基于优先分配的玉米单个籽粒生长模拟(英文)

Simulation of maize kernel growth using source-sink approach with priority function

精确预测作物产量对于作物生产、栽培措施优化等具有重要意义。玉米单个籽粒的质量差异对玉米产量有显著影响,并且雌穗不同位置的籽粒获取同化物的能力不同。当前的玉米模型中由于缺乏基于单个籽粒生长机制的模拟过程,从而限制了其在更广泛环境下对产量的模拟精度和预测能力。为了量化雌穗不同位置籽粒对于同化物的竞争能力,基于源库理论建立了玉米单个籽粒灌浆过程的模型,并引入"优先权"方程量化雌穗一列籽粒中每个籽粒获取同化物的"优先"能力,整合进入潜在籽粒生长需求计算新的籽粒库强。通过多年多源库水平的玉米田间试验数据对模型的有效性进行系统评估。结果表明,引入"优先权"后明显提高不同位置籽粒的干质量的模拟精度。这为理解单个籽粒的生长发育过程、玉米产量形成过程提供基础依据。

Accurate estimation of crop yield is important for agricultural research and crop production. However, there can be a large variation of individual kernel size that can have a significant impact on final yield. Current maize models lack mechanistic processes at the individual kernel level and therefore limit their applications for a wide range of environments. Growing kernels can be separated into superior and inferior kernels. Superior kernels have the priority over inferior kernels for receiving carbohydrates. A model was developed to simulate dry matter accumulation of each kernel of an ear using a source-sink approach with a priority function. Model evaluation using experimental data from different plant densities showed that the accuracy for simulating individual kernel on different positions improved significantly when incorporating a priority function into source-sink approach.