Research on the relationship between electrical signal and growth state of plants based on temperature factor

It is a weak signal that changes the resting potential of plant cells or tissues under the stimulation of external environmental factors and can be transmitted between cells and tissues. Plant electrical signals are closely related to plant movement, growth, metabolism, etc., and the characteristic changes of plant electrical signals can then respond to the growth condition of the plant itself. In this paper, the electrical signals of Aloe vera are related to plant movement, growth, and metabolism. In this paper, according to the time-frequency domain distribution of this Aloe vera electrical signal, we choose to improve the wavelet threshold noise reduction to process the original electrical signal and then use the empirical mode decomposition into multiple eigenmode functions from 0-5Hz, multiple eigenmode functions form a two-dimensional time-frequency matrix signal and input the two-dimensional time-frequency matrix signal into the convolutional neural network for training to get the general law of plant electrical signal and plant growth state under different temperature levels. To further improve the model accuracy, the convolutional neural network model is optimized in this paper by adding a two-layer bidirectional LSTM behind the CNN.