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

被引：0

作者：

Li J. ^{[1
,2
]}

Li Y. ^{[1
,3
]}

De Oliveira R.F. ^{[4
]}

Yao J. ^{[1
,3
]}

Huang L. ^{[1
,3
]}

Wang Z. ^{[1
,2
]}

机构：

[1] College of Information and Electrical Engineering, China Agricultural University, Beijing

[2] Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing

[3] Key Laboratory of Agricultural Information Acquisition Technology (Beijing), Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing

[4] Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo, Piracicaba

来源：

Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery | 2021年 / 52卷 / 07期

关键词：

Isotonic drought stress and salt stress; Leaf surface potentials of wheat seedlings; Light-induced plant electrical signals; Support vector machine;

D O I：

10.6041/j.issn.1000-1298.2021.07.024

中图分类号：

学科分类号：

摘要：

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. © 2021, Chinese Society of Agricultural Machinery. All right reserved.

引用

页码：231 / 236

页数：5

共 29 条

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