当前位置: X-MOL 学术J. Agric. Sci. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Modelling and inference of maize pollen emission rate with a Lagrangian dispersal model using Monte Carlo method
The Journal of Agricultural Science ( IF 1.7 ) Pub Date : 2020-10-01 , DOI: 10.1017/s0021859620000763
Otmane Souhar , Alexis Marceau , Benjamin Loubet

This work explores the uncertainty of the inferred maize pollen emission rate using measurements and simulations of pollen dispersion at Grignon in France. Measurements were obtained via deposition of pollen on the ground in a canopy gap; simulations were conducted using the two-dimensional Lagrangian Stochastic Mechanistic mOdel for Pollen dispersion and deposition (SMOP). First, a quantitative evaluation of the model's performance was conducted using a global sensitivity analysis to analyse the convergence behaviour of the results and scatter diagrams. Then, a qualitative study was conducted to infer the pollen emission rate and calibrate the methodology against experimental data for several sets of variable values. The analysis showed that predicted and observed values were in good agreement and the calculated statistical indices were mostly within the range of acceptable model performance. Furthermore, it was revealed that the mean settling velocity and vertical leaf area index are the main variables affecting pollen deposition in the canopy gap. Finally, an estimated pollen emission rate was obtained according to a restricted setting, where the model studied includes no deposition on leaves, no resuspension and with horizontal pollen fluctuations either taken into account or not. The estimated pollen emission rate obtained was nearly identical to the measured quantity. In conclusion, the findings of the current study show that the described methodology could be an interesting approach for accurate prediction of maize pollen deposition and emission rates and may be appropriate for other pollen types.

中文翻译:

使用蒙特卡罗方法的拉格朗日扩散模型对玉米花粉排放率的建模和推断

这项工作通过测量和模拟法国 Grignon 的花粉扩散来探索推断的玉米花粉排放率的不确定性。测量结果是通过花粉在树冠间隙的地面上沉积获得的;使用用于花粉分散和沉积 (SMOP) 的二维拉格朗日随机机制模型进行模拟。首先,使用全局敏感性分析对模型的性能进行定量评估,以分析结果和散点图的收敛行为。然后,进行了一项定性研究,以推断花粉释放率,并针对多组变量值的实验数据校准方法。分析表明,预测值与观测值吻合良好,计算出的统计指标大多在模型性能可接受的范围内。此外,还揭示了平均沉降速度和垂直叶面积指数是影响冠层间隙花粉沉积的主要变量。最后,根据受限设置获得估计的花粉排放率,其中研究的模型包括叶片无沉积、无再悬浮以及考虑或不考虑水平花粉波动。获得的估计花粉释放率与测量的数量几乎相同。综上所述,
更新日期:2020-10-01
down
wechat
bug