The Optimization of the 3-d Structure of Plants, Using Functional-Structural Plant Models. Case Study of Rice (Oryza sativa L.) in Indonesia

Utama (2015)

Abstract. One component of the performance of plants is their capability to intercept light. By using a functional-structural modelling approach, an optimization model of the 3-d above-ground structure of plants is constructed, especially for four Indonesian rice varieties. The constructed model consists of three main clusters: rice plant, skylight, and optimization. Virtual experiments, using the optimization method of "simulated annealing", deliver as a result the optimized shape of each rice variety. Twenty-one parameters of rice plant structure are considered in the optimization process.

Keywords: functional-structural plant model, rice, Oryza sativa, optimization, simulated annealing

Taken from Paper: Utama, D.N. 2015. The Optimization of the 3-d Structure of Plants, Using Functional-Structural Plant Models. Case Study of Rice (Oryza sativa L.) in Indonesia [Doctoral Thesis]. Fakultät für Mathematik und Informatik, Georg-August-Universität Göttingen.

A Structural Model of the Rice Plant for Optimizing the Light Interception Capability

Utama and Kurth (2015)
 
Abstract: One important component of the performance of a plant phenotype is its capability to capture photosynthetically active radiation (PAR). By using the approach of functional-structural plant modelling (FSPM) on the software platform GroIMP, a virtual 3-d representation of the above-ground part of a single rice plant was created. The structural model was specified in the programming language XL, which combines object-oriented and rule-based programming. Technically, the model consists of three sub-models: a structural plant model, a radiation model, and, at a meta-level, a toolbox of five different optimization methods, with simulated annealing as the most advanced technique. Our structural model of rice can simulate the vegetative phase of growth of four Indonesian rice varieties and of virtual varieties with a geometry interpolated between the existing ones. Sun movement and skylight simulation (direct and diffuse light) are based on the geographical location of Indonesia, but can easily be adapted to other places on Earth. Intercepted PAR is calculated by stochastic photon tracing. We identified 15 architectural parameters of the rice plant with influence on light interception and applied our optimization methods to them. The platform GroIMP can also be used to compare measured 3-d phenotypes with the optimized virtual shapes.

Taken from Paper: Utama, D.N., Kurth, W. 2015. A structural model of the rice plant for optimizing the light interception capability. International Plant and Algal Phenomics Meeting (IPAP), Prague, Czech
Republic.

Determining the Influence of Plant Architecture on Light Interception of Virtual Rice Plants on the Simulation Platform GroIMP

Utama et al. (2014)

Abstract: Functional-structural plant models (FSPMs) combine the specification of 3-d structure and development of plants with simulation models of some of their functions and thus allow to assess the impact of 3-d architecture on plant performance. The availability and distribution of photosynthetically-active radiation is a key factor for photo-synthesis and biomass production in all green plants. The open-source simulation software GroIMP provides a rule-based model specification language, XL, suitable to generate realistic time series of growing 3-d plant shapes, and a spectral raytracer which allows to estimate the amount of radiative power intercepted by each organ of the virtual plants, taking arbitrary light sources (direct and / or diffuse light) and spectral qualities into account. We designed a rule-based 3-d model of rice plants (Oryza sativa L.) during their vegetative growth phase and parameterized it for different cultivars, particularly, Yongdao 6 and Wuxiangjing 14. The model has a time step of 1 day. Internodes were modelled as cylinders and leaves as NURBS surfaces. A mechanical approach was used to estimate the bending of the leaves under their weight. Architectural parameters, like leaf shape and dimensions, leaf angle, number of tillers and number of leaves, were then varied in a continuum between the values which were reported for the existing cultivars, thus producing a large number of "virtually-bred" intermediate cultivars. In simulation experiments, we measured the total amount of intercepted light at the end of vegetative growth, i.e., at the onset of panicle formation. The optimal parameter combinations which we found could, after some validation and improvement of our model, guide the future breeding of rice for improved resource exploitation. However, in the moment our focus is still on the development of the virtual methods and tools rather than on realistic breeding scenarios.

