虚拟生态环境中的植物生长预报系统初探

植物生长的早期预报在农林业生产和植物栽培业的决策和管理中有着重要的意义。由于生态因素的不确定性,使植物生长的早期预报工作成为了人们不断探索的课题。本文研究了生态因子的变化对植物能量生长过程的影响方式,提出了利用生命能量系统动力学模型对不同生态条件下植物生长仿真的策略和目标函数。根据已往的生态因子组合关系归纳出植物生长的几种典型的生态环境,通过Markov过程虚拟了这些生态环境演变的时间序列。并根据植物生长的实验数据,建立了此环境下的植物生长预报模型,从而模拟植物可能的生长状态,估算生长过程中产量分布的置信区间和各种生长状态的概率。

A Forepart Prediction Model of Plant Vegetative Growth in Virtual Ecological Circumstance

Forepart prediction on plant growth is significant in policy-making and management of agriculture and forestry production. However, stochastic ecological factors interfere the efficiency of the prediction. Based on the analysis of Life Energy System model (LESM), this paper proposed an objective function defined by eigen parameter of LESM. Influenced by ecological factors variation the objective function would govern plant growth in different patterns. Under different typical virtual ecological circumstances which are produced by Markov chain from meteorological record, possible plant growth states and their confidence limits can be predicted, and also the maximum production and its probability can be estimated.