基于植物电信号的小麦苗期等渗干旱胁迫与盐胁迫辨识

针对早期干旱胁迫与盐胁迫在植物处于逆境时难以区分的问题，提出一种基于光诱导植物电信号的干旱胁迫与盐胁迫辨识方法。使用光/暗循环刺激获取了小麦幼苗在正常状态以及等渗干旱胁迫与盐胁迫下的植物叶表面电位，并利用一对一分类策略的支持向量机（One-versus-one support vector machine，OVOSVM）对获取的植物电信号样本进行分类。三折交叉验证结果显示：对正常状态与干旱胁迫下小麦幼苗叶表面电位进行二分类，分类准确率达到100%；对正常状态与盐胁迫下小麦幼苗叶表面电位进行二分类，准确率为94.44%；进行三分类时准确率达到96.30%；对等渗干旱胁迫与盐胁迫下获取的小麦叶表面电位进行二分类，分类准确率为100%。研究表明，植物电信号作为一种辨识逆境胁迫的方法，可对等渗条件下早期干旱胁迫与盐胁迫进行准确区分。

Identification of Isotonic Drought Stress and Salt Stress in Wheat Seedling Based on Plant Electric Signal

In order to solve the problem that drought stress and salt stress are difficult to distinguish in the early stage when plants are under stress, a method was proposed to identify drought stress and salt stress based on light-induced plant electrical signals. The illumination/darkness cycle stimulation was used to obtain the surface potentials of wheat seedlings under normal conditions, as well as under isotonic drought and salt stress. One-versus-one support vector machine (OVOSVM) was used to classify the obtained plant electrical signals. The results of 3-fold cross validation showed that the two-class classification of wheat seedling leaf surface potential under normal and drought stress had an accuracy of 100%, and the two-class classification of leaf surface potential under normal and salt stress had an accuracy of 94.44%. The accuracy of three-class classifications reached 96.30%. Under the conditions of isosmotic drought stress and salt stress, the classification accuracy of wheat seedling leaf surface potential was 100%. The results showed that plant electrical signals can be used as a method to identify adversity stress, and can accurately identify early drought stress and salt stress under isotonic conditions.