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+====== User and Developer Workshop, December 2024 ======
+===== FruitCropXL, a Generic Functional–Structural Fruit Crop Model to Study Tree Architecture and Fruit Quality =====
+//Junqi Zhu<sup>1</sup>, James Bristow<sup>2</sup>, Ou An Chuang<sup>2</sup>, Xiumei Yang<sup>3</sup>, Anand Rampadarath<sup>2</sup>, Francisco Rojo<sup>4</sup>//
+//The New Zealand Institute for Plant and Food Research Limited, <sup>1</sup>Marlborough, <sup>2</sup>Auckland, <sup>3</sup>Lincoln, <sup>4</sup>Havelock North//
+Functional–structural fruit crop models that represent the 3D architecture of plants and the functionality
+of different organs, can be used to guide the interventions that improve fruit productivity and quality,
+enhance resource and energy use efficiency, and facilitate the use of autonomous robots. Here we present
+FruitCropXL, a generic functional–structural model tailored for **Fruit Crops**, developed within GroIMP
+using the eXtended L-system (**XL**).
+FruitCropXL conceptualizes plants as collections of objects including buds, flowers, fruits, leaves,
+internodes, fine roots, and structural roots, complemented by classes such as Phenology, Environment,
+and Resource Arbitrator. FruitCropXL, originating from GrapevineXL, simulates various physiological
+processes such as light interception, photosynthesis, and transpiration at the individual leaf level, along
+with water uptake from different soil layers and water transport from soil to leaf based on the water
+potential gradient, and solves phloem carbon concentration based on the carbon dynamics of each
+organ. Furthermore, we integrated a well-recognized biophysical virtual fruit model, which enables the
+simulation of various fruit types and their growth processes, including the metabolism of sugars and
+acids.
+Over time, we have enhanced FruitCropXL with a modularization framework that enables the toggling
+between different species (e.g. grapevine and apple), module versions (simple or complex root module),
+and functionalities such as light interception and carbon transport. This flexible framework allows users
+to customize simulations ranging from a single organ to an entire plant, and from one hour to an entire
+season, all within a single configuration file. The model is equipped to handle both static and dynamic
+canopy architecture scenarios starting at any point in a growing season. It can also accommodate
+different canopy and root architectures, which can be integrated either through csv files from our newly
+developed shoot and root architecture generators, or directly coded architecture types within the model
+itself.
+===== Eco-Fuzzy Decision Model: Optimizing Agricultural Investment =====
+//Ditdit Nugeraha Utama//
+//Bina Nusantara University, Indonesia//
+Environmental aspects are no longer merely a trend to study; they have become a critical factor to
+consider in various strategic matters, including investment decision-making. The eco-decision model
+(ecoDM) is a computational model designed to assist decision-makers in making objective decisions,
+with one of its key parameters being the environmental (ecological) aspect. Specifically, for agricultural
+investment decisions, ecoDM can be developed by utilizing data inputs supplied through plant
+modeling with the functional-structural plant modeling (FSPM) approach, implemented using GroIMP.
+The FSPM approach enables plant modeling to provide input data and information in various forms,
+including trends, forecasts, and statistical explanations. These inputs can be further modeled to
+generate actionable decision recommendations. In this context, fuzzy logic can serve as the primary
+method for building the inference engine.
+===== Light Quality Modelling =====
+//Maarten van der Meer//
+//Wageningen University %%&%% Research, The Netherlands//
+Light quality is hard to measure, but very relevant for plant research as it largely determines plant
+growth. With an increasing capacity to steer light quality in Controlled-Environment Agriculture (CEA) by
+the minute, an understanding of how this influences plant growth is essential. Modelling with the use of
+raytracing helps us to visualize and quantify light quality during crop growth. By having the numbers
+quantified, we can retrospectively explain observed effects on crop growth. At the same time, better
+fitting solutions and insight is provided to breeders, growers and material suppliers that work, one way
+or the other, with light quality.
+===== Structural Optimization of Chinese Energy-Saving Solar Greenhouses and Ideal Canopy Design for Tomato Cultivation =====
+//Yue Zhang//
+//Shanxi Datong University, China//
+Since the 1980s, Chinese energy-saving solar greenhouses (CESGs) have evolved through three
+generations, achieving significant economic and ecological benefits. However, optimizing greenhouse
+structures to maximize solar energy utilization and the identification of ideal crop canopy
+configurations remains critical.
+A virtual simulation method for the light environment of the greenhouse and tomato canopy is
+proposed, and relevant models are established. Based on this, an optimal structure screening modelling
+method is created. Multiple greenhouse structure parameters are simulated and verified, and the
+optimal building structure configuration for the 41.5°N latitude area in China is obtained. The new
+structure can improve room temperature and light interception performance, reduce coal consumption
+and increase tomato yield.
