Cici S-Zahra-Hosseini, Adkins Steve, Hanan Jim
Advanced Computational Modeling Center, University of Queensland, St Lucia, Brisbane, 4072, Australia.
Ann Bot. 2008 Jun;101(9):1311-8. doi: 10.1093/aob/mcn040. Epub 2008 Mar 28.
Improving the competitive ability of crops is a sustainable method of weed management. This paper shows how a virtual plant model of competition between chickpea (Cicer arietinum) and sowthistle (Sonchus oleraceus) can be used as a framework for discovering and/or developing more competitive chickpea cultivars.
The virtual plant models were developed using the L-systems formalism, parameterized according to measurements taken on plants at intervals during their development. A quasi-Monte Carlo light-environment model was used to model the effect of chickpea canopy on the development of sowthistle. The chickpea-light environment-sowthistle model (CLES model) captured the hypothesis that the architecture of chickpea plants modifies the light environment inside the canopy and determines sowthistle growth and development pattern. The resulting CLES model was parameterized for different chickpea cultivars (viz. 'Macarena', 'Bumper', 'Jimbour' and '99071-1001') to compare their competitive ability with sowthistle. To validate the CLES model, an experiment was conducted using the same four chickpea cultivars as different treatments with a sowthistle growing under their canopy.
The growth of sowthistle, both in silico and in glasshouse experiments, was reduced most by '99071-1001', a cultivar with a short phyllochron. The second rank of competitive ability belonged to 'Macarena' and 'Bumper', while 'Jimbour' was the least competitive cultivar. The architecture of virtual chickpea plants modified the light inside the canopy, which influenced the growth and development of the sowthistle plants in response to different cultivars. This is the first time that a virtual plant model of a crop-weed interaction has been developed. This virtual plant model can serve as a platform for a broad range of applications in the study of chickpea-weed interactions and their environment.
提高作物的竞争力是一种可持续的杂草管理方法。本文展示了鹰嘴豆（鹰嘴豆属）与苦苣菜（苦苣菜属）之间竞争的虚拟植物模型如何能够作为一个框架，用于发现和/或培育更具竞争力的鹰嘴豆品种。
使用L - 系统形式主义开发虚拟植物模型，并根据植物在发育过程中间隔测量的数据进行参数化。使用准蒙特卡罗光环境模型来模拟鹰嘴豆冠层对苦苣菜发育的影响。鹰嘴豆 - 光环境 - 苦苣菜模型（CLES模型）验证了这样一个假设，即鹰嘴豆植株的结构改变了冠层内的光环境，并决定了苦苣菜的生长和发育模式。对不同的鹰嘴豆品种（即‘马卡雷纳’、‘丰收’、‘吉姆布尔’和‘99071 - 1001’）的所得CLES模型进行参数化，以比较它们与苦苣菜的竞争能力。为了验证CLES模型，进行了一项实验，使用相同的四个鹰嘴豆品种作为不同处理，让苦苣菜在它们的冠层下生长。
在计算机模拟和温室实验中，苦苣菜的生长受‘99071 - 1001’（一个叶龄期短的品种）的抑制最大。竞争能力排名第二的是‘马卡雷纳’和‘丰收’，而‘吉姆布尔’是竞争力最弱的品种。虚拟鹰嘴豆植株的结构改变了冠层内的光照，这影响了苦苣菜植株对不同品种的生长和发育反应。这是首次开发出作物 - 杂草相互作用的虚拟植物模型。这个虚拟植物模型可以作为一个平台，用于鹰嘴豆 - 杂草相互作用及其环境研究中的广泛应用。
