Pub Date : 2018-11-01DOI: 10.1109/pma.2018.8747359
Binglin Zhu, Fusang Liu, Yingpu Che, Fang Hui, Yuntao Ma
High-throughput phenotyping of plant threedimensional (3D) architecture is critical for determining plant phenotypic characteristics. The acquisition of 3D architecture of plant phenotypic traits based on multi-view photographing has been widely applied in greenhouse research. Growth process of the plants can be dynamically monitored. However, the application of this method in the field is more difficult and less due to the complex environment. In this study, maize/soybean intercropping plant populations in the field were selected as the research objects. We combined ground and aerial photography to obtain the image sequences. at the stage of seedling, jointing, tasseling and grain filling. The targeted plants were photographed with fixed point from multi-view hemispherical directions on ground photography before tasseling stage. Then, Unmanned Aerial Vehicle was used to take photos in the way of concentric circles with different radius. We preprocessed the image sequences by Support Vector Machine (SVM) method, and pixel information only containing targeted plants were achieved. We evaluated the accuracy of calculated individual height, blade length and maximum width with the measured data. Image sensitivity analysis was also done at 25 and 79 days after emergence by reducing the image numbers. Canopy coverage and plant height were compared between different scenarios. The results showed that there was a good agreement between measured and calculated plant height, blade length and blade maximum width with R2>0.90. Then the dynamic changes of plant height, crown surface and organ growth were extracted based on reconstructed 3D architecture. Sensitivity analysis showed that at the early growth stage, 50 images are enough for 3D reconstruction of the plant. However, all 300 images need to be included at the late growth stage of plants. The results can provide a basis for high-throughput phenotypic analysis related to genotypes and help to evaluate the plant architecture and canopy radiation interception.
{"title":"Three-dimensional quantification of intercropping crops in field by ground and aerial photography","authors":"Binglin Zhu, Fusang Liu, Yingpu Che, Fang Hui, Yuntao Ma","doi":"10.1109/pma.2018.8747359","DOIUrl":"https://doi.org/10.1109/pma.2018.8747359","url":null,"abstract":"High-throughput phenotyping of plant threedimensional (3D) architecture is critical for determining plant phenotypic characteristics. The acquisition of 3D architecture of plant phenotypic traits based on multi-view photographing has been widely applied in greenhouse research. Growth process of the plants can be dynamically monitored. However, the application of this method in the field is more difficult and less due to the complex environment. In this study, maize/soybean intercropping plant populations in the field were selected as the research objects. We combined ground and aerial photography to obtain the image sequences. at the stage of seedling, jointing, tasseling and grain filling. The targeted plants were photographed with fixed point from multi-view hemispherical directions on ground photography before tasseling stage. Then, Unmanned Aerial Vehicle was used to take photos in the way of concentric circles with different radius. We preprocessed the image sequences by Support Vector Machine (SVM) method, and pixel information only containing targeted plants were achieved. We evaluated the accuracy of calculated individual height, blade length and maximum width with the measured data. Image sensitivity analysis was also done at 25 and 79 days after emergence by reducing the image numbers. Canopy coverage and plant height were compared between different scenarios. The results showed that there was a good agreement between measured and calculated plant height, blade length and blade maximum width with R2>0.90. Then the dynamic changes of plant height, crown surface and organ growth were extracted based on reconstructed 3D architecture. Sensitivity analysis showed that at the early growth stage, 50 images are enough for 3D reconstruction of the plant. However, all 300 images need to be included at the late growth stage of plants. The results can provide a basis for high-throughput phenotypic analysis related to genotypes and help to evaluate the plant architecture and canopy radiation interception.","PeriodicalId":268842,"journal":{"name":"2018 6th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116696819","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 : 2018-11-01DOI: 10.1109/PMA.2018.8611609
Sebastian Munz, S. Graeff‐Hönninger, M. Henke
Intercropping is an important aspect for the sustainable intensification of agriculture. Maize and a shorter legume crop are common species in intercropping systems and competition for light plays a major role on productivity given the large differences in canopy height. Particularly in intercropping systems, the light intensity for the shorter crop fluctuates strongly during the day. For selecting a maize cultivar, the influence of its architecture on this light fluctuation is very important. With the aim to pre-select suitable cultivars for experimentation and to guide breeding programs, modelling approaches are crucial. Here we present and evaluate a functional-structural plant model (FSPM) able to simulate on an hourly resolution the influence of architectural characteristics of maize on light distribution within strip-intercropping systems. This is a first step towards a complex dynamic FSPM intercropping model, suitable for detailed investigations of the effects of plant architecture on light absorption, photosynthesis and finally biomass production.