+A light-thermal coupling model for simulating the microenvironment of tomato canopy leaves is also
+established and verified, revealing the dynamic light and thermal microclimate of the greenhouse. The
+simulation model is used to calculate the effects of various planting strategies and tomato plant
+architectures, determine the ideal canopy configuration and plant architecture, analyze the quantitative
+relationship between planting patterns and plant configurations, and design an ideal tomato plant
+architecture, providing a reference for tomato planting and breeding
+===== Quantifying the Impact of Structural Model Complexity on Light Interception Simulation in Cucumber Crops Using Point Cloud Data =====
+//Peige Zhong//
+//Wageningen University %%&%% Research, The Netherlands//
+Structural complexity plays a crucial role in the accuracy of light interception simulations for functional-
+structural plant models (FSPMs). In this study, point cloud data was used to construct cucumber FSPMs
+with varying levels of structural complexity. Sensitivity analyses were performed to quantify the
+influence of these variations on light interception simulation outcomes. The results provide new
+insights into optimizing structural model detail for accurate and efficient light interception modeling in
+cucumber crops.
+===== A Dwarf Tomato FSP Model for Vertical Farming =====
+//Michele Butturini//
+//Wageningen University %%&%% Research, The Netherlands//
+Dwarf tomato plants, characterized by compact size and determinate growth patterns, offer significant
+advantages for vertical farming (VF) systems. Their reduced pruning requirements, short cultivation
+cycles, and potential for automation could also revolutionize labor-intensive greenhouse practices, such
+as side-shoot pruning and fruit harvesting. While these traits make dwarf tomatoes promising for VF,
+their adaptation to VF-specific conditions remains limited. Breeding architectural ideotypes that
+enhance light absorption and carbon assimilation is crucial for improving yield and light-use efficiency
+in VF systems. A functional-structural plant (FSP) model tailored for dwarf tomatoes can facilitate this by
+simulating growth dynamics and light interaction at the organ level. Using dynamic and static
+simulations, the model can evaluate architectural scenarios, optimize photosynthetic efficiency, and
+predict yield. Incorporating MTG (multiscale tree graph) formalism provides a robust framework for
+capturing plant architecture and growth dynamics. The model’s application in VF enables the analysis of
+light interception, photosynthesis, and assimilate allocation under controlled environments. This study
+highlights the potential of integrating FSP modeling with experimental data to develop ideotypes that
+maximize yield and resource efficiency in urban VF systems.
+===== From Scrap to Craft? Using and Re-Using GroIMP Models as Serious Games for Teaching =====
+//Gerhard Buck-Sorlin<sup>1</sup>, Michael Henke<sup>2</sup>//
+//<sup>1</sup>Institut Agro Rennes-Angers, France, <sup>2</sup>Hunan Agriculture University, China//
+In this presentation I will give an overview of the use of GroIMP as a tool for teaching, with an emphasis
+on simple, "data-free" or "data-lean" models that can be used as serious games or educational toy
+models for ecophysiology. Examples include (but are not limited to) the effect of mineral deficiencies on
+growth and photosynthesis in tomato, or the effect of light spectrum on organ growth. Using GroIMP as
+a tool for teaching plant modelling to Master students in agronomy and horticulture has been a real
+challenge since I started this endeavour more than 15 years ago. This workshop contribution provides a
+personal review of the various experiences and lessons drawn and attempts to sketch an outlook on
+future improvements necessary to make GroIMP an (even more) attractive tool for teaching.
+===== Graph-Based Point Cloud Management in GroIMP =====
+//Gaëtan Heidsieck//
+//University of Göttingen, Germany//
+The graph-based functional structural plant modeling (FSPM) platform GroIMP was extended by a set of
+functionalities for managing point clouds on the level of individual points using GroIMPs relational
+graph grammar. These functionalities include the import of XYZ (simple x y z coordinates in CSV style)
+and PLY based point clouds as balanced trees to the GroIMP simulation graph and a set of basic point
+cloud manipulation tools. They are extended to support the possible faces and edges from the PLY as
+part of the point cloud. We use this new implementation in GroIMP in two examples to showcase its
+usage: a model validation and a fine-grained light interception on meshes
+===== Managing Additional Graphs in GroIMP =====
+//Tim Oberländer//
+//University of Göttingen, Germany//
+With the latest version of the Graph Explorer plugin, two new types of objects are introduced to support
+the use of additional graph structures in GroIMP. These additional graphs can be used for instantiation
+or cloning into other graphs, or for analysis and modification using XL, RGG or the visual editors. It is
+possible to import these graphs from any format supported by GroIMP, to create new secondary graphs
+on the fly or clone parts of other graphs into new graph objects.
