Crop growth simulation model is one of the most active domains in agricultural science.
作物生长模拟模型是目前农业科学中最为活跃的一个领域。
Crop yield estimation by remote sensing and crop growth simulation models have highly potential application in crop growth monitoring and yield forecasting.
卫星遥感估产和作物生长模拟两项新技术在作物监测和估产方面有巨大的应用价值。
Crop growth simulation models belongs to the core parts of supporting techniques in precision agriculture and intellectualized operations and management softwares in greenhouse production.
作物生长模拟模型是精准农业支持技术的核心部分之一，也是温室生产智能化操作与管理软件的核心部分。
Crop growth simulation is a newly established research area, and useful for understanding, predicting, and then regulating growth and development of crop plantS in response to environment.
作物生长模拟是一门新兴的研究领域。有助于理解、预测和调控作物生长发育及其对环境的反应。
In order to optimize the parameters in a crop growth simulation model, a new method based on nonlinear least squares method was developed for estimation of hidden parameters of crop growth.
为了使作物生长模型中的参数最优化，提出了一种改进型非线性最小二乘法在作物生长模型中隐含参数估计的应用技术，针对多目标项的情况提出了权矩阵的自动计算方法。
Dynamic crop growth simulation models have been developed at a plot or a field scale. However, crop growth monitoring and yield predication at regional scale are concerned by decision makers.
作物生长模型是在田间尺度上开发的，而区域尺度上的作物生长信息更受决策部门的关注。
Aims Accurate simulation of green area index is critical for reliable prediction of crop growth and yield using a crop growth model.
准确模拟绿色面积指数是作物生长模拟模型可靠预测作物生长和产量的关键。
Aims Accurate simulation of green area index is critical for reliable prediction of crop growth and yield using a crop growth model.
准确模拟绿色面积指数是作物生长模拟模型可靠预测作物生长和产量的关键。
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