{"title":"Functional-structural plant model for testing the effect of maize architecture on hourly light distribution in strip-intercropping systems","authors":"Sebastian Munz, S. Graeff‐Hönninger, M. Henke","doi":"10.1109/PMA.2018.8611609","DOIUrl":"https://doi.org/10.1109/PMA.2018.8611609","url":null,"abstract":"Intercropping is an important aspect for the sustainable intensification of agriculture. Maize and a shorter legume crop are common species in intercropping systems and competition for light plays a major role on productivity given the large differences in canopy height. Particularly in intercropping systems, the light intensity for the shorter crop fluctuates strongly during the day. For selecting a maize cultivar, the influence of its architecture on this light fluctuation is very important. With the aim to pre-select suitable cultivars for experimentation and to guide breeding programs, modelling approaches are crucial. Here we present and evaluate a functional-structural plant model (FSPM) able to simulate on an hourly resolution the influence of architectural characteristics of maize on light distribution within strip-intercropping systems. This is a first step towards a complex dynamic FSPM intercropping model, suitable for detailed investigations of the effects of plant architecture on light absorption, photosynthesis and finally biomass production.","PeriodicalId":268842,"journal":{"name":"2018 6th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116158307","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 : 2018-11-01DOI: 10.1109/PMA.2018.8611582
A. Seleznyova, A. Saei, Liqi Han, B. V. van Hooijdonk
The objective of this project is development of methods for mechanistic modelling of apple tree growth and function. The project consists of two interrelated workstreams: the prototype model building, and the experimental data collection and analysis to provide conceptual and quantitative support for model fitting, evaluation and improvement. The L-system model is built at a metamer scale and incorporates the tree architecture and carbohydrate dynamics, including acquisition, transport, allocation and reserve accumulation and mobilization. The objective and the scale of the model determined the type of the data collected in the project and their spatial and temporal resolution. Currently, the experimental results are used for testing and improving the model functions governing organ growth and carbohydrate dynamics.
{"title":"From field data to modelling concepts: building a mechanistic FSPM for apple","authors":"A. Seleznyova, A. Saei, Liqi Han, B. V. van Hooijdonk","doi":"10.1109/PMA.2018.8611582","DOIUrl":"https://doi.org/10.1109/PMA.2018.8611582","url":null,"abstract":"The objective of this project is development of methods for mechanistic modelling of apple tree growth and function. The project consists of two interrelated workstreams: the prototype model building, and the experimental data collection and analysis to provide conceptual and quantitative support for model fitting, evaluation and improvement. The L-system model is built at a metamer scale and incorporates the tree architecture and carbohydrate dynamics, including acquisition, transport, allocation and reserve accumulation and mobilization. The objective and the scale of the model determined the type of the data collected in the project and their spatial and temporal resolution. Currently, the experimental results are used for testing and improving the model functions governing organ growth and carbohydrate dynamics.","PeriodicalId":268842,"journal":{"name":"2018 6th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122446523","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 : 2018-11-01DOI: 10.1109/PMA.2018.8611566
Xiangtuo Chen, Benoit Bayol, P. Cournède
An accurate prediction of the production level for certain individual crops is always an important topic for the crop sector and the government decision-makers. From a perspective of the global market, these statistics are needed to make accurate price predictions, which in turn serve to make business decisions. With the development of computer science and mathematics and the easier access to the open agricultural datasets, the statistical learning methods can serve as an alternative for this purpose. In this article, the weighted statistical learning methods will be applied to predict the soft wheat production in France for the period 1995-2010 with the related methodological records. In term of prediction error, the weighted regression methods are proved to be more effective with a 5.5% relative prediction error. Besides, some simple data preprocessing methods are tested to make the predictive model simpler and more robust.
