patterns of leaves. The auxin spatial localization underlying these phenomena involves polar auxin transport (PAT) at the cellular level, particularly the preferential allocation of PIN efflux proteins to certain areas of the plasma membrane. Two general mechanisms have been studied: an up-the-gradient (UTG) allocation dependent on neighbouring-cell auxin concentrations, and a with-the-flux (WTF) allocation dependent on the flow of auxin across walls. We have developed a combined UTG+WTF model to quantify the observed auxin flows both towards (UTG) and away from (WTF) auxin maxima during primary and secondary vein patterning in leaves. The model simulates intracellular and membrane kinetics and intercellular transport, and is solved for a 2D leaf of several hundred cells. In addition to normal development, modelling of increasing PAT inhibition generates, as observed experimentally: a switch from several distinct vein initiation sites to many less-distinct sites; a delay in vein canalization; inhibited connection of new veins to old; and finally loss of patterning in the margin, loss of vein extension, and confinement of auxin to the margin. The model generates the observed formation of discrete auxin maxima at leaf vein sources and shows the dependence of secondary vein patterning on the efficacy of auxin flux through cells. Simulations of vein patterning and leaf growth further indicate that growth itself may bridge the spatial scale from the cell-cell resolution of the PIN-auxin dynamics to vein patterns on the whole-leaf scale.
{"title":"Polar auxin transport dynamics of primary and secondary vein patterning in dicot leaves","authors":"D. Holloway, C. Wenzel","doi":"10.1093/insilicoplants/diab030","DOIUrl":"https://doi.org/10.1093/insilicoplants/diab030","url":null,"abstract":"\u0000 The growth regulator auxin plays a central role in the phyllotaxy, shape, and venation patterns of leaves. The auxin spatial localization underlying these phenomena involves polar auxin transport (PAT) at the cellular level, particularly the preferential allocation of PIN efflux proteins to certain areas of the plasma membrane. Two general mechanisms have been studied: an up-the-gradient (UTG) allocation dependent on neighbouring-cell auxin concentrations, and a with-the-flux (WTF) allocation dependent on the flow of auxin across walls. We have developed a combined UTG+WTF model to quantify the observed auxin flows both towards (UTG) and away from (WTF) auxin maxima during primary and secondary vein patterning in leaves. The model simulates intracellular and membrane kinetics and intercellular transport, and is solved for a 2D leaf of several hundred cells. In addition to normal development, modelling of increasing PAT inhibition generates, as observed experimentally: a switch from several distinct vein initiation sites to many less-distinct sites; a delay in vein canalization; inhibited connection of new veins to old; and finally loss of patterning in the margin, loss of vein extension, and confinement of auxin to the margin. The model generates the observed formation of discrete auxin maxima at leaf vein sources and shows the dependence of secondary vein patterning on the efficacy of auxin flux through cells. Simulations of vein patterning and leaf growth further indicate that growth itself may bridge the spatial scale from the cell-cell resolution of the PIN-auxin dynamics to vein patterns on the whole-leaf scale.","PeriodicalId":36138,"journal":{"name":"in silico Plants","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49141313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-27DOI: 10.1093/insilicoplants/diab026
R. Janoutová, L. Homolová, J. Novotný, B. Navrátilová, M. Pikl, Z. Malenovský
This study presents a method for three-dimensional (3D) reconstruction of forest tree species that are, for instance, required for simulations of 3D canopies in radiative transfer modelling. We selected three forest species of different architecture: Norway spruce (Picea abies) and European beech (Fagus sylvatica), representatives of European production forests, and white peppermint (Eucalyptus pulchella), a common forest species of Tasmania. Each species has a specific crown structure and foliage distribution. Our algorithm for 3D model construction of a single tree is based on terrestrial laser scanning (TLS) and ancillary field measurements of leaf angle distribution, percentage of current-year and older leaves, and other parameters that could not be derived from TLS data. The algorithm comprises four main steps: i) segmentation of a TLS tree point cloud separating wooden parts from foliage, ii) reconstruction of wooden parts (trunks and branches) from TLS data, iii) biologically genuine distribution of foliage within the tree crown, and iv) separation of foliage into two age categories (for spruce trees only). The reconstructed 3D models of the tree species were used to build virtual forest scenes in the DART model and to simulate canopy optical signals, specifically: angularly anisotropic top-of-canopy reflectance (for retrieval of leaf biochemical compounds from nadir canopy reflectance signatures captured in airborne imaging spectroscopy data) and solar-induced chlorophyll fluorescence signal (for experimentally unfeasible sensitivity analyses).
