This study generated regression models through a direct harvesting method to estimate carbon storage and uptake by Pinus densiflora and Pinus koraiensis, the major evergreen tree species in urban landscape, and established essential information to quantify carbon reduction by urban trees. Open-grown landscape tree individuals for each species were sampled reflecting various diameter sizes at a given interval. The study measured biomass for each part including the roots of sample trees to compute the total carbon storage per tree. Annual carbon uptake per tree was quantified by analyzing radial growth rates of stem samples at breast height. The study then derived a regression model easily applicable in estimating carbon storage and uptake per tree for the two species by using diameter at breast height (DBH) as an independent variable. All the regression models showed high fitness with $r^2$ values of higher than 0.98. While carbon storage and uptake by young trees tended to be greater for P. densiflora than for P. koraiensis in the same diameter sizes, those by mature trees with DBH sizes of larger than 20 cm showed results to the contrary due to a difference in growth rates. A tree of P. densiflora and P. koraiensis with DBH of 25 cm stored 115.6 kg and 130.0 kg of carbon, respectively, and annually sequestered 9.4 kg and 14.6 kg. The study has broken new grounds to overcome limitations of the past studies which quantified carbon reduction of the study species by substituting, due to a difficulty in direct cutting and root digging of landscape trees, coefficients from forest trees such as biomass expansion factors, ratios of below ground/above ground biomass, and diameter growth rates.
Arbuscular mycorrhizal fungi (AMF) are widespread soil endophytic fungi, forming mutualistic relationships with the vast majority of land plants. Biochar (BC) has been reported to improve soil fertility and promote plant growth. However, limited studies are available concerning the combined effects of AMF and BC on soil community structure and plant growth. In this work, a pot experiment was designed to investigate the effects of AMF and BC on the rhizosphere microbial community of Allium fistulosum L. Using Illumina high-throughput sequencing, we showed that inoculation of AMF and BC had a significant impact on soil microbial community composition, diversity, and versatility. Increases were observed in both plant growth (the plant height by 8.6%, shoot fresh weight by 12.1%) and root morphological traits (average diameter by 20.5%). The phylogenetic tree also showed differences in the fungal community composition in A. fistulosum. In addition, Linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed that 16 biomarkers were detected in the control (CK) and AMF treatment, while only 3 were detected in the AMF + BC treatment. Molecular ecological network analysis showed that the AMF + BC treatment group had a more complex network of fungal communities, as evidenced by higher average connectivity. The functional composition spectrum showed significant differences in the functional distribution of soil microbial communities among different fungal genera. The structural equation model (SEM) confirmed that AMF could improve the microbial multifunctionality by regulating the rhizosphere fungal diversity and soil properties. Our findings provide new information on the effects of AMF and biochar on plants and soil microbial communities.
Hyun-Chang Lim;Yeek Herr;Jong-Hyuk Chung;Seung-Yun Shin;Seung-Il Shin;Ji-Youn Hong
Journal of Korean Dental Science
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v.16
no.2
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pp.172-181
/
2023
Purpose: To investigate the effect of epidermal growth factor (EGF) with collagen matrix (CM) for increasing gingival thickness. Materials and Methods: In five mongrel dogs, bilateral gingival defects were surgically made on the maxillary canines. After two months, either a subepithelial connective tissue graft (group SCTG) or CM with EGF (0.1 ug/ml, group EGF) was grafted, and the flap was coronally positioned to cover the graft materials. The animals were sacrificed after three months. Intraoral scanning was performed for soft tissue analysis. Histologic and histomorphometric analyses were performed. Result: Two animals exhibited wound dehiscence during the healing phase, leaving three for analysis. No statistically significant difference was found in soft tissue changes (P>0.05). The level of gingival margin (GM) increased in both groups (1.02±0.74 mm in group SCTG vs. 1.24±0.83 mm in group EGF). Linear increases at the GM pre-augmentation in the soft tissue profile were 1.08±0.58 mm in group SCTG and 0.96±0.73 mm in group EGF. Histomorphometric parameters (keratinized tissue height, tissue thickness, and rete peg density) were not significantly different between the groups (P>0.05). Conclusion: EGF loaded onto CM led to comparable gingival phenotype enhancement to SCTG.