+===== Consolidating the GroIMP Plant Modelling Platform – Software Update, Plugin Management & Documentation Improvements =====
+//Gaëtan Heidsieck, Tim Oberländer//
+//University of Göttingen, Germany//
+The GroIMP platform continues being upgraded, with newer versions of software dependencies, quality
+of life improvements, additional features and more options for installation and deployment. The project
+management becomes easier with some improvement in the file management, the possibility of
+saving/sharing options files, and the usage of project templates. Additionally, a plugin manager ease
+the usage of plugins within a GroIMP installation, which enables to benefit from the latest updates and
+bug fixes. The new features implemented include: a data structure to support point clouds as graphs
+within a project, which includes import/export formats as well as some basic functionalities: split,
+merge, convert, and XL queries; a basic text auto completion which provides completions for modules,
+classes and classes defined in a project as well as static imports: methods and classes. Finally, some
+points have been raised in order to be discussed during this workshop for future improvements.
+======Tutorials======
+If you struggle with something in the following tutorials and you can not attend the workshop session, please feel free to reach out to the community using the FSPM forum.
+===== Introduction to modelling with XL  =====
+Introduction to XL (eXtended L-systems) and turtle graphics
+  * [[02_user_tutorials:01_getting_started:02_rgg-code-structure|RGG Code structure introduction]]
+  * [[02_user_tutorials:03_graph_xl:01_xl-queries-and-operators| XL queries and operators ]]
+  * [[02_user_tutorials:03_graph_xl:02_xl-turtle-geometry| XL turtle geometry ]]
+===== Creating a simple plant in 3D =====
+How to create a simple tomato plant and a simple tree
+  * [[02_user_tutorials:tutorials:architecture-model| A step by step growth model ]]
+  * [[02_user_tutorials:02_growth_modelling:02_simple-tomato-model| A simple tomato plant model ]]
+  * [[02_user_tutorials:02_growth_modelling:leaf-triangulation| Leaf triangulation ]]
+===== Basic to advanced XL queries  =====
+Some tips on using XL queries and XL operators
+  * [[02_user_tutorials:03_graph_xl:basic-to-advanced-xl-queries|Basic to advanced XL queries]]
+===== Spectral light modelling  =====
+Setting up light sources, shaders, and spectral raytracer to
+calculate light distribution in the canopy
+  * [[02_user_tutorials:04_light_modelling:basic-spectral-light-modeling| Basic spectral light modeling ]]
+===== Point cloud management  =====
+Setting up a project with point clouds as organs in a
+model. Using point cloud with XL queries
+  * [[01_user_documentation:groimp-platform:pointcloudtools|Getting started with using point clouds and tools]]
+  * [[02_user_tutorials:06_complex_objects:01_pointcloud:05_using-point-cloud-to-validate-model|Using a point cloud to validate a simulation]]
+  * [[02_user_tutorials:06_complex_objects:01_pointcloud:04_using-mesh-clouds-as-organ|Using a mesh cloud as a high resolution organ]]
+===== GroIMP API (GroLink)  =====
+Starting the [[01_user_documentation:10_additional_interfaces:api| GroIMP API]] and connecting to it through Python or R.
+  * [[02_user_tutorials:07_additional_interfaces:api:03_getting-started-with-grolink-and-gropy|Getting started with GroLink and Python(GroPy)]]
+  * [[02_user_tutorials:07_additional_interfaces:api:04_getting-started-with-grolink-and-gror|Getting started with GroLink and R(GroR)]]
+  * [[02_user_tutorials:07_additional_interfaces:api:06_sensitivity-analysis-using-grolink-and-gror|Sensitivity Analysis using GroR]]
+  * [[02_user_tutorials:07_additional_interfaces:api:05_handeling-data-in-grolink-projects|Handling data in GroLink projects]]
+===== Creating/managing GroIMP plugins =====
+How to create new plugins/add features to GroIM
+  * [[05_developer_tutorials:02_extending_groimp:01_create-groimp-plugin| Create a GroIMP Plugin]]
+===== Git & GroIMP =====
+Setting up git/Eclipse/Maven to work with the development
+of GroIMP
+  * [[05_developer_tutorials:01_setup:01_setup-groimp-dev-environment|Setup GroIMP with git and Eclipse]]
+===== GroLink and Kubernetes =====
+Setting up distributed calculation
+  * [[02_user_tutorials:07_additional_interfaces:api:07_grolink-on-kubernetes| Deploying GroIMP/GroLink on Kubernetes]]