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A DYNAMIC MODEL TO ESTIMATE IN–CANOPY AND LEAF–SURFACE MICROCLIMATE OF GREENHOUSE CUCUMBER CROPS

机译:估算温室黄瓜叶片冠层和叶面微气候的动态模型

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摘要

A dynamic one-dimensional model, PSCLIMATE, was developed to simulate microclimate on and around leaf surfaces for greenhouse cucumbers. Based on an energy balance of plant leaves and heat and mass transfer among air strata and leaves, the model predicts climate profiles within a plant canopy and the microclimate within a leaf surface boundary layer. The simulated in-canopy and leaf-surface climate profiles can be used to improve the prediction of pest outbreaks and their control for greenhouse cucumbers. Validation of the model with data collected from a glass greenhouse indicated that air temperature (T a ) and relative humidity (RH a ) within the canopy were accurately predicted (RMSDs 0.6°C and 2.9% at night and RMSDs 0.2°C and 3.9% in the daytime). Leaf surface temperature (T l ) was predicted with an RMSD 1.3°C for shaded leaves and 2.7°C for sunlit leaves. Leaf wetness incidence, as measured by a leaf wetness sensor, was predicted correctly for a sunlit leaf but not for a shaded leaf. Predicted vapor pressure deficit within the leaf surface boundary layer provides information that cannot be measured directly by sensors. This model can be used for other crop canopies or greenhouse structures once the specific characteristics of the greenhouse structure and the plant canopy are defined. Further improvements to the model are discussed
机译:建立了动态​​一维模型PSCLIMATE,以模拟温室黄瓜叶片表面上和周围的微气候。基于植物叶片的能量平衡以及空气层和叶片之间的热量和质量传递,该模型可以预测植物冠层内的气候特征以及叶片表面边界层内的微气候。模拟的冠层内和叶表面气候概况可用于改善对害虫暴发的预测及其对温室黄瓜的控制。使用从玻璃温室中收集的数据对模型进行的验证表明,可以准确地预测冠层内的气温(T a )和相对湿度(RH a )(RMSDs <0.6晚上的温度为2.9%,白天的RMSD <0.2°C,白天为3.9%)。预测叶片表面温度(T l ),其中阴影叶片的RMSD <1.3°C,阳光叶片的RMSD <2.7°C。通过叶子湿度传感器测量的叶子湿度发生率可以正确预测阳光照射的叶子,而不是阴影阴影的叶子。预测的叶片表面边界层内的蒸气压不足会提供传感器无法直接测量的信息。一旦定义了温室结构和植物冠层的特定特征,该模型就可以用于其他农作物冠层或温室结构。讨论了模型的进一步改进

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