{"title":"Detailed reconstruction of trees from terrestrial laser scans for remote sensing and radiative transfer modelling applications","authors":"R. Janoutová, L. Homolová, J. Novotný, B. Navrátilová, M. Pikl, Z. Malenovský","doi":"10.1093/insilicoplants/diab026","DOIUrl":"https://doi.org/10.1093/insilicoplants/diab026","url":null,"abstract":"This study presents a method for three-dimensional (3D) reconstruction of forest tree species that are, for instance, required for simulations of 3D canopies in radiative transfer modelling. We selected three forest species of different architecture: Norway spruce (Picea abies) and European beech (Fagus sylvatica), representatives of European production forests, and white peppermint (Eucalyptus pulchella), a common forest species of Tasmania. Each species has a specific crown structure and foliage distribution. Our algorithm for 3D model construction of a single tree is based on terrestrial laser scanning (TLS) and ancillary field measurements of leaf angle distribution, percentage of current-year and older leaves, and other parameters that could not be derived from TLS data. The algorithm comprises four main steps: i) segmentation of a TLS tree point cloud separating wooden parts from foliage, ii) reconstruction of wooden parts (trunks and branches) from TLS data, iii) biologically genuine distribution of foliage within the tree crown, and iv) separation of foliage into two age categories (for spruce trees only). The reconstructed 3D models of the tree species were used to build virtual forest scenes in the DART model and to simulate canopy optical signals, specifically: angularly anisotropic top-of-canopy reflectance (for retrieval of leaf biochemical compounds from nadir canopy reflectance signatures captured in airborne imaging spectroscopy data) and solar-induced chlorophyll fluorescence signal (for experimentally unfeasible sensitivity analyses).","PeriodicalId":36138,"journal":{"name":"in silico Plants","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44681925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-12DOI: 10.1093/insilicoplants/diab024
Junqi Zhu, F. Gou, G. Rossouw, Fareeda Begum, M. Henke, Ella Johnson, B. Holzapfel, Stewart K. Field, A. Seleznyova
Variability in fruit quality greatly impedes the profitability of an orchard. Modelling can help find the causes of quality variability. However, studies suggest that the common assimilate pool model is inadequate in terms of describing variability in organ biomass. The aim of the current study was to compare the performances of the common assimilate pool and phloem carbohydrate transport models in simulating phloem carbohydrate concentration and organ biomass variability within the whole-plant functional-structural grapevine (Vitis vinifera L.) model that we developed previously. A statistical approach was developed for calibrating the model with a detailed potted experiment that entails three levels of leaf area per vine during the fruit ripening period. Global sensitivity analysis illustrated that carbohydrate allocation changed with the amount of leaf area as well as the limiting factors for organ biomass development. Under a homogenous canopy architecture where all grape bunches were equally close to the carbohydrate sources, the common assimilate pool and phloem transport models produced very similar results. However, under a heterogeneous canopy architecture with variable distance between bunches and carbohydrate sources, the coefficient of variation for fruit biomass rose from 0.01 to 0.17 as crop load increased. These results indicate that carbohydrate allocation to fruits is affected by both the size of crop load and fruit distribution, which is not adequately described by the common assimilate pool model. The new grapevine model can also simulate dynamic canopy growth and be adapted to help optimise canopy architecture and quality variability of other perennial fruit crops.