{"title":"Application of Weighted Regression for the Prediction of Soft Wheat Production in France","authors":"Xiangtuo Chen, Benoit Bayol, P. Cournède","doi":"10.1109/PMA.2018.8611566","DOIUrl":"https://doi.org/10.1109/PMA.2018.8611566","url":null,"abstract":"An accurate prediction of the production level for certain individual crops is always an important topic for the crop sector and the government decision-makers. From a perspective of the global market, these statistics are needed to make accurate price predictions, which in turn serve to make business decisions. With the development of computer science and mathematics and the easier access to the open agricultural datasets, the statistical learning methods can serve as an alternative for this purpose. In this article, the weighted statistical learning methods will be applied to predict the soft wheat production in France for the period 1995-2010 with the related methodological records. In term of prediction error, the weighted regression methods are proved to be more effective with a 5.5% relative prediction error. Besides, some simple data preprocessing methods are tested to make the predictive model simpler and more robust.","PeriodicalId":268842,"journal":{"name":"2018 6th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133356191","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 : 2018-11-01DOI: 10.1109/PMA.2018.8611579
Katarína Streit, J. Evers, M. Renton
Weather conditions are an important driver of disease development. For example for yellow spot in wheat, warm and moist conditions favour secondary infection. Although the relationship between environment and disease development is the basis of many epidemiological models, changes in plant architecture and growth have an effect on disease progress and severity as well. Functional-structural plant models (FSPMs) are well suited to study the interactions between pathogen, climatic conditions and growing host crop. In this study we focused on simulating the effect of weather conditions on the progression of secondary infection in yellow spot and the interaction with growing wheat canopy. Simulations were performed using a coupled host-pathogen FSPM with standard meteorological data input. The model develops on previous coupled host-pathogen FSPMs by combining response functions to temperature and wetness duration and calculating the hourly progression of secondary infection. The simulated diseased area differed with different combinations of temperature and moisture response models. Changes in dispersal pattern were observed mainly in relation to spore release rate.
{"title":"Modelling the combined effect of moisture and temperature on secondary infection in a coupled host-pathogen FSPM","authors":"Katarína Streit, J. Evers, M. Renton","doi":"10.1109/PMA.2018.8611579","DOIUrl":"https://doi.org/10.1109/PMA.2018.8611579","url":null,"abstract":"Weather conditions are an important driver of disease development. For example for yellow spot in wheat, warm and moist conditions favour secondary infection. Although the relationship between environment and disease development is the basis of many epidemiological models, changes in plant architecture and growth have an effect on disease progress and severity as well. Functional-structural plant models (FSPMs) are well suited to study the interactions between pathogen, climatic conditions and growing host crop. In this study we focused on simulating the effect of weather conditions on the progression of secondary infection in yellow spot and the interaction with growing wheat canopy. Simulations were performed using a coupled host-pathogen FSPM with standard meteorological data input. The model develops on previous coupled host-pathogen FSPMs by combining response functions to temperature and wetness duration and calculating the hourly progression of secondary infection. The simulated diseased area differed with different combinations of temperature and moisture response models. Changes in dispersal pattern were observed mainly in relation to spore release rate.","PeriodicalId":268842,"journal":{"name":"2018 6th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133421976","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 : 2018-11-01DOI: 10.1109/PMA.2018.8611617
Xiao-Ran Zhou, A. Schnepf, A. Lacointe, J. Vanderborght, D. Leitner, H. Vereecken, G. Lobet
Plant growth and development are limited by the available resources. The carbon and water flows are both important content and indicators of resource translocations. Modelling is helpful to increase the spatial and temporal resolutions of carbon and water reallocations in plants. However, the mechanism of carbon and water translocations has not been coupled into a whole Functional-Structural Plant Model (FSPM) yet. Here we developed a FSPM called CPlantBox which could (1) simulate the growth and development of the full plant structure (both root and shoot); (2) connect to a mechanistic model of water and carbon flow (PiafMunch). Our results demonstrate how carbon and water are flowing inside a plant which has three sources (leaf) and two sinks (root). We anticipate the model can be used as a tool to explore the variabilities and possibilities of plant behavior. Furthermore, several tool sets will be developed to visualize the morphological and physiological attributes of plants, which are helpful to deepen our understanding of plants and produce more with less.
