Regulation of tillering in sorghum: environmental effects
Regulation of tillering in sorghum: environmental effects
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DOI：
10.1093/aob/mcq079
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发表时间：
2010-07-01
期刊：
影响因子：
4.2
通讯作者：
Hammer, Graeme
中科院分区：
文献类型：
--
作者：
Kim, Hae Koo;van Oosterom, Erik;Hammer, Graeme
分蘖对高粱冠层发育具有显著影响，因此对高粱的资源捕获、作物生长和籽粒产量具有显著影响。然而，分蘖的生理基础及其受环境影响的调节尚未完全了解。为了解和定量分析环境对高粱分蘖的影响，采用碳水化合物供需模型，在不同温度和光照条件下，对高粱分蘖的影响进行了研究。植物内部竞争碳水化合物的概念被开发用于分析这些响应。分蘖的出现与主茎叶的出现高度同步，在不同环境中分蘖具有一致的层次结构。主要的环境效应是分蘖出现的频率，特别是低级别的分蘖。这解释了一些观察到的分蘖发生的环境差异。一个综合的植株内部竞争指数（S/D指数）考虑了分蘖关键期植株同化物的供给和需求，解释了5个试验中最大分蘖数的大部分变化，这一结果与植株内部同化物竞争调节高粱分蘖的假说一致。因此，概述的框架具有预测价值，可以为作物生长模型中的分蘖动态模拟提供基础。
Tillering has a significant effect on canopy development and, hence, on resource capture, crop growth and grain yield in sorghum. However, the physiological basis of tillering and its regulation by environmental effects are not fully understood. The objective of this study was to understand and quantify the environmental effects on tillering in sorghum using a carbohydrate supply-demand framework.A series of five experiments with a wide range of radiation and temperature conditions was conducted and details of the tillering responses of a single representative hybrid were monitored. The concept of internal plant competition for carbohydrate was developed for analysis of these responses.Tiller appearance was highly synchronized with main shoot leaf appearance, with a consistent hierarchy for tillering across environments. The main environmental effect was on the frequency of tiller appearance, in particular of the lower-rank tillers. This explained some of the observed environmental differences in the onset of tillering. A generalized index of internal plant competition, which took account of plant assimilate supply and demand (S/D-index) during the critical period for tillering, explained most of the variation in maximum tiller number observed across the five experiments.This result was consistent with the hypothesis that internal plant competition for assimilates regulates tillering in sorghum. Hence, the framework outlined has a predictive value that could provide the basis for dynamic simulation of tillering in crop growth models.