{"title":"Simulating organ biomass variability and carbohydrate distribution in perennial fruit crops: a comparison between the common assimilate pool and phloem carbohydrate transport models","authors":"Junqi Zhu, F. Gou, G. Rossouw, Fareeda Begum, M. Henke, Ella Johnson, B. Holzapfel, Stewart K. Field, A. Seleznyova","doi":"10.1093/insilicoplants/diab024","DOIUrl":"https://doi.org/10.1093/insilicoplants/diab024","url":null,"abstract":"\u0000 Variability in fruit quality greatly impedes the profitability of an orchard. Modelling can help find the causes of quality variability. However, studies suggest that the common assimilate pool model is inadequate in terms of describing variability in organ biomass. The aim of the current study was to compare the performances of the common assimilate pool and phloem carbohydrate transport models in simulating phloem carbohydrate concentration and organ biomass variability within the whole-plant functional-structural grapevine (Vitis vinifera L.) model that we developed previously. A statistical approach was developed for calibrating the model with a detailed potted experiment that entails three levels of leaf area per vine during the fruit ripening period. Global sensitivity analysis illustrated that carbohydrate allocation changed with the amount of leaf area as well as the limiting factors for organ biomass development. Under a homogenous canopy architecture where all grape bunches were equally close to the carbohydrate sources, the common assimilate pool and phloem transport models produced very similar results. However, under a heterogeneous canopy architecture with variable distance between bunches and carbohydrate sources, the coefficient of variation for fruit biomass rose from 0.01 to 0.17 as crop load increased. These results indicate that carbohydrate allocation to fruits is affected by both the size of crop load and fruit distribution, which is not adequately described by the common assimilate pool model. The new grapevine model can also simulate dynamic canopy growth and be adapted to help optimise canopy architecture and quality variability of other perennial fruit crops.","PeriodicalId":36138,"journal":{"name":"in silico Plants","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45484199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-22DOI: 10.1093/insilicoplants/diab021
Junqi Zhu, A. Parker, F. Gou, R. Agnew, Linlin Yang, M. Greven, V. Raw, S. Neal, D. Martin, M. Trought, N. Huth, H. Brown
A new model for grapevines (Vitis vinifera L.) is the first perennial fruit crop model using the Agricultural Production System sIMulator (APSIM) Next Generation framework. Modules for phenology, light interception, carbohydrate allocation, yield formation and berry composition were adapted or added into APSIM Next Generation to represent the nature of fruit-bearing vines. The simulated grapevine phenological cycle starts with the dormancy phase triggered by a critical photoperiod in autumn, and then goes through the subsequent phenophases sequentially and finally returns to dormancy for a new cycle. The canopy microclimate module within APSIM Next Generation was extended to allow for row crop light interception. The carbohydrate arbitrator was enhanced to consider both sink strength and sink priority to reflect carbohydrate reserve as a concurrent competing sink. Weather conditions and source-sink ratio at critical developmental stages were used to determine potential grapevine yield components e.g., bunch number, berry number and berry fresh weight. The model was calibrated and tested extensively using four detailed datasets. The model captured the variations in the timing of measured budburst, flowering and véraison over 15 seasons across New Zealand for five different varieties. The calculated seasonal dynamics of light interception by the row and alley were consistent with field observations. The model also reproduced the dynamics of dry matter and carbohydrate reserve of different organs, and the wide variation in yield components caused by seasonal weather conditions and pruning regimes. The modelling framework developed in this work can also be used for other perennial fruit crops.
