Arrangement Analysis of Leaves Optimized on Photon Flux Density or Photosynthetic Rate

摘要

By clarifying a plant evolutive process, useful information may be obtained on engineering. Consequently, an analysis algorithm that investigates the optimal arrangement of plant leaves was developed. In the developed algorithm, the Monte Carlo method is introduced and sunlight is simulated. Moreover, the arrangement optimization of leaves is analyzed using a Genetic Algorithm (GA). The number of light quanta (photon flux density) that reaches leaves, or the average photosynthetic rate of the same was set as the objective function, and leaf models of a dogwood and a ginkgo tree were analyzed. The number of leaf models was set between two to four, and the position of the leaf was expressed in terms of the angle of direction, elevation angle, rotation angle, and the representative length of the branch of a leaf. The chromosome model introduced into GA consists of information concerning the position of the leaf. Based on the analysis results, the characteristics of the leaf of an actual plant could be simulated by ensuring the algorithm had multiple constrained conditions. The optimal arrangement of leaves differs in maximization of the photon flux density, and that of the average value of a photosynthetic rate. Furthermore, the leaf form affecting the optimal arrangement of leave and also having a significant influence also on a photosynthetic rate was shown.