• Korean Journal of Environmental Agriculture
• /
• v.39 no.3
• /
• pp.204-213
• /
• 2020

BACKGROUND: Since the number of crops cultivated in reclaimed land is huge, it is very difficult to quantify the total crop production. Therefore, a non-destructive method for predicting crop production is needed. Salt tolerant root vegetables such as red beets and sugar beet are suitable for cultivation in reclaimed land. If their underground biomass can be predicted, it helps to estimate crop productivity. Objectives of this study are to investigate maximum leaf length and weight of red beet, sugar beet, and turnips grown in reclaimed land, and to determine optimal model with regression analysis for linear and allometric growth models. METHODS AND RESULTS: Maximum leaf length, width, and root fresh weight of red beets, sugar beets, and turnips were measured. Ten linear models and six allometric growth models were selected for estimation of root fresh weight and non-linear regression analysis was conducted. The allometric growth model, which have a variable multiplied by square of maximum leaf length and maximum leaf width, showed highest R² values of 0.67, 0.70, and 0.49 for red beets, sugar beets, and turnips, respectively. Validation results of the models for red beets and sugar beets showed the R² values of 0.63 and 0.65, respectively. However, the model for turnips showed the R² value of 0.48. The allometric growth model was suitable for estimating the root fresh weight of red beets and sugar beets, but the accuracy for turnips was relatively low. CONCLUSION: The regression models established in this study may be useful to estimate the total production of root vegetables cultivated in reclaimed land, and it will be used as a non-destructive method for prediction of crop information.

• Journal of Forest and Environmental Science
• /
• v.34 no.2
• /
• pp.108-118
• /
• 2018

Biomass determination of species-specific in forest ecosystem by semi-destructive measures requires the development of allometric equations; predict aboveground biomass observable independent variables such as, Diameter at Breast Height, Height, and Volume are crucial role. There has not been equation of this type in mountain Chuqala natural forest. In this study two species namely, Hypericum revolutum Vahl. & Maesa lanceoleta Forssk. with tree diameter classes (15-20, 20.5-25, and 25.5-35 cm), with the purpose of conducting allometric equations were characterized. Each species assumed considered individually. For the linear model fit the two observed variable DBH, H and V were preferred for the prediction of above ground biomass. The best fitted model choose among the two formed model were identified using Akaike Information Criterion (AIC), and $R^2$ and adjacent $R^2$. Based on this the best fit model for Hypericum revolutum Vahl. was AGB=-681.015+4,494.06 (DBH), and for Maesa lanceoleta Forrsk. was. AGB=-936.96+5,268.92 (DBH).

• Journal of Forest and Environmental Science
• /
• v.30 no.4
• /
• pp.351-361
• /
• 2014

Leaf area ($A_0$) and leaf biomass ($M_0$) estimation are significant prerequisites to studying tree physiological processes and modeling in the forest ecosystem. The objective of this study was to develop allometric models for estimating $A_0$ and $M_0$ of Swietenia mahagoni L. from different tree parameters such as DBH and tree height of mahogany plantations in the northeastern region of Bangladesh. A total of 850 healthy and well formed trees were selected randomly for sampling in the five study sites. Then, twenty two models were developed based on different statistical criteria that propose reliable and accurate models for estimating the $A_0$ and $M_0$ using non-destructive measurements. The results exposed that model iv and xv were selected on a single predictor of DBH and showed more statistically accuracy than other models. The selected models were also validated with an additional test data set on the basis of linear regression and t-test for mean difference between observed and predicted values. After that, a comparison between the best logarithmic and non-linear allometric model shows that the non-linear model produces systematic biases and underestimates $A_0$ and $M_0$ for larger trees. As a result, it showed that the bias-corrected logarithmic model iv and xv can be used to help quantify forest structure and functions, particularly valuable in future research for estimating $A_0$ and $M_0$ of S. mahagoni in this region.

