分别获取了棉花新陆早33号、13号2个品种在5个关键生育时期经5种水分处理后的冠层红外热图像和叶片水势（ψL）。从红外热图像中提取了棉花冠层受光叶片的温度，计算了棉花的作物水分胁迫指数（Crop Water Stress Index,CWSI）。分析表明， 2个品种的棉花经5种水分处理后冠层的CWSI和ψL随生育进程的变化趋势相反，ψL与棉花的生育进程趋势一致，变化顺序均为W5>W4>W3>W2>W1。利用棉花建模样本的CWSI与ψL的线性相关函数方程（r= -0.8903**，n=24, α=1%）对检验样本的ψL进行了估测。实测的ψL与估测的ψL呈极显著线性关系（r= 0.8971**，RMSE=0.1223，n=24, α=1%），估测的ψL的相对误差为0.0981，估计精度为90.2%。结果表明，由红外热图像提取的CWSI能够实时、快速、非破坏性地估算棉花叶片的水势，较精确地预测棉花的水势。

The infrared thermal images and leaf water potential (ψL) of two cotton cultivars named Xinluzao-33 and -13 were obtained at five growth stages after five different irrigation processes. The temperature values of the canopysunlit leaves were extracted from the thermal images and the crop water stress indexes (CWSI) were calculated. The analysis result showed that the canopy CWSI and ψL of two cotton cultivars at five different irrigation levels changed inversely withthe growth stage, and the ψL was consistent with the growth of cotton. Their change orders were all W5>W4>W3>W2>W1. The ψL of the tested samples was estimated by using the linear regression function between the CWSI and ψL of the modeled samples (r=0.8903,n=24,α=1%). The measured ψL had a significant linear correlation with the estimated ψL (r=08971,RMSE=0.1223,n=24,α=1%). The estimated ψL had a relative error of 0.0981. Its estimation accuracy was 90.2%. The result showed that the CWSI based on the infrared thermography could be used to estimate the leaf water potential of cotton rapidly and nondestructively in real time and could be used to predict the water potential accurately.