Research on ARIMA Parameter Model Analysis Method Based on Plant Electrical Signal

Plant electrical signals are physiological signals that transmit information in plants, and are related to a variety of physiological activities of plants. This paper takes aloe as the research object and uses wavelet packet to analyze and de-noise the original signal of aloe. Plant electrical signal is a weak, non-linear and unstable signal. The traditional methods cannot achieve the research of unstable signal. In this paper, a time series analysis method is proposed to test the stationarity of the de-noised electrical signal and determine the difference order of the model. Model parameters are determined by Akaike Information Criterion(AIC) and the Autoregressive Integrated Moving Average Model(ARIMA) parameter model is established to analyze and predict the de-noised electrical signal. The results show that ARIMA parameter model achieves the stability and prediction of short-term data trends. The ARIMA parameter model analysis method based on plant electrical signals can be used as a new method in greenhouses or plant factories and other environments. It can regulate the external environment where plants are located in the later stage according to the trend amplitude of plant electrical signals and predicted data.