葡萄(Vitis vinifera L.)的新模型是第一个使用农业生产系统模拟器(APSIM)下一代框架的多年生水果作物模型。物候、光截获、碳水化合物分配、产量形成和浆果组成等模块被调整或添加到APSIM Next Generation中，以代表结果藤的性质。模拟的葡萄物候周期从秋季一个关键的光周期触发的休眠阶段开始，依次经历随后的物候阶段，最后回到休眠阶段进入新的周期。APSIM下一代中的冠层小气候模块被扩展到允许行作物光拦截。对碳水化合物仲裁者进行了改进，考虑了碳汇强度和碳汇优先级，以反映碳水化合物储备作为并发竞争汇的情况。关键发育阶段的天气条件和源汇比被用来确定潜在的葡萄产量成分，如束数、浆果数和浆果鲜重。该模型使用四个详细的数据集进行了广泛的校准和测试。该模型捕捉了新西兰5个不同品种在15个季节中测量的花蕾、开花和变节时间的变化。计算得到的行、巷截光季节动态与野外观测结果基本一致。该模型还再现了不同器官的干物质和碳水化合物储备的动态变化，以及季节天气条件和修剪制度引起的产量成分的广泛变化。在这项工作中开发的建模框架也可用于其他多年生水果作物。
{"title":"Developing perennial fruit crop models in APSIM Next Generation using grapevine as an example","authors":"Junqi Zhu, A. Parker, F. Gou, R. Agnew, Linlin Yang, M. Greven, V. Raw, S. Neal, D. Martin, M. Trought, N. Huth, H. Brown","doi":"10.1093/insilicoplants/diab021","DOIUrl":"https://doi.org/10.1093/insilicoplants/diab021","url":null,"abstract":"\u0000 A new model for grapevines (Vitis vinifera L.) is the first perennial fruit crop model using the Agricultural Production System sIMulator (APSIM) Next Generation framework. Modules for phenology, light interception, carbohydrate allocation, yield formation and berry composition were adapted or added into APSIM Next Generation to represent the nature of fruit-bearing vines. The simulated grapevine phenological cycle starts with the dormancy phase triggered by a critical photoperiod in autumn, and then goes through the subsequent phenophases sequentially and finally returns to dormancy for a new cycle. The canopy microclimate module within APSIM Next Generation was extended to allow for row crop light interception. The carbohydrate arbitrator was enhanced to consider both sink strength and sink priority to reflect carbohydrate reserve as a concurrent competing sink. Weather conditions and source-sink ratio at critical developmental stages were used to determine potential grapevine yield components e.g., bunch number, berry number and berry fresh weight. The model was calibrated and tested extensively using four detailed datasets. The model captured the variations in the timing of measured budburst, flowering and véraison over 15 seasons across New Zealand for five different varieties. The calculated seasonal dynamics of light interception by the row and alley were consistent with field observations. The model also reproduced the dynamics of dry matter and carbohydrate reserve of different organs, and the wide variation in yield components caused by seasonal weather conditions and pruning regimes. The modelling framework developed in this work can also be used for other perennial fruit crops.","PeriodicalId":36138,"journal":{"name":"in silico Plants","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44716465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1093/INSILICOPLANTS/DIAB019
Yoshiki Tokuyama, Y. Koide, K. Onishi, Kiwamu Hikichi, Miku Omachi, I. Takamure, Y. Kishima
Three-dimensional plant shapes are influenced by their phyllotaxy, which plays a significant role in their environmental adaptation. Grasses with distichous phyllotaxy have linearly aligned culms and usually have vertical fan-like shapes. Counterintuitively, some distichous phyllotaxy grasses have radial shapes. Here, we investigate the organ-level mechanism underlying radial shape development in the distichous phyllotactic wild rice species (Oryza rufipogon). Detailed time-course phenotyping and three-dimensional micro-computed tomography showed that changes in the elevation angle in the main culm and azimuth angle in the primary tillers contribute to radial shape development. To infer the mechanical basis of the shape change, we simulated the movements of culms controlled by different kinematic factors. The computational models predicted that the combination of movements, including that controlled by negative gravitropism, produces the overall radial shape. This prediction was experimentally assessed. The analysis using a near-isogenic line of the gene, PROG1 for prostrate growth and the gravitropic mutant (lazy1) showed an association between genes and our model parameters. Our findings provide a simple, yet substantial, kinematic model for how the shape in distichous phyllotaxy plants changes as part of their adaptation to the surrounding environment.
