Aiming at the problem that the signal generated in capacitive cotton seeding monitoring contained noise and thus the seeding information was not easy to be extracted, the CEEMDAN-wavelet threshold joint noise reduction method was proposed. Firstly, according to the detection principle of cotton seedling quality, the noisy simulation signal was constructed, and the empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) denoising effects of three traditional methods were compared on normal seeding, missed seeding, and repeat seeding simulation signals. Secondly, the wavelet threshold denoising method was integrated into the CEEMDAN denoising method, and the threshold formula of the correlation coefficient was designed to differentiate a large number of intrinsic mode function (IMF) componented with a large number of noisy and IMF components with effective signals, and the noise in the noisy IMF components was removed and more of the shape characteristics of the original signal were retained, and the signal-to-noise ratio(SNR) of the omitted rebroadcasting was increased by 4.9509dB and 6.8493dB, respectively. The similarity of the curve (NCC) was increased by 0.0280 and 0.0549, and smoothness(SR) was decreased by 0.0024 and 0.0045, respectively, which improved the problem of the poor noise reduction effect of the CEEMDAN denoising method alone on the omitted replay signal. Finally, a rowing signal acquisition test platform was built to validate the proposed method, and the results showed that the method had good noise reduction and signal feature reduction capability, and after noise reduction, it implemented a noise reduction effect on the number of distinguished seeds. The results showed that the method had good noise reduction and signal feature reduction ability, and the noise reduction could realize monitoring of number of sown seeds.