Broad-leaved evergreen trees create urban forests for mitigation of climate warming and adsorption of particulate matter (PM). This study was performed to identify the species suitable for urban greening by examining the adsorption capacity of the evergreen species in urban areas in Korea, the adsorption points and the elemental composition of PM in the adsorbed tree. Leaf sampling was carried out four times (period of seven months from October 2017 to May 2018) and used after drying (period 28 to 37 days). Particulate matter (PM) was classified and measured according to size PM_2.5 (0.2–2.5 μm), PM₁₀ (2.5–10 μm), PM₁₀₀ (10–100 μm). The total amount of PM adsorbed on the leaf surface was highest in Pinus densiflora (24.6 μg∙cm⁻²), followed by Quercus salicina (47.4 μg∙cm⁻²). The composition of PM adsorbed by P. densiflora is 4.0% PM_2.5, 39.5% PM₁₀ and 56.5% PM₁₀₀, while those adsorbed by Q. salicina are evergreen at 25.7% PM_2.5, 27.4% PM₁₀ and 46.9% PM_100. When the amount of PM adsorbed on the leaf was calculated by LAI, the species that adsorbed PM the most was P. densiflora, followed by Q. salicina, followed by Q. salicina in the wax layer, then P. densiflora. As a result of this study, the amount of PM adsorbed per unit area of leaves, and the amount of PM calculated by LAI, showed a simpler pattern. The hardwoods had a high adsorption rate of PM_2.5. The adsorption ratio of ultra-fine PM_2.5 by evergreen broad-leaved trees was greater than that of coniferous trees. Therefore, broad-leaved evergreens such as Q. salicina are considered very suitable as species for adsorbing PM in the city. PM_2.5 has been shown to be adsorbed through the pores and leaves of trees, indicating that the plant plays an important role in alleviating PM in the atmosphere. As a result of analyzing the elemental components of PM accumulated on leaf leaves by scanning electron microscopy (SEM)/ energy dispersive x-ray spectroscopy (EDXS) analysis, it was composed of O, C, Si, and N, and was found to be mainly generated by human activities around the road. The results of this study provide basic data regarding the selection of evergreen species that can effectively remove aerial PM. It also highlights the importance of evergreen plants for managing PM pollution during the winter and provides insights into planning additional green infrastructure to improve urban air quality.

This study compared carbon (C) and nitrogen (N) distribution at a stand level in an exotic Japanese cedar (Cryptomeria japonica D. Don) plantation and a natural Serrata oak (Quercus serrata Murray) stand growing under similar site conditions in South Korea. The aboveground biomass (stems, branches, and leaves) of 20 trees (10 of each species), the forest floor, and the mineral soils to a depth of 30 cm were sampled to determine C and N concentrations. Except in branches, C concentrations were significantly higher (p < 0.05) in the Japanese cedar plantation than in the Serrata oak stand, whereas N concentrations, except in the stem bark, were significantly lower in the Japanese cedar plantation. Reforestation with an exotic coniferous species significantly increased the C stocks in the aboveground biomass and the N stocks in the forest floor and mineral soils compared with a natural oak stand. The N stocks in the aboveground biomass were dependent on either the N concentrations or the C stocks in the tree components, whereas soil C and N stocks were negatively related to soil fertility parameters such as C/N ratio. Although it is uncertain which factors are responsible for the difference in aboveground C and soil N stocks following the establishment of Japanese cedar plantations on former natural Serrata oak stands, tree replacement may have an impact on C and N allocation within different forest compartments.

Background and objective: Expanding the use of lawns is necessary for environmental improvement and climate change mitigation. This study analyzed public perceptions of expanding lawn uses with different generations.Methods: We divided the respondents into Generation Z, Generation Y (Millennials), Generation X (Xers), and Baby Boomers, and analyzed the experiences and preferences of lawn uses, and the perception of the need for lawn planting or installation (hereinafter referred to as "lawn P/I") in major locations and expanding lawn uses. A survey was conducted online from May to June 2024 nationwide. The survey had a total of 1,012 respondents, including 189 from Generation Z, 288 from Generation Y, 309 from Generation X, and 226 from the Baby Boomers. The collected data were statistically analyzed using chi-square test, multiple regression analysis, etc.Results: For the frequency of places where lawns were experienced and the amount of time spent on lawns, statistically significant differences were found among generations. Preferred activities on lawns did not differ. There was no difference between generations in the perception of the need for lawn P/I in places such as parks, idle land, and reserved land, but there was a difference between generations in places such as school playgrounds, artificial grounds, and pet parks. Generation Z had a statistically significantly lower perception of the need to expand the use of lawns for eco-friendly living environment management. Compared to Baby Boomers, Generation Z also had a statistically significantly lower perception of the need for policies to expand green spaces with lawns, and the need for national institute-led research. There was no statistically significant difference between generations in the perception of the need for policies to revitalize the lawn industry, but Generation Z's interest in or expectations for jobs related to the lawn industry seemed to be low.Conclusion: Lawn use experiences and preferences, as well as perceptions of the need for lawns, need to be considered by generations. Generations Z and Y have limited experience with lawns and perceive the need for lawn P/I as low, with Generation Z showing a significant difference in particular. Baby Boomers have a positive attitude toward lawns as a part of nature. Generation X and Baby Boomers have a high level of perception of the need for policies and research to expand lawn use, and showed a positive attitude toward lawn industrialization and job creation. The public relations of policies and research to expand lawn use toward Generations Z and Y will be necessary.