{"title":"The mechanical origin of the radial shape in distichous phyllotaxy grass plants","authors":"Yoshiki Tokuyama, Y. Koide, K. Onishi, Kiwamu Hikichi, Miku Omachi, I. Takamure, Y. Kishima","doi":"10.1093/INSILICOPLANTS/DIAB019","DOIUrl":"https://doi.org/10.1093/INSILICOPLANTS/DIAB019","url":null,"abstract":"\u0000 Three-dimensional plant shapes are influenced by their phyllotaxy, which plays a significant role in their environmental adaptation. Grasses with distichous phyllotaxy have linearly aligned culms and usually have vertical fan-like shapes. Counterintuitively, some distichous phyllotaxy grasses have radial shapes. Here, we investigate the organ-level mechanism underlying radial shape development in the distichous phyllotactic wild rice species (Oryza rufipogon). Detailed time-course phenotyping and three-dimensional micro-computed tomography showed that changes in the elevation angle in the main culm and azimuth angle in the primary tillers contribute to radial shape development. To infer the mechanical basis of the shape change, we simulated the movements of culms controlled by different kinematic factors. The computational models predicted that the combination of movements, including that controlled by negative gravitropism, produces the overall radial shape. This prediction was experimentally assessed. The analysis using a near-isogenic line of the gene, PROG1 for prostrate growth and the gravitropic mutant (lazy1) showed an association between genes and our model parameters. Our findings provide a simple, yet substantial, kinematic model for how the shape in distichous phyllotaxy plants changes as part of their adaptation to the surrounding environment.","PeriodicalId":36138,"journal":{"name":"in silico Plants","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43815013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1093/INSILICOPLANTS/DIAB020
R. Shaw, C. Y. M. Cheung
Rice is a major staple food worldwide and understanding its metabolism is essential for improving crop yield and quality, especially in a changing climate. Constraint-based modelling is an established method for studying metabolism at a systems level, but one of its limitations is the difficulty in directly integrating certain environmental factors, such as water potential, to the model for predicting metabolic changes in response to environmental changes. Here, we developed a framework to integrate a crop growth model and an upgraded diel multi-organ genome-scale metabolic model of rice to predict the metabolism of rice growth under normal and water-limited conditions. Our model was able to predict distinct metabolic adaptations under water-limited stress compared to normal condition across multiple developmental stages. Our modelling results of dynamic changes in metabolism over the whole-plant growth period highlighted key features of rice metabolism under water-limited stress including early leaf senescence, reduction in photosynthesis and significant nitrogen assimilation during grain filling.
{"title":"Integration of crop growth model and constraint-based metabolic model predicts metabolic changes over rice plant development under water-limited stress","authors":"R. Shaw, C. Y. M. Cheung","doi":"10.1093/INSILICOPLANTS/DIAB020","DOIUrl":"https://doi.org/10.1093/INSILICOPLANTS/DIAB020","url":null,"abstract":"\u0000 Rice is a major staple food worldwide and understanding its metabolism is essential for improving crop yield and quality, especially in a changing climate. Constraint-based modelling is an established method for studying metabolism at a systems level, but one of its limitations is the difficulty in directly integrating certain environmental factors, such as water potential, to the model for predicting metabolic changes in response to environmental changes. Here, we developed a framework to integrate a crop growth model and an upgraded diel multi-organ genome-scale metabolic model of rice to predict the metabolism of rice growth under normal and water-limited conditions. Our model was able to predict distinct metabolic adaptations under water-limited stress compared to normal condition across multiple developmental stages. Our modelling results of dynamic changes in metabolism over the whole-plant growth period highlighted key features of rice metabolism under water-limited stress including early leaf senescence, reduction in photosynthesis and significant nitrogen assimilation during grain filling.","PeriodicalId":36138,"journal":{"name":"in silico Plants","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43972652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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