{"title":"Presentation of CPlantBox: a whole functional-structural plant model (root and shoot) coupled with a mechanistic resolution of carbon and water flows","authors":"Xiao-Ran Zhou, A. Schnepf, A. Lacointe, J. Vanderborght, D. Leitner, H. Vereecken, G. Lobet","doi":"10.1109/PMA.2018.8611617","DOIUrl":"https://doi.org/10.1109/PMA.2018.8611617","url":null,"abstract":"Plant growth and development are limited by the available resources. The carbon and water flows are both important content and indicators of resource translocations. Modelling is helpful to increase the spatial and temporal resolutions of carbon and water reallocations in plants. However, the mechanism of carbon and water translocations has not been coupled into a whole Functional-Structural Plant Model (FSPM) yet. Here we developed a FSPM called CPlantBox which could (1) simulate the growth and development of the full plant structure (both root and shoot); (2) connect to a mechanistic model of water and carbon flow (PiafMunch). Our results demonstrate how carbon and water are flowing inside a plant which has three sources (leaf) and two sinks (root). We anticipate the model can be used as a tool to explore the variabilities and possibilities of plant behavior. Furthermore, several tool sets will be developed to visualize the morphological and physiological attributes of plants, which are helpful to deepen our understanding of plants and produce more with less.","PeriodicalId":268842,"journal":{"name":"2018 6th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130297456","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 : 2018-11-01DOI: 10.1109/PMA.2018.8611578
Marion Gauthier, R. Barillot, A. Schneider, C. Fournier, C. Pradal, A. Pinet, B. Andrieu
Leaf dimensions, specific mass and composition are traits of interest, as leaves constitute the main exchange surface with the aboveground environment. These variables arise from the interplay between many processes, and vary with growth conditions. Models of plant growth are useful tools to explore a wide range of climatic scenarios, management practices and genotypes. However, most models lacks process-based formalisms allowing simulating shoot architecture plasticity. We propose a functional-structural wheat model that couples carbon and nitrogen metabolism with leaf morphogenesis during the vegetative stage. The originality of our model relies on the interaction between leaf growth and the metabolism of carbon and nitrogen in the growing zone, which is possible thanks to an explicit and detailed formalism of the processes at organ level. The model simulates the appearance of successive leaves using coordination rules instead of a constant phyllochron as a driving mechanism. As a first step, main modules were evaluated separately: the coordination model and the metabolism model of a single growing leaf. The model shows interesting emergent properties: phyllochron stability, pattern of mature leaf length along the culm and realistic kinetics of length, dry mass and concentrations in both growing and mature zones. A qualitative evaluation strategy of the completely integrated model at plant scale is then proposed. As a conclusion, the model appears to be a useful concept, which could be transposed to other grasses.
{"title":"Towards a model of wheat leaf morphogenesis at plant scale driven by organ-level metabolites","authors":"Marion Gauthier, R. Barillot, A. Schneider, C. Fournier, C. Pradal, A. Pinet, B. Andrieu","doi":"10.1109/PMA.2018.8611578","DOIUrl":"https://doi.org/10.1109/PMA.2018.8611578","url":null,"abstract":"Leaf dimensions, specific mass and composition are traits of interest, as leaves constitute the main exchange surface with the aboveground environment. These variables arise from the interplay between many processes, and vary with growth conditions. Models of plant growth are useful tools to explore a wide range of climatic scenarios, management practices and genotypes. However, most models lacks process-based formalisms allowing simulating shoot architecture plasticity. We propose a functional-structural wheat model that couples carbon and nitrogen metabolism with leaf morphogenesis during the vegetative stage. The originality of our model relies on the interaction between leaf growth and the metabolism of carbon and nitrogen in the growing zone, which is possible thanks to an explicit and detailed formalism of the processes at organ level. The model simulates the appearance of successive leaves using coordination rules instead of a constant phyllochron as a driving mechanism. As a first step, main modules were evaluated separately: the coordination model and the metabolism model of a single growing leaf. The model shows interesting emergent properties: phyllochron stability, pattern of mature leaf length along the culm and realistic kinetics of length, dry mass and concentrations in both growing and mature zones. A qualitative evaluation strategy of the completely integrated model at plant scale is then proposed. As a conclusion, the model appears to be a useful concept, which could be transposed to other grasses.","PeriodicalId":268842,"journal":{"name":"2018 6th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122819278","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 : 2018-11-01DOI: 10.1109/PMA.2018.8611601
F. Ribeyre, M. Jaeger, Alexandre Ribeyre, P. de Reffye
FSPM are getting popular, open to a wide range of application and implemented in numerous simulation software or platforms. However, those seldom cover the field calibration aspects. We propose here a simple tool, StemGL, limited to single-stemmed plants, covering both calibration and simulation aspects of biomass production and allocation. Based on GreenLab model assumptions, the tool implements stochastic simulation capabilities; it offers virtual insights, and also presents field data comparisons. The application is delivered with a set of examples, with virtual plants to analyze and simulate, and real field plants with their parameters to retrieve.