This study conducted a comparative analysis on the effects of smart automatic and semi-automatic irrigation methods on the physiological characteristics and growth of Prunus × yedoensis Matsum. seedlings. The smart automatic irrigation system, which activates irrigation when the soil moisture drops below 15%, demonstrated superior characteristics in sap-wood area and bark ratio, as well as excellent water management efficiency, compared to the semi-automatic irrigation method, which involves watering (2.0 L) for 10 min at 60 min intervals starting at 8 AM every day. The analysis of soil moisture content changes under varying weather conditions and irrigation methods showed that smart automatic irrigation effectively maintained optimal moisture levels. Moreover, sap flow in the smart automatic irrigation treatment was more efficiently regulated in response to seasonal variations, showing a strong correlation with climatic factors such as temperature and solar radiation. In contrast, the semi-automatic irrigation treatment led to excessive sap flow during the summer due to a fixed watering schedule, resulting in unnecessary water supply. Analysis of photosynthesis parameters and chlorophyll fluorescence also revealed that smart automatic irrigation achieved higher values in light compensation and saturation points, maximizing photosynthetic efficiency. These findings suggest that the smart automatic irrigation system can enhance plant growth and water use efficiency, contributing to sustainable water management strategies. This research provides critical foundational data for developing efficient agricultural and horticultural irrigation management strategies in response to future climate change.

Efficient phenotyping is essential for accelerating genetic improvement in turfgrass breeding, where manual measurements are labor-intensive. This study evaluated hyperspectral imaging (HSI) as a high-throughput tool for assessing Zoysia spp. breeding populations consisting of 464 genotypes. HSI data (400–1000 nm) were processed through a user-in-the-loop hybrid segmentation pipeline integrating UMAP dimensionality reduction, DBSCAN clustering, Random Forest classification, and pseudo-RGB refinement. To independently assess vegetation classification performance, 10,000 manually annotated reference points from 50 pseudo-RGB images were compared with the automated module, yielding an overall accuracy of 0.9697, a precision of 0.8830, a recall of 0.9240, a specificity of 0.9779, an F1-score of 0.9030, and Cohen’s kappa of 0.8851. A Combined Ranking Score (CRS) integrating five vegetation indices and vegetation pixel count was significantly associated with aerial shoot count (r = −0.445, p < 0.001) and runner count (r = −0.207, p < 0.001). The highest-ranked genotype showed a 9370.3-pixel increase in vegetation area between 6 and 16 weeks after transplanting, compared with 1417.7 pixels for the lowest-ranked genotype. Classification performance declined under high-coverage conditions, indicating increased mixed-pixel ambiguity in dense canopies. These results suggest that HSI-based CRS can support rapid, objective, and non-destructive relative ranking of density-related vegetative growth in turfgrass breeding. Because the study was conducted at a single location and season and correlations with manual traits were moderate, the framework is best interpreted as a screening and ranking tool rather than a direct predictive model.

The RGB (red, green, and blue) imagery analysis is an important remote sensing tool, which estimates the effect of environmental stress on turfgrass growth and physiology. Therefore, this study investigated the effect of continuous wear stress treatment on Zoysia japonica through RGB imagery analysis. The results of the growth measurement showed that the plant height substantially decreased, after nine hours of treatment with no considerable difference thereafter. Dry weight measurement showed a substantial difference in the morphological growth characteristics of the aerial part of the turfgrass, but none in the stolon and root zone. This could be attributed to the short period of compaction treatment. The ROS (reactive oxygen species) analysis showed that ROS rapidly increased due to wear stress treatment. The MDA content increased during the traffic process, whereas the green pixels increased and decreased repeatedly; however, overall, the trend declined but the overall trend decreased. Thus, this study confirmed that MDA was effective in reflecting the wear stress of turfgrass; however, it could through RGB image analysis.