• Biomolecules & Therapeutics
• /
• v.25 no.6
• /
• pp.648-658
• /
• 2017

7-O-Succinyl macrolactin A (SMA) exerts several pharmacological effects including anti-bacterial, anti-inflammation, and anti-cancer activities. Recently, SMA has been extensively evaluated as an anti-cancer drug. Thus, the objectives of the present study were to characterise the pharmacokinetics of SMA via both non-compartmental and compartmental analysis in mice, rats, and dogs, and to derive an appropriate first-in-man dose based on allometric scaling of the animal data. The time courses of plasma SMA concentrations after intravenous administration to rats and dogs were analysed retrospectively, as were data collected after intraperitoneal SMA injection in mice. Pharmacokinetic parameters were estimated via both noncompartmental and compartmental analysis, and were correlated with body weight and/or the potential maximum life-span. The clearance and distribution volume of SMA in humans were predicted, and a first-in-man dose proposed. A two-compartment model best described the time courses of SMA plasma concentrations after a saturation elimination process was applied to fit the dataset obtained from rats. Incorporation of the maximum potential life-span during allometric scaling was required to improve the estimation of human clearance. The SMA clearance and the distribution volume in the steady state, in a 70-kg adult male, were estimated to be 30.6 L/h and 19.5 L, respectively. To meet the area under the curve (AUC) required for anti-tumour activity, a dose of 100 mg (~1.5 mg/kg) was finally proposed as the first dose for a 70-kg human. Although toxicological profiles derived from non-clinical studies must be considered before any final decision is made, our work will facilitate clinical studies on SMA.

• Journal of Korean Society of Forest Science
• /
• v.112 no.2
• /
• pp.127-135
• /
• 2023

This study aimed to develop biomass allometric equations and estimate carbon emission factors, such as the wood density, biomass-expansion factor, and root-to-shoot ratio, for Platanus occidentalis and Metasequoia glyptostroboides planted in urban areas. Twenty M. glyptostroboides and 25 P. occidentalis trees were harvested, and the dry weights and stem volumes of stems, branches, leaves, and roots (>5 mm) were measured. The wood densities of M. glyptostroboides and P. occidentalis were 0.293 ± 0.008 g cm^-3 and 0.509 ± 0.018 g cm^-3, and the biomass-expansion factors were 1.738 ± 0.031 and 1.561 ± 0.035. The root-to-shoot ratios were 0.446 ± 0.009 and 0.402 ± 0.012. The uncertainty tests (coefficient of variation, %) gave 2.8% and 3.5% values for wood density, 1.8% and 2.3% for biomass-expansion factor, and 2.1% and 2.9% for root-to-shoot ratio, respectively. Among the developed allometric equations, Model I using the diameter at breast height (DBH) was suitable. The allometric equations of M. glyptostroboides and P. occidentalis above ground were y = 1.679 (DBH)^1.315 and y = 0.505 (DBH)^1.896, and the allometric equations of the root and total were y = 0.746 (DBH)^1.315, y = 0.301 (DBH)^1.751, y = 2.422 (DBH)^1.316, and y = 0.787 (DBH)^1.858. If the carbon-emission factors of this study and biomass allometric equations of the three developed models are used to estimate the carbon storage and biomass of urban forests, errors caused by not considering the use of fixed factors and the environmental differences can be reduced.

• Journal of Korean Society of Forest Science
• /
• v.110 no.4
• /
• pp.569-576
• /
• 2021

This study developed an estimation model for litterfall input using the stand parameters (basal area, stand density, mean DBH, and carbon stocks of the aboveground tree biomass) collected from the Korean red pine (Pinus densiflora S. et Z.) stands of seven regions in Gyeongsangnam-do. The mean annual litterfall was 2,779 kg ha^-1 year^-1 for needles, 883 kg ha^-1 year^-1 for miscellaneous, 611 kg ha^-1 year^-1 for broadleaved, 513 kg ha^-1 year^-1 for branches, and 340 kg ha^-1 year^-1 for bark litter. The mean annual total litterfall was 5,051 kg ha^-1 year^-1. Litterfall components were significantly correlated with stand parameters, except for broadleaved litter. A stronger correlation was observed between the carbon stock of the aboveground tree biomass and all the litterfall components compared with the other stand variables. The allometric equations for all the litterfall components were significant (P < 0.05), with the stand parameters accounting for 5%-43% and 8%-42% of the variation in the needle litter and total litterfall, respectively. The results indicated that the annual litterfall inputs of the Korean red pine stands on a regional scale can be effectively estimated by allometric equations using the basal area and carbon stocks of the aboveground tree biomass.

