Published online July 11, 2022
Journal of Ecology and Environment (2022) 46:16
© The Ecological Society of Korea.
Department of Biological Science, Kongju National University, Gongju 32588, Republic of Korea
Correspondence to:Young-Han You
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Results: In order to examine the changes in the physiological and growth responses of
Conclusions: The light condition suitable for the propagation by the stolons, which are the propagules of
Keywords: artificial light, light stress, photosynthesis, rhizome, stolon, vegetative propagation, wetland plant
Nowadays, one of the most important issues related to ecology in the world is the restoration of endangered species, and the cause of the threat is largely due to man-made habitat destruction (Primack 2004). The loss of these species can also adversely affect the ecosystem as endangered species mainly are specialist that play an important role in inter-species interaction within the ecosystem (Dehling et al. 2021). In order to maintain the population sizes of endangered species due to habitat destruction, approaches should be attempted from a restoration ecological viewpoint. Ecological restoration refers to the attempt to return an ecosystem to a certain point in time in the past, but it is difficult or impossible. Therefore, ecological restoration should proceed through realistic goal setting (Falk et al. 2006).
As an ecological restoration method as such, a method of reintroducing the endangered species into their natural habitats can be used (Clements 2013). However, in order to re-introduce a certain species and lead to the resettlement of the species, a problem that a certain number of the individual plant species should be secured in advance should be solved. In addition, in the case of reintroduction, the degree to which the genetic diversity of the population that will be introduced is similar to that of the original population is one of the issues that must be considered (Falk et al. 2006). Furthermore, species preservation through reintroduction is not always successful (Allen 1994). Therefore, rather than collecting and introducing a small number of the endangered plant from another area, a measure to secure a large number of individuals with genetic diversity close to that of the individuals of the original population through artificial cultivation and proliferation including vegetative propagation in a facility where the effects of the surrounding environments are minimized is necessary.
However, for propagation studies as such, first, basic ecophysiological research on the plant should precede. Ecophysiological approaches to the restoration of rare plants can improve the outcome of restoration so that the plants can settle and grow in disturbed environments by analyzing the interactions between the plants and the environments (Valliere et al. 2021). The smart farm is an optimal technology for such research. A smart farm is a facility that can improve plant productivity by monitoring the physical environment, soil, fertilizer, water supply, and plant growth based on information communication technologies (ICT), the Internet of things (IoT), and big data analysis (Jayaraman et al. 2016).
A smart farm can use sunlight and artificial light as light sources for plant cultivation (Mahdavian and Wattanapongsakorn 2017). However, using only sunlight as a light source can be economical for crop cultivation (Mahdavian and Wattanapongsakorn 2017), but it is not suitable for studies on the optimal light quality for plant cultivation. Therefore, using light-emitting diode (LED) light as a light source for such studies is appropriate. Whereas fluorescent lamps, incandescent lamps, high pressure sodium lamps, high pressure mercury lamps, and metal halides, which are light sources used as artificial light sources, have wide spectrums instead of single wavelengths and cannot supply a sufficient amount of photosynthetic photon flux density (PPFD) so that it is difficult to expect high plant productivity, LED light enables selecting certain optical wavelengths, has a long lifespan, and reaches the maximum output immediately after the switch is turned on so that high light frequencies can be set to save power (Dutta Gupta and Agarwal 2017; D’Souza et al. 2017). In addition, since it generates less heat than other light sources, heat damage to plants can be reduced, so that the distance between the light source and the plant can be maximally reduced in cultivation to use the cultivation space efficiently (Dutta Gupta and Agarwal 2017).
Since plants store energy through photosynthesis and use the energy for growth and reproduction (Jansson et al. 2021), light quality can affect plant productivity (Yavari et al. 2021). The photosynthetic reactions according to light quality are regulated by various physiological variables including the leaf temperature, transpiration rate, photosynthetic quantum efficiency, and intercellular CO2 partial pressure (Galle et al. 2009; Kim et al. 2013; Simon et al. 2018; Vilfan et al. 2019). However, the photosynthetic pathways of
The size of the smart farm (Plant Factory System, Parus, Shanghai, China) used in this study is 582 cm wide, 334 cm long, and 260 cm high, and chambers that enables treatments with different light conditions were installed on the shelf inside the smart farm. The size of each of the chambers is 120 cm in width, 52 cm in length, and 41.5 cm in height, and LED panels are installed on the ceiling of each chamber.
In order to examine changes in the physiological and growth responses of
Based on the foregoing, the light irradiation time ratios of blue light to red light in three chambers were set to 1:1 (T1), 1:1/2 (T2), and 1:1/5 (T3), respectively. The light irradiation time ratio of red light, blue light, and white light in the remaining one chamber was set to 1:1:1 (T4). In this case, the ratio of blue light to red light (B:R) was 0.64 in T1, 0.32 in T2, 0.13 in T3, and 0.36 in T4.
The temperature inside the plant factory was kept constant using a hot and cold air blower (SS-2000; Zero Engineering, Daejeon, Korea), and the humidity was kept constant using a humidifier. The amount of light in each chamber was adjusted using a computer so that a constant amount of light was maintained at the height of the water tank. The data on the physical environment inside the plant factory was transmitted to the computer at 30-minute intervals through the sensors installed inside each chamber.
