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Plant electrical signals often contains low frequency drifts with or withoutthe application of external stimuli. Quantification of the randomness in plantsignals in a stimulus-specific way is hindered because the knowledge of vitalfrequency information in the actual biological response is not known yet. Herewe design an optimum Infinite Impulse Response (IIR) filter which removes thelow frequency drifts and preserves the frequency spectrum corresponding to therandom component of the unstimulated plant signals by bringing the bias due tounknown artifacts and drifts to a minimum. We use energy criteria of waveletpacket transform (WPT) for optimization based tuning of the IIR filterparameters. Such an optimum filter enforces that the energy distribution of thepre-stimulus parts in different experiments are almost overlapped but underdifferent stimuli the distributions of the energy get changed. The reportedresearch may popularize plant signal processing, as a separate field, besidesother conventional bioelectrical signal processing paradigms.

Drift Removal in Plant Electrical Signals via IIR Filtering Using Wavelet Energy