[Variation characteristics of plant electrical signal and their relationship with negative air ion under different light intensities.] / ä¸åŒå ‰ç §å¼ºåº¦ä¸‹æ¤ç‰©ç”µä¿¡å·å˜åŒ–ç‰¹å¾åŠå ¶ä¸Žç©ºæ°”è´Ÿç¦»å­çš„å ³ç³».

ABSTRACT

Negative air ion (NAI) is an essential indicator for measuring air cleanliness of a given area, with vital role in regulating psychological and physiological functions of human body. The photoelectric effect is an important source and influencing factor for the generation of NAI during photosynthesis, but the photoelectric effect is extremely weak and difficult to monitor. Plant electrical signal is an important indicator that indirectly reflects photoelectric effect. Previous studies mostly focused on the spatiotemporal variation of NAI in different forest communities and its relationship with meteorological factors. At present, there is little research on NAI and plant electrical signal. In this study, we explored the effect of different light intensities (0, 150, 300, 500, 700, 800, 1000 and 1200 µmol·m-2·s-1) on characteristics of the plant electrical signal and its relationship with negative air ion, with Pinus bungeana as the research object. The results showed that the intensity of plant electrical signal increased significantly with the increases of light intensity in the illumination range of 0-700 µmol·m-2·s-1. When light intensity reached 700 µmol·m-2·s-1, plant electrical signal activity reached the highest level, and plant was inhibited by light when light intensity increased further, with plant electrical signal activity decreased. The frequency-domain parameters (edge frequency, gravity frequency, power spectrum entropy and power spectrum peak) of plant electrical signals were significantly correlated with NAI. The correlation coefficient between edge frequency (E) and NAI was the highest, the relationship between them was NAI=30.981E+168.814 (R2=0.54), and the mean square error was 52.203. There was a significant correlation between plant electrical signals and NAI, which could characterize the change rule of NAI, and provide scientific evidence for further understanding the contribution potential and production mechanism of forest to NAI.