Key Laboratory of Arable Land Conservation (North China), Ministry of Agriculture, College of Resources and Environmental Sciences, China Agricultural University, Beijing.
Institute of Vegetables and Flowers, Chinese Academy of Agricultural Science, Beijing, China.
Ann Bot. 2018 Apr 18;121(5):961-973. doi: 10.1093/aob/mcx189.
Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel).
The model used potential individual kernel growth rates to characterize the individual potential sink demand. The remobilization of non-structural carbohydrates from reserve organs to kernels was also incorporated. Two years of field experiments were conducted to determine the model parameter values and to evaluate the model using two maize hybrids with different plant densities and pollination treatments. Detailed observations were made on the dimensions and dry weights of individual kernels and other above-ground plant organs throughout the seasons.
Three basic traits characterizing an individual kernel were compared on simulated and measured individual kernels: (1) final kernel size; (2) kernel growth rate; and (3) duration of kernel filling. Simulations of individual kernel growth closely corresponded to experimental data. The model was able to reproduce the observed dry weight of plant organs well. Then, the source-sink dynamics and the remobilization of carbohydrates for kernel growth were quantified to show that remobilization processes accompanied source-sink dynamics during the kernel-filling process.
We conclude that the model may be used to explore options for optimizing plant kernel yield by matching maize management to the environment, taking into account responses at the level of individual kernels.
在谷物模拟模型中如果不能考虑到内核生长的变化，可能会导致作物产量的估计严重偏差。本研究的目的是修订 GREENLAB-玉米模型，纳入源和汇限制分配方法来模拟穗上单个玉米籽粒的干物质积累（GREENLAB-玉米-内核）。
该模型使用潜在的单个籽粒生长速率来描述单个潜在的汇需求。还纳入了从储备器官向籽粒再分配非结构性碳水化合物的过程。进行了两年的田间试验，以确定模型参数值，并使用具有不同种植密度和授粉处理的两种玉米杂交种来评估模型。在整个季节中，对单个籽粒和其他地上植物器官的尺寸和干重进行了详细观察。
模拟和测量的单个籽粒之间比较了三个描述单个籽粒的基本特征：（1）最终籽粒大小；（2）籽粒生长速率；（3）籽粒填充持续时间。单个籽粒生长的模拟与实验数据非常吻合。该模型能够很好地再现观察到的植物器官的干重。然后，量化了源-汇动态和用于籽粒生长的碳水化合物的再分配，以表明在籽粒填充过程中，再分配过程伴随着源-汇动态。
我们得出结论，该模型可以用于通过将玉米管理与环境相匹配来探索优化植物籽粒产量的方案，同时考虑到单个籽粒水平的响应。
