【摘要】 分析了不同供水条件下的黄瓜茎流日变化规律及环境因素对茎流变化的影响,提出了基于作物茎流变化的作物亏水诊断方法。研究表明:作物茎流的日变化规律明显,茎流的变化与光辐射强度、空气温湿度等气象因子显著相关;在相同的环境下,充分供水与水分亏缺的黄瓜茎流日变化曲线间的相关系数ρ可以反映作物水分的亏缺程度,当ρ<0.80～0.77时,黄瓜叶片出现萎蔫现象。此外,基于作物茎流变化规律,应用神经网络技术开发了作物水分亏缺诊断系统。实验证明:系统的推测值与实测值无明显差异。更多还原

【Abstract】 The diurnal variations of the cucumber stem sap flow(SSF) under different environmental conditions and their effects on SSF were discussed. The study revealed that the dirunal variation of SSF has a clear rhythm. SSF ascends promptly in the morning(6∶00～10∶00 am) and peaks at noon(11∶30～14∶00), then descends slowly towards evening and reaches down to the valley at night.SSF is greatly affected by the meteorological factors such as solar radiation intensily, air huminity and temperature,etc. Under the same environment, the correlation factor ρ of diurnal SSF curves between cucumber stem with and without sufficient water supply reflects the water deficit degree of peant. When ρ <0.80～0.77, the leaves of cucumber begin to wither. Based on the variation of SSF, a plant water deficiency diagnosis system using the neural network technique was developed. The experiments showed that the system prediction is in good agreement with the measured results.更多还原