This study was conducted to estimate carbon stocks of Quercus serrata with drawing volume of trees in each tree height and DBH applying the suitable stem taper equation and tree specific carbon emission factors, using collected growth data from all over the country. Information on distribution area, tree number per hectare, tree volume and volume stocks were obtained from the $5^{th}$ National Forest Inventory (2006~2010), and method provided in IPCC GPG was applied to estimate carbon storage and removals. Performance in predicting stem diameter at a specific point along a stem in Quercus serrata by applying Kozak's model,$d=a_1DBH^{a_2}a_3^{DBH}X^{b_1Z^2+b_2ln(Z+0.001)+b_3{\sqrt{Z}}+b_4e^Z+b_5({\frac{DBH}{H}})}$, which is well known equation in stem taper estimation, was evaluated with validations statistics, Fitness Index, Bias and Standard Error of Bias. Consequently, Kozak's model turned out to be suitable in all validations statistics. Stem volume tables of Quercus serrata were derived by applying Kozak's model and carbon stock tables in each tree height and DBH were developed with country-specific carbon emission factors ($WD=0.65t/m^3$, BEF=1.55, R=0.43) of Quercus serrata. As a result of carbon stock analysis by age class in Quercus serrata, carbon stocks of IV age class (11,358 ha, 36.5%) and V age class (10,432; 33.5%) which take up the largest area in distribution of age class were 957,000 tC and 1,312,000 tC. Total carbon stocks of Quercus serrata were 3,191,000 tC which is 3% compared with total percentage of broad-leaved forest and carbon sequestration per hectare(ha) was 3.8 tC/ha/yr, $13.9tCO_2/ha/yr$, respectively.
Dae-Wook Cha;Hui-Yeon Jo;Ji-Soo Han;Kwang-Sup Shin;Yun-Hong Min
The Journal of Bigdata
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v.8
no.2
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pp.149-163
/
2023
Due to the continuous growth of the E-commerce market, the volume of orders that fulfillment centers have to process has increased, and various customer requirements have increased the complexity of order processing. Along with this trend, the operational efficiency of fulfillment centers due to increased labor costs is becoming more important from a corporate management perspective. Using historical performance data as training data, this study focused on real-time box recommendations applicable to packaging areas during fulfillment center shipping. Four types of data, such as product information, order information, packaging information, and delivery information, were applied to the machine learning model through pre-processing and feature-engineering processes. As an input vector, three characteristics were used as product specification information: width, length, and height, the characteristics of the input vector were extracted through a feature engineering process that converts product information from real numbers to an integer system for each section. As a result of comparing the performance of each model, it was confirmed that when the Gradient Boosting model was applied, the prediction was performed with the highest accuracy at 95.2% when the product specification information was converted into integers in 21 sections. This study proposes a machine learning model as a way to reduce the increase in costs and inefficiency of box packaging time caused by incorrect box selection in the fulfillment center, and also proposes a feature engineering method to effectively extract the characteristics of product specification information.
The growth and yield models for five different kinds of natural forest types were systemically developed in the natural Broadleaved-Korean pine Forests in Northeast China. The data were collected from 359 temporary plots and 58 permanent plots with area ranged from 0.06 ha to 1.0 ha, ranging in stand age from 43 to 364 years. The Site Class Index (SCI) was introduced to evaluate site quality and the Crown Competition Factor (CCF) was selected as a measure of stand density for the mixed natural forest. The Chapman-Richards function was adopted to develop SCI equation and height-diameter curve. The Schumacher growth function was selected as base model to develop the DBH, basal area, and stand volume growth models by using re-parameterized method. In modeling mean DBH and basal area growth, it was found that the asymptotic parameter A of Schumacher function was exponentially related to site quality (SCI) and stand density (CCF). The rate parameter k was related to stand density and it was independent of SCI. Several validation measures for predicted stand variables were evaluated in the growth and yield models using independent data sets. The results indicated that relative mean errors (RME) in predicted stand attributes were less than ${\pm}5%$ and the estimated precision values of the stand variables were all greater than 95%.
Based on the movement characteristics of overlying strata with gangue backfilling, the compression test of gangue is designed. The deformation characterristics of gangue is obtained based on the different Talbot index. The deformation has a logarithmic growth trend, including sharp deformation stage, linear deformation stage, rheological stage, and the resistance to deformation changes in different stages. The more advantageous Talbot gradation index is obtained to control the surface subsidence. On the basis of similarity simulation test with gangue backfilling, the characteristics of roof failure and the evolution of the supporting force are analyzed. In the early stage of gangue backfilling, beam structure damage directly occurs at the roof, and the layer is separated from the overlying rock. As the working face advances, the crack arch of the basic roof is generated, and the separation layer is closed. Due to the supporting effect of filling gangue, the stress concentration in gangue backfilling stope is relatively mild. Based on the equivalent mining height model of gangue backfilling stope, the relationship between full ratio and mining height is obtained. It is necessary to ensure that the gradation of filling gangue meets the Talbot distribution of n=0.5, and the full ratio meets the protection grade requirements of surface buildings.