The amount of light (mean ± standard deviation) in the smart farm during the experiment period was 107.98 ± 17.61
In the case of
Factor analysis was carried out to identify major factors and variables for changes in the physiological response of
Simple regression analysis was performed to identify the trend of the growth response of
According to the results of the factor analysis, the variables that showed correlations with factor 1 were W, ΔT, E, and Pn, and the variables that showed correlations with factor 2 were B:R, W, Ci, Pn, and Φ (Table 1). The key variables of factor 1 were W, ΔT, E, and Pn, and the key variables of factor 2 were B:R, Ci, and Φ (Table 1). The variables that commonly showed correlations with factor 1 and factor 2 were W and Pn (Table 1).
When the factor score distribution area for the four light conditions was divided into 4 groups according to individual light conditions, T1, which had the highest ratio of blue light to red light, was mainly located in the third quadrant, and T4 treated with white light was located in the first quadrant. Therefore, the physiological changes due to blue light and white light had opposite tendencies from each other (Fig. 1). T2, which had a lower blue light ratio and a relatively high red light ratio compared to T1, was mainly distributed in the second quadrant, and T3 was mainly distributed in the fourth quadrant (Fig. 1). However, the distribution area of T2 and T3 overlapped in part (Fig. 1).
According to the results of the path analysis, the increase in B:R increased ΔT (
According to the results of the simple regression analysis, the number of leaves of branches (
According to the result of the Mann–Whitney U-tests, the numbers of the aerial and stolons of
As the blue light ratio increased, the leaf temperature and photosynthetic quantum efficiency of
In contrast, when treated with white light, the leaf temperature and photosynthetic quantum efficiency of
The increase in leaf temperature and photosynthetic quantum efficiency increased the net photosynthetic rate (Fig. 3). However, the increase in the blue light ratio increased the leaf temperature and photosynthetic quantum efficiency while decreasing the net photosynthetic rate and white light treatment decreased leaf temperature and photosynthetic quantum efficiency while increasing the net photosynthetic rate. These results mean that the absorption of excessive light energy not used for photosynthesis increases when the ratio of blue light increases, and on the contrary, when white light is added, the absorption of excessive light energy relatively decreases.
Meanwhile, blue light is known as a direct signal inducing stomatal opening (Inoue and Kinoshita 2017).
In this study, an increase in the leaf temperature increased the intercellular CO2 partial pressure. This result is thought to be related to photorespiration. Plants use photorespiration to directly use molecules such as ATP or NADPH thereby removing excess energy or increasing the amount of internal CO2 in order to suppress the accumulation of harmful reactive oxygen species generated under light stress (Voss et al. 2013). In addition, when the leaf temperature rises, the solubility of CO2 in water decreases, so that CO2 cannot be used for photosynthesis and can be accumulated in the substomatal cavity. Therefore, it is judged that the net photosynthetic rate decreases as the intercellular CO2 partial pressure increases (Fig. 3).
However, the increase in the blue light ratio increased the leaf temperature while simultaneously decreasing the intercellular CO2 partial pressure and on the other hand, white light treatment decreased the leaf temperature while simultaneously increasing the intercellular CO2 partial pressure (Fig. 3). Given that the increase in the blue light ratio consequently decreased the net photosynthetic rate of
Based on these results, when the blue light ratio increased, the photosynthetic quantum efficiency of
When the ratio of blue light to red light increased, the number of leaves of the branches of
The number of branches of
In addition, there was no difference in the length and number of leaves of the branch of
The increase in the blue light ratio increased the number of stolons of
Treatment with white light increased the number of stolons similar to the increase in blue light ratio (Tables 2, 3). However, it produced a greater number of stolons than when only blue light was irradiated (Table 3). This is because more efficient production of photosynthetic products is possible by increasing the number of aerial steams when treated with white light than when treated with only blue light thanks to the lower light stress when treated with white light than when treated with only blue light. However, given that there is a tendency for the production of stolons to decrease when the ratio of blue decreases despite that the light stress decreases and the photosynthetic rate increases (Fig. 3 and Table 2), both light stress and blue light are judged to contribute to the production of the stolons of
This seems to be also related to the correlation between blue light and the net photosynthetic rate of
In addition, the ramets of wild strawberry (
The number of leaves of stolons decreased more when treated with white light than when treated with blue light alone. Unlike the leaves of branches, the leaves of stolons of
However, the length of stolons of
Unlike the results from the branches and stolons, the length and number of leaves of the main stem did not show any difference following the adjustment of the ratio of blue light to red light and white light treatment. When
Based on these results, The leaves of the branch of
As a result, when the blue light ratio increased, light stress was induced, resulting in a rise in leaf temperature, and the transpiration rate and net photosynthetic rate decreased due to stomatal closure. In this light condition, more branch and stolon leaves were produced due to light stress. On the contrary, when white light is treated, leaf temperature decreased by reducing light stress and increasing the transpiration rate and net photosynthetic rate. In addition, branch leaves were produced for efficient photosynthesis. Low light stress and high net photosynthetic rate increased the number of stolons used for vegetative propagation.
In this study, the effects of the ecophysiological response of
To put together the above results, in the case of
ICT: Information communication technologies
IoT: the Internet of things
LED: Light-emitting diode
PPFD: Photosynthetic photon flux density
ABA: Abscisic acid
SOD: Superoxide dismutase
CO2: Carbon dioxide
ATP: Adenosine triphosphate
NADPH: Nicotinamide adenine dinucleotide phosphate
YHY conceptualized the research and did experimental design. JHP and JML collected data. JHP analyzed data. JHP prepared first draft of the manuscript. JHP, EJK, JML, and YHY revised and finalized the manuscript.
This research was supported by the National University Development Project by the Ministry of Education in 2020 (Grant No: 2020-0727-01).
The authors declare that they have no competing interests.