水肥亏缺下水稻叶片气孔导度与光合速率耦合模型

叶片气孔导度．光合速率的耦合模型是作物生理模拟的关键，是估算作物生长及水分利用动态的基础．采用盆栽试验实测资料，建立Leuning—Ball气孔导度模型及其耦合模型，考虑水肥因子对气孔导度、光合速率的影响，引入水稻叶片叶气温差、叶绿素相对含量修正气孔导度模型，并进行比较．结果表明，考虑叶气温差、叶绿素相对含量的气孔导度-光合速率耦合模型具有针对水肥限制条件下更高的模拟验证解释能力，针对气孔导度，最大相对误差由125．5％、128．8％分别降至98．2％和126．6％，针对光合速率，平均相对误差由32．3％、74．3％降至20．5％和39．3％，最大相对误差则由331．5％、327．9％降至177．1％和113．4％．

A Coupled Model of Photosynthesis and Stomatal Conductance for Rice Leaves with Soil Moisture and Nitrogen Deficit

A leaf-scale coupled approach to photosynthesis-stomatal conductance modeling is a key element in predicting physiology of crop, estimating crop growth and water use. In order to consider the effect of moisture and nitrogen deficit of soil on stomatal conductance and photosynthesis, the leaf-air temperature and chlorophyll relative content were introduced to regulate coupled Leuning-Ball photosynthesis-stomatal conductance model. Field data of a pot experiment were used to validate the model. The results show that the improved coupled model yields reasonable interpretation and the best photosynthesis interpretation ability under soil moisture and nitrogen deficit. For stomatal conductance, the maximum relative errors were reduced from 125.5% and 128.8% to 98.2% and 126.6%. For photosynthetic rate, the average relative errors were reduced from 32.3%, 74.3% to 20.5% and 39.3%, and the maximum relative errors from 331.5% and 327.9% down to 113.4% and 177.1%, respectively. The coupled model can reflect the water and energy situation considering the limiting water and nitrogen more reasonably.