Kim, Junki;Choi, Seung-cheon;Kim, Jaehwi;Seo, Hong-Seok
The Korean Journal of Applied Statistics
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v.33
no.6
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pp.763-776
/
2020
Onions show severe volatility in production and price because crop conditions highly depend on the weather. The government has designated onions as a sensitive agricultural product, and prepared various measures to stabilize the supply and demand. First of all, preemptive and reliable information on predicting onion production is essential to implement appropriate and effective measures. This study aims to contribute to improving the accuracy of production forecasting by developing a model to estimate the final weight of onions bulb. For the analysis, multi-level model is used to reflect the hierarchical data characteristics consisting of above-ground growth data in individual units and meteorological data in parcel units. The result shows that as the number of leaf, stem diameter, and plant height in early May increase, the bulb weight increases. The amount of precipitation as well as the number of days beyond a certain temperature inhibiting carbon assimilation have negative effects on bulb weight, However, the daily range of temperature and more precipitation near the harvest season are statistically significant as positive effects. Also, it is confirmed that the fitness and explanatory power of the model is improved by considering the interaction terms between level-1 and level-2 variables.
In this study, a number of distance-dependent competition indices on tree-level which incorporate the tree sizes and distances to competitors, and traditional stand-level density measures were estimated from the data compiled with position-dependent survey in a Pinus densiflora stand. The performance of the estimated competition indices was examined by comparing the relationship with the diameter growth, and a dbh growth function, in which the competition index is considered as a one of influence factors, are developed. In the searching method of competing trees, the competition index estimated with $30^{\circ}$ competition interrupting angle showed the highest correlation with the annual dbh growth, while the expanding the competing zone distance had no significant effect on the performance of competition index in estimating annual dbh growth. The most of the examined stand-level competition indices, based on distance-dependent single-tree competition indices, were evaluated to describe similarly the stand competition status. As a result of partial correlation analysis in which the effect of age and site index are eliminated, Alemdag's mean competition index and relative spacing index were determined to have the highest correlation with dbh. The relative spacing index, which can be easily measured in field without measuring the position of individual trees, was considered to be a better suited one for estimating mean dbh of a stand. Among distance-dependent competition indices on tree-level, Hegyi's competition index showed the best performance in their correlation with annual dbh growth, if eliminated the effect of site index and dbh. This enabled to derive the following annual dbh growth function of individual trees which incorporate age, dominant height, dbh and Hegyi's competition index as influence factors : $$dbh^{\prime}=3.975362676{\cdot}age^{-1.099274613}{\cdot}ho^{0.199893990}{\cdot}dbh^{0.269430865}{\cdot}HgCI^{-0.353643587}$$ This function is coincided to the growth principle in which site index has a positive effect on the annual dbh growth, while high age or competition causes to reduce the annual dbh growth, and can be used as a function in single tree growth model.
Dae Ho Jung;Su Hwan Oh;Da Mi Kim;Su Oh Lee;Chul Hee Cho;Hye Won Cho;Chul Kyoo Ha;Hyun-Ah Lee
Journal of Bio-Environment Control
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v.32
no.1
/
pp.72-80
/
2023
Melons, a rich source of vitamins and fibers, are commonly grown in the soil. Hydroponic cultivation could improve yield and quality of melon and selection of substrate volume and the kind of substrates is important for hydroponic cultivation of melons. This study investigated the effect on melon growth according to volume of granular rockwool and substrates of coir and rockwool slab. 'Geumsegye' melon (Cucumis melo L. cv. Geumsegye) was cultivated hydroponically according to volume of granular rockwool to 1.0, 1.5, 2.0, 3.0, and 4.0 L, and was also cultivated using coir and rockwool slabs. Logistic model was applied to estimate the growth characteristics of melons such as plant height, leaf length, leaf width, and the characteristics of fruit. The growth characteristics of melons were significantly increased at 4.0 L compared to those grown of 1.0 L volume of on granular rockwool, and the results were the highest in coir and rockwool slabs. Melons grown in rockwool slabs showed the largest fruit fresh weight, fruit length, and fruit width. During hydroponic cultivation, growth characteristics of melon appropriate at the 4.0 L volume of granular rockwool, and the highest at coir and rockwool slabs. This study provides a basis for understanding the effect of root zone environment to the growth characteristics and fruit quality of non-netted melon.
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