Room : CIP I

Dr. Yixiang Shan, University of Sheffield, UK

9:00 - 9:25

Selection under cultivation has caused numerous morphological changes in today’s modern wheat varieties compared with their wild relatives. However, the exact timing of these changes and the selection mechanisms involved, have not been determined. Here, we screened morphological traits across a diversity of wild and domesticated wheat varieties to infer the timing of morphological changes, with a focus on domestication, by comparing three independent domestication events. We also conducted experiments and model simulations to investigate the role of competition as a potential selection mechanism. Domestication increased the sizes of wheat leaves and seeds, and made plants grow taller, with more erect architecture. Associated changes to the biomass of domesticated wheats generated more grains and achieved higher yields. Competition experiments showed that domesticated varieties in each case are stronger competitors than their wild relatives. Modelling analysis showed that a number of traits are responsible for this competitive advantage in domesticated crops, including increased leaf size, steeper leaf insertion angle and greater plant height. This implies that natural selection increased the competitiveness of individual wheat plants in the new field environment through changes to canopy morphology. However, strong individual competitiveness has negative consequences for field-scale yields under high modern planting densities. Modern selective breeding has therefore had to reverse these domestication traits by making leaves shorter and more erect, and reducing plant height to improve grain biomass. Our work outlines the shifts in morphological strategy that occurred during wheat domestication, while uncovering the selection pressures behind them. This is an important contribution to our understanding of wheat domestication, as well as to the improvement of agricultural production. It shows that ecological selection mechanisms during ancient domestication events have shaped crop phenotypes for reasons that are irrelevant or detrimental for modern agriculture.

Peige Zhong, Wageningen University & Research

9:25 -9:50

Digital twins use information provided by greenhouse sensors, and may include a virtual plant model which can be updated by this information to simulate the morphological and physiological status of real plants. This enables growers to achieve remote management and helps researchers to understand plant structure. A real-time updated Functional-Structural Plant Model (FSPM) of cucumber can be built by integrating 3D point clouds data. It can not only reflect the current morphological plant structure but will also integrate physiological processes to predict the future growth of cucumbers. The ultimate goal of the research is to develop a methodology for constructing a plant model based on fast-phenotyping techniques for modern greenhouse digital twin systems.

9:50- 10:15

Thomas Hay, University of Göttingen

I present a structural model of adult spruce trees to quantify their phenotypic plasticity across ecotypes in central Germany, utilizing terrestrial laser scans and quantitative structural models for parameterization.

10:15-10:45

Kristýna Šleglová, Mendel University in Brno

This presentation introduces the modelling of four different trees from Czech and Portuguese forests using the GroImp simulation tool. The models focus on crown architecture and root system structure of both coniferous and deciduous species, with each tree simulated under ideal conditions without competition. The results highlight differences in structure and growth strategies between species from temperate and Mediterranean climates. The presentation also outlines future development plans, including the addition of competition, light, and water effects for more realistic modelling.

11:00- 11:25

Wei Sun, Wageningen University & Research

Indoor rice seedling production has become a critical strategy in Chinese agriculture to extend the growing period in regions where otherwise only a single annual harvest would be feasible. By cultivating seedlings indoors during the cold spring months and again while the first field-grown crop is still maturing, growers can extend the overall cultivation period by two additional three-week intervals, thereby enabling two harvests per year. However, several challenges remain associated with this technique: (1) cold spells can cause substantial damage to newly transplanted seedlings, significantly reducing yield, and (2) seedling cultivation in vertical farming environments is highly energy-intensive. This project therefore aims to enhance the cold stress resistance of rice seedlings while simultaneously reducing the time required from sowing to transplantation. High-throughput plant phenotyping platforms are employed to capture sophisticated traits capable of quantifying subtle aspects of plant physiology. By analyzing and correlating these traits with critical physiological stress indicators, such as photosynthetic efficiency, a set of so-called “hidden traits” is identified. Hidden traits refer to plant characteristics that quantify the plant’s stress response, although they are not readily observable through conventional phenotyping. Both the hidden traits and conventional morphological traits, along with their dynamic changes, are used as input parameters for the development of a dynamic digital twin (DT) model of rice seedlings. The DT model integrates a virtual representation of a vertical farming platform with a functional–structural plant model (FSPM) of rice seedlings. In the final step, the rice seedling DT model is employed as a decision-support tool to optimize management strategies. This includes minimizing the seedling growth duration before transplantation and adapting climate control strategies within the vertical farm to mitigate the impact of adverse environmental conditions during field establishment. This presentation will introduce the overarching project concept and present initial modeling approaches.

11:25 - 11:50

Andrej Liebert, University of Göttingen

In the context of the Multiscale Tree Graph (MTG) framework, we introduce a new node type called the AggregationNode. This node represents a simplified scale that categorizes the underlying graph structure based on its topology. We present methods for both manual and automated creation of Aggregations, along with their graphical representation and export capabilities.

11:50-12:15

Tianyun Ni, Wageningen University & Research

This research aims to determine the importance of parameters controlling tomato light interception and biomass in the FSP model under the Digital Twin context. A local sensitivity analysis has been done for the model output. This will help us to identify the key model parameters, providing insights on which parameters to focus on in order to improve plant growth simulations.

12:15-12:30