九洲封头

Air negative ions (NAIs) are a crucial indicator of air cleanliness in a region, playing a significant role in regulating human mental health and physiological functions. The photoelectric effect during vegetation photosynthesis is a primary source and influencing factor for NAI generation, but this effect is exceedingly subtle and difficult to monitor directly. Plant electrical signals, on the other hand, serve as an indirect indicator reflecting the photoelectric effect. While previous studies have largely focused on the spatio-temporal variation of NAI in different forest communities and its relationship with meteorological factors, research on the link between NAI and plant electrical signals remains scarce. This study, using Pinus bungeana (whitebark pine) as the subject, employed controlled experiments in an artificial climate chamber to investigate the variation characteristics of plant electrical signals under different light intensities (0, 150, 300, 500, 700, 800, 1000, and 1200 μmol·m-2·s-1) and their relationship with air negative ions.

The results indicate that within the light intensity range of 0 to 700 μmol·m-2·s-1, the intensity of plant electrical signals in Pinus bungeana significantly increases with enhanced light intensity. When the light intensity reaches 700 μmol·m-2·s-1, the activity of plant electrical signals peaks, and further increases in light intensity lead to photoinhibition, causing a decline in plant electrical signal activity. The frequency domain parameters of plant electrical signals (edge frequency, center of gravity frequency, power spectrum entropy, and power spectrum peak) exhibit significant correlations with NAI, among which the edge frequency (E) shows the highest correlation coefficient with NAI. The relationship between the two can be expressed as NAI = 30.981E + 168.814 (R² = 0.54), with a mean square error of 52.203. The significant correlation between plant electrical signals and NAI indicates that plant electrical signals can characterize the variation pattern of NAI, providing a scientific basis for further understanding the mechanism and potential contribution of forest vegetation to NAI.

In recent years, with the rise of forest eco-tourism, air negative ions (NAIs) have garnered increasing attention, and related research has become more active [1-3]. NAIs refer to air ions with an excess of electrons, which are also known as negative oxygen ions due to oxygen molecules' preference for acquiring electrons due to their chemically active nature. They are widely distributed in natural environments such as forests and wetlands [4-5]. NAIs possess various antibacterial properties and biological effects, significantly promoting human mental health and physiological functions [5-6], earning them the title of "air vitamins" [7]. As a result, they have become one of the critical indicators for measuring air cleanliness in a region. The occurrence and influencing mechanisms of NAIs are hot topics in fields such as biometeorology, forest ecology, and forest health preservation [8-10]. Relevant research suggests that changes in NAI concentration are closely related to the photosynthetic process of vegetation. The photoelectric effect during green plant photosynthesis is a vital source and influencing factor for NAI. On the one hand, the photoelectric effect influences the transfer and transmission of electrons within plants; on the other hand, it promotes the crown and leaves of forest vegetation to produce a tip discharge effect, both of which can initiate air ionization outside, thereby promoting the generation of NAI [14]. Therefore, accurately estimating the intensity of the photoelectric effect during forest vegetation photosynthesis and the release of NAI, and quantitatively analyzing the relationship between plant photosynthesis and NAI and its influencing mechanisms, are of great significance for revealing the contribution potential of forest vegetation to NAI.

Since the photoelectric effect of vegetation is extremely subtle, it is currently impossible to monitor it directly and accurately. However, the generation of the photoelectric effect in vegetation is accompanied by the transfer and transmission of electrons, which generates a current in the process. Plant electrical signals can be used to indirectly reflect the intensity of the photoelectric effect. The generation of the photoelectric effect in plants is primarily due to potential fluctuations induced by light stimulation, leading to changes in membrane potential. A potential difference appears between stimulated and resting areas, causing local charge movement to generate an action potential and form a current. The newly generated action potential acts on its neighboring points in the same manner, and this process is transmitted point by point, transmitting the stimulation signal throughout the cell [16]. Action potentials possess the characteristic of non-attenuation during transmission [17], enabling plants to rapidly transmit information over long distances in response to complex environmental changes. When the current generated by action potentials is transmitted to the tips of plant leaves, the charge quantity increases sharply, which can trigger a tip discharge effect, causing air ionization outside and further stimulating the generation of NAI. Since coniferous tree species have larger tip curvatures, the tip discharge effect is more pronounced. Currently, plant electrical signals, as an essential indicator for studying vegetation photosynthetic processes, have been confirmed in related research. For example, Lautner et al. [18] studied the photosynthetic changes of Populus under different thermal stimuli, elucidating the conduction mechanism of plant electrical signals and their relationship with photosynthesis. Eric et al. [19] conducted research on plant biology, elucidating the generation and conduction mechanisms of plant electrical signals. Oyarce et al. [20] used plant electrical signals to study plant sensitivity to light and water, finding that plant electrical signal spectra exhibited different frequency domain characteristics in response to light and water.

Pinus bungeana, a unique coniferous tree species native to northwestern China, is an essential afforestation tree species [21]. This study, taking this species as an example, collected plant electrical signals and NAI concentrations of Pinus bungeana under different lighting conditions, analyzed the variation patterns of plant electrical signals under different light intensities and their relationship with NAI, and provided a scientific basis for revealing the mechanism and contribution potential of forest vegetation to air negative ions.