Keywords: rice (Oryza sativa L.), light interception, plant architecture, FSPM, virtual plants, virtual breeding, radiation regime, simulation, raytracing, XL, GroIMP

Taken from Paper: Utama, D.N., Ong, Y., Streit, K., Kurth, W. 2014. Determining the influence of plant architecture on light interception of virtual rice plants on the simulation platform GroIMP. Proceeding of International Conference on Plant Physiology, pp. 92-101.

Intelligent Model for Distributing Product in Supply Chain Management

Utama et al. (2012)

Abstract. Distributing product is the one of many issues in supply chain management area. There are many variables that have to be involved to solve the problem, such as: type of transportation mode, optimum path, type of product, and performance of supply chain elements. By using multiple criteria decision making concept, we use four methods (fuzzy ant colony optimization, analytical hierarchy process, smoothing exponential, and fuzzy simple additive weighting) to develop generic intelligent model for distributing product in supply chain management as the aims of this paper. We produce generic model to predict future trend, choose the transportation mode, and search the optimum path in supply chain.

Taken from Paper: Utama, D.N., Zulfiandri, Marho, F. 2012. Intelligent model for distributing product in supply chain management. Proceeding of International Conference on Management and Artificial Intelligence, Vol.35, pp. 55-59. 

Intelligent Decision Support Systems for Searching the Optimum Palm Oil based Bio-energy Supply Chain by Using Ant Colony Optimization Method

Utama et al. (2011)

Abstract: Main backgrounds of developing model of intelligent decision support systems, for searching the most optimum supply path in palm oil based bio-energy supply chain management, are importance of supply chain management concept implementation in doing business activities that involve more than one companies; importance of palm oil based bio-energy management availability; and difficulty of management and searching of the most optimum path of perishable product supply chain. The objectives of this paper were the explanation of setting optimum value and searching the most optimum path of palm oil based bio-energy supply chain. The method used in this paper was combination of Balance Score Card (BSC), Supply Chain Operation Reference (SCOR), and ant colony optimization (SCO) methods. On the other hand, this paper explained the model suggestion of the most optimum path and comparation of developed model with the common model (shortest path). In conclusion, the developed model gave more  optimum result than shortest path mehod gave. Furthermore, the model could show the optimum value that was generated from supply chain perspectives. It was better than shortest path method. Whereas, the shortest path method showed only the shortest path that involved only one variable, distance. Finally, the paper suggested that combination of the fuzzy and ant colony optimization method research was needed to do.   

Keywords: palm oil based bio-energy, intelligent decision support system, optimum path, supply chain management, ant colony optimization

Taken from Paper: Utama, D.N., Djatna, T., Hambali, E., Marimin, Kusdiana, D. 2011. Intelligent decision support systems for searching the optimum palm oil based bio-energy supply chain by using ant colony optimization method. Journal of Agroindustrial Technology, Vol.21 No.1, pp. 50-62. 

An UML Modeling for Optimization of Supply Chain in Palm Oil Based Bioenergy



Djatna and Utama (2010)

Abstract: Shifting bioenergy use to be a commercial fuel is an important thing for this moment. The fact said that not only conventional energy (fossil based energy) will be lost in around twenty years later, but also energy demand increases significantly that insist to find energy resource alternative to solve this phenomenon. The best energy resource alternative is biomass resource such as a palm oil based biomass. Technology, management, and supply chain issues are some of many useful research areas to keep bioenergy supply and its availability as a whole. The management of supply chain issue is the one of those issues in bioenergy field research. The classic problem in supply chain management, especially bioenergy supply chain management, is an optimum supply chain path search. In this paper we use ant colony algorithm as our main research contribution. This methodology is used to optimize supply chain path search. The result of this research analysis described by using Unified Modeling Language (UML) that consisted of activity diagram, use case diagram, class diagram, state chart diagram, sequence diagram, and collaboration diagram. We prepare some solution for the problem such as electronic mapping based supply chain route analysis, optimization of supply chain path searching and the best supply chain route search.


Keywords: supply chain path, UML, ant colony optimization (ACO), palm oil based bioenergy

Taken from Paper:  Djatna, T., Utama, D.N. 2010. An UML modeling for optimization of supply chain in palm oil based bioenergy. Proceeding of AFITA International Conference, pp.311-315.