{"title":"StemGL, a FSPM tool dedicated to crop plants model calibration in the single stem case","authors":"F. Ribeyre, M. Jaeger, Alexandre Ribeyre, P. de Reffye","doi":"10.1109/PMA.2018.8611601","DOIUrl":"https://doi.org/10.1109/PMA.2018.8611601","url":null,"abstract":"FSPM are getting popular, open to a wide range of application and implemented in numerous simulation software or platforms. However, those seldom cover the field calibration aspects. We propose here a simple tool, StemGL, limited to single-stemmed plants, covering both calibration and simulation aspects of biomass production and allocation. Based on GreenLab model assumptions, the tool implements stochastic simulation capabilities; it offers virtual insights, and also presents field data comparisons. The application is delivered with a set of examples, with virtual plants to analyze and simulate, and real field plants with their parameters to retrieve.","PeriodicalId":268842,"journal":{"name":"2018 6th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134031083","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 : 2018-11-01DOI: 10.1109/PMA.2018.8611603
Fang Hui, Yan Guo, B. Li, Chunli Lv, Yuntao Ma
Root system architecture determines the ability of crop in water and nutrient uptake, which affects interspecific facilitation in the maize/soybean intercropping. In this study, field experiments were conducted to investigate the differences of adult root system architecture between maize (Zea mays L.)/soybean (Glycine max L.) intercropping and monocropping. The skeleton of root system was captured with 3D digitalization at filling stage of maize, then the roots were sampled and scanned. Root length and root diameter were extracted from the scanned root images. Root overlap of maize and soybean were calculated by counting the percentage of the points located on axile roots of one plant inside root system of another plant to quantify the interspecific interactions in 3D. The results showed that root-root interactions between maize and soybean altered the root system architecture of both crops. The early axile roots of maize and soybean longer than the late axile roots in two cropping patterns. Maize/soybean interspecific interactions promoted axile root elongation of maize and soybean. The asymmetric interspecific facilitation was found in diameter of axile roots, which was the late axile roots of intercropped maize significantly thicker but most axile roots of intercropped soybean significantly thinner (ANOVA, P < 0.05). Root overlap of maize and soybean in intercropping was about 4.58% and mainly distributed 20~40 cm below soil surface. The axile roots of N1~N3 of maize trended to flatly grow first and rapidly grow downward later, mainly leading to the overlap between maize and soybean root system.
根系结构决定了作物对水分和养分的吸收能力，从而影响玉米/大豆间作的种间促进。通过田间试验研究了玉米(Zea mays L.)/大豆(Glycine max L.)间作与单作成体根系构型的差异。利用三维数字化技术对灌浆期玉米根系骨架进行了捕获，并对根系进行了采样和扫描。从扫描的根图像中提取根长和根直径。通过计算一株植物轴根上的点在另一株植物根系内的百分比来计算玉米和大豆的根重叠，以三维方式量化种间相互作用。结果表明，玉米和大豆的根-根互作改变了两种作物的根系结构。两种种植方式下，玉米和大豆的早轴根比晚轴根长。玉米/大豆种间互作促进了玉米和大豆的轴根伸长。间作玉米的中轴根直径存在不对称的种间促进作用，间作大豆的中轴根较粗，间作玉米的中轴根较粗(方差分析，P < 0.05);间作玉米与大豆根系重叠度约为4.58%，主要分布在地表以下20~40 cm处。玉米N1~N3轴根呈先平生后快速下生的趋势，主要导致玉米与大豆根系重叠。
{"title":"Quantification of differences in root system architecture under maize/soybean interspecific interactions","authors":"Fang Hui, Yan Guo, B. Li, Chunli Lv, Yuntao Ma","doi":"10.1109/PMA.2018.8611603","DOIUrl":"https://doi.org/10.1109/PMA.2018.8611603","url":null,"abstract":"Root system architecture determines the ability of crop in water and nutrient uptake, which affects interspecific facilitation in the maize/soybean intercropping. In this study, field experiments were conducted to investigate the differences of adult root system architecture between maize (Zea mays L.)/soybean (Glycine max L.) intercropping and monocropping. The skeleton of root system was captured with 3D digitalization at filling stage of maize, then the roots were sampled and scanned. Root length and root diameter were extracted from the scanned root images. Root overlap of maize and soybean were calculated by counting the percentage of the points located on axile roots of one plant inside root system of another plant to quantify the interspecific interactions in 3D. The results showed that root-root interactions between maize and soybean altered the root system architecture of both crops. The early axile roots of maize and soybean longer than the late axile roots in two cropping patterns. Maize/soybean interspecific interactions promoted axile root elongation of maize and soybean. The asymmetric interspecific facilitation was found in diameter of axile roots, which was the late axile roots of intercropped maize significantly thicker but most axile roots of intercropped soybean significantly thinner (ANOVA, P < 0.05). Root overlap of maize and soybean in intercropping was about 4.58% and mainly distributed 20~40 cm below soil surface. The axile roots of N1~N3 of maize trended to flatly grow first and rapidly grow downward later, mainly leading to the overlap between maize and soybean root system.","PeriodicalId":268842,"journal":{"name":"2018 6th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121803674","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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