Abstract
At present, water shortage in agriculture becomes more and more serious. This situation makes it necessary to develop precision irrigation, which needs to obtain the accurate crop water stress in advance. However, this signal is too weak to be detected easily. Wavelet analysis has been widely used in the signal processing area for almost two decades due to its excellent time-frequency analysis ability. Therefore, the wavelet decomposition and reconstruction technique is applied to reduce the noises of experimental data collected from corn plants in a farmland. Finally, data analysis results show that wavelet denoising is effective to achieve the weak signal extraction.
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