利用功能结构模型GREENLAB研究棉花叶片脱落对植株生长的影响

Z. Zhan, H. Rey, D. Li, Yan Guo, P. Cournède, P. de Reffye
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引用次数: 8

摘要

对于功能结构植物模型GREENLAB,可以以植物结构数据为目标,通过模型反演获取源汇关系参数。为了更精确地研究源器官的产生,在单茎棉花植株上进行了对照落叶试验。采用四种常规的叶片修剪处理,与对照植株(单茎植株保留所有叶片)相比,单茎植株在整个植株发育过程中茎顶保留一定数量的功能叶片(分别为6、9、12和15)。结果表明:以保留12片功能叶片处理的地上鲜生物量最高,显著高于对照植株;研究发现,GREENLAB优化后的源汇关系功能参数与植物保留的功能叶片数量有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on the Effects of Defoliation on the Growth of Cotton Plant Using the Functional Structural Model GREENLAB
For the functional structural plant model GREENLAB, parameters for the source and sink relationships can be retrieved through model inversion with plant architectural data as targets. In order to study more precisely the production of source organs, a controlled defoliation experiment was performed on single-stemmed cotton plants. Four regular leaf-pruning treatments were implemented to produce single-stemmed plants that retained a given number of functional leaves (i.e., 6, 9, 12 and 15, respectively) at the top of stem during the whole period of plant development, and compared with control plants (single-stemmed plants retaining all the leaves). Results show that the most productive treatment in terms of fresh above-ground biomass was the treatment with 12 functional leaves retained, which were significantly greater than control plants. The optimized functional parameters of GREENLAB for the source and sink relationships were found to be affected in relation with the number of functional leaves retained on the plants.
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