叶片含水量是植物健康状况的重要衡量指标之一。 太赫兹波处于红外和微波之间, 对样品水分变化非常敏感, 当太赫兹光谱穿透含水丰富的叶片时, 叶片中水分等物质能对太赫兹光谱产生强烈的吸收, 根据叶片不同位置处水分含量的不同, 能利用太赫兹光谱技术对植物叶片进行成像。 本研究利用太赫兹技术检测植物叶片的水分含量, 初步探讨植物叶片中水分和太赫兹成像的相关关系。 实验采集离体绿萝叶片, 每隔一定时间通过太赫兹光谱仪对叶片逐点扫描, 获取叶片每一点的太赫兹时域光谱数据, 经过傅里叶变换得到对应频域光谱, 提取时域幅值的光谱参数以及特定频域光谱, 对植物叶片图像进行重构, 获取植物叶片的二维图像。 结果表明, 不同频率下, 绿萝离体叶片的太赫兹二维图像呈现明显差异, 叶肉与叶脉中水分含量不同, 对太赫兹波的吸收也不同, 根据图像, 能清晰显示植物叶片叶肉与叶脉部位的水分含量差异。 通过叶片时域幅值的平均值、 叶片频域平均值与叶片水分含量建立相应的回归模型, 时域最小幅值光谱与水分含量建立的最佳模型预测相关性达0.989 1, 预测均方根误差为0.024 4 g。 研究表明太赫兹技术用于植物叶片的水分含量检测具有较好的研究潜力。

Leaf moisture is an important parameter of plant health, and Terahertz is sensitive to leaf moisture. When terahertz spectra penetrate the leaf, the leaf can be imaged according to different moisture contents at different positions. In this research, Terahertz technology was used to detect the isolated leaf moisture. The relationship between leaf moisture and terahertz spectroscopy data was studied. Terahertz data were obtained by scanning the leaf in vitro. Then the time domain amplitude was obtained and the frequency domain spectra were extracted to rebuild the leaf images. The distribution of the leaf moisture could be clearly observed. This study showed that the image quality with the minimum time domain performed the best. Also, the optimal model was established. The correlation coefficient and the root mean square error of the prediction model were 0.981 7 and 0.023 7 g, respectively. The result of the research provides a guidance to predict live leaf moisture using Terahertz technology in the future.