• Animal Bioscience
• /
• v.37 no.5
• /
• pp.817-825
• /
• 2024

Objective: The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls. Methods: A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied. Results: Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture. Conclusion: Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance.

• Journal of Korean Society of Forest Science
• /
• v.78 no.3
• /
• pp.323-330
• /
• 1989

Pinass densiflora natural forests of four local forms in Korea were studies to investigate effective biomass estimation method. Dimension analysis was used and three allometric regression models, such as logWt=A+BlogD, logWt=$A+B1ogD^2H$ and 1ogWt=A+BlogD+ClogH were applied to estimate biomass, The most accurate estimation was made by the regression model of logWt=A+BlogD+ClogH where Wt is dry weight, D is diameter at breast height, and H is tree height. However, dry weights of cones and dead branches were remotely related to tree size factor, such as D and H. In the interest of practical use. generalized allometric regressions for all samples trees of four stands were computed and analysis of covariance was used to compare the allometric regressions among the four stands. Based on the test criteria applied in this study, significant differences were found in terms of error variance and regression intercept, not in terms of regression slope. These trends suggest a generalized biomass regression is not valid for accurate estimation over a range of four local form stands.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.52 no.6
• /
• pp.719-724
• /
• 2019

This study is an extension of our previous model for a size-based fish stock assessment. In the previous model, we applied an allometric length-weight relationship (W=α·L^β) to convert lengths of fish to weights, and estimated those parameters α and β, using data about lengths and weights aggregated over years. In this study, we focused on whether consideration of temporal (e.g., year-to-year) variability in those estimates (i.e., ${\hat{\alpha}}$ and ${\hat{\beta}}$) would contributive. After calculating year-specific estimates (i.e., year-specific pairs of ${\hat{\alpha}}$ and ${\hat{\beta}}$) by applying data about lengths and weights separated by year, we evaluated the contribution of those year-specific pairs of ${\hat{\alpha}}$ and ${\hat{\beta}}$ to the performance of the size-based stock assessment model. The model with such year-to-year variability being considered (lower AIC) outperformed that with the variability being ignored (higher AIC). We illustrated this study using data on Korean chub mackerel Scomber japonicus from 2005-2017.

• Journal of Korean Society of Forest Science
• /
• v.99 no.5
• /
• pp.673-681
• /
• 2010

This study examined the biomass data estimated from different allometric models and calculated the mean aboveground biomass, mean belowground biomass and root/shoot ratio values according to the forest types and age classes. These mean values and the forest inventories in 2009 were used to estimate the aboveground and total biomass carbon storage in different forest types (coniferous, deciduous and mixed forests). The aboveground and total biomass carbon storage for all forest types in Korea were 350.201 Tg C and 436.724 Tg C. Over the past 36 years, plantations by reforestation programs have accounted for more than 70% of the observed carbon storage. The carbon storage in Korean forest biomass was 436.724 Tg C, of which 175.154 Tg C for coniferous forests, 126.772 Tg C for deciduous forests and 134.518 Tg C for mixed forests, comprising approximately 1/20 of the total carbon storage of the East Asian countries. The total carbon storage for the whole forest sector in Korea was 1213.122 Tg C, of which 436.724 Tg C is stored in forest biomass if using the ratio of carbon storage in different pools examined from the United States. Such large carbon storage in Korean forests is due mainly to active plantations growth and management practices.