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Modeling Leaf Color Dynamic in Rice Plant Based on Spad Value

机译:基于SPAD值的水稻工厂造型叶片颜色动态

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Modeling leaf color dynamics in rice (Oryza saliva L.) is an important task for realizing virtual and digital plant growth. This study was undertaken to analyze the dynamics of leaf color changes at different leaf positions on main stems and tillers under different growing conditions, and to build a dynamic simulation model on leaf color changes in rice plant in relation to growing degree-days (GDD). Time-course observations were made on leaf color (in SPAD value) changes at different leaf positions of stem and tillers under different nitrogen rates and water regimes with four rice cultivars. Leaf color changes in SPAD could be described in three phases. The first phase during leaf elongation period was based on the exponential relationship of leaf color to cumulative GDD; the second phase during leaf function period was represented with a relative stable SPAD; the third phase during leaf senescence period was described in a quadratic equation between SPAD and GDD. In addition, the effects of nitrogen and water conditions on leaf color were quantified through the effectiveness values of leaf nitrogen concentration and water content in relation to SPAD. Then, the RGB (red, green, and blue) values were further predicted from the changing SPAD during leaf development. The model was validated with the independent field experiment data involving different rice cultivars and nitrogen rates. The average root mean square errors (RMSE) between the simulated and observed SPAD values at different leaf positions were 2.58, 3.69 and 3.82, respectively, for three leaf color phases on main stem; 4.65, 4.39, 3.51 and 4.25, respectively, for four individual tillers; and 2.98 and 3.25, respectively, for SPAD and R, G values in rice. The results indicate that the present model has a good performance in predicting leaf color changes at different leaf positions in rice under various growth conditions, and thus lays a foundation for further constructing digital and visual rice growth system.
机译:稻米建模叶片颜色动力学(Oryza Saliva L.)是实现虚拟和数字植物生长的重要任务。本研究进行了在不同生长条件下分析了在主要茎和分蘖下的不同叶子位置的叶子颜色变化的动态,并在生长程度(GDD)中建立水稻植物叶子颜色变化的动态模拟模型。在不同的氮气率和四种水稻品种的不同氮气速率和水中的不同叶子和分蘖下的不同叶子位置的叶子颜色(Spad值)的变化进行了时间过程观测。 SPAD中的叶子颜色变化可以在三个阶段描述。叶伸长期间的第一阶段基于叶子颜色与累积GD的指数关系;叶片函数期间的第二阶段用相对稳定的Spad表示;叶片衰老期间的第三阶段在SPAD和GDD之间的二次方程中描述。此外,通过叶片氮浓度和含水含量与剥片的有效性值量化氮和水条件对叶片颜色的影响。然后,进一步从叶片开发期间从更换的侧面预测RGB(红色,绿色和蓝色)值。该模型与涉及不同水稻品种和氮速率的独立现场实验数据验证。在不同叶子位置的模拟和观察的SPAD值之间的平均均方根误差(RMSE)分别为2.58,3.69和3.82,用于主干上的三个叶子颜色相; 4.65,4.39,3.51和4.25分别为四个单独分蘖; 2.98和3.25分别用于米饭中的SPAD和R,G值。结果表明,本模型在各种生长条件下预测水稻不同叶子位置的叶子颜色变化具有良好的性能,因此为进一步构建数字和视液生长系统奠定了基础。

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