• 한국환경농학회지
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• 제39권3호
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• pp.204-213
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• 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
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• 제34권2호
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• pp.108-118
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• 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
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• 제30권4호
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• pp.351-361
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• 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
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• 제25권6호
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• pp.648-658
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• 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.

• 한국산림과학회지
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• 제112권2호
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• pp.127-135
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• 2023

본 연구는 도시림 주요 식재 수종인 양버즘나무와 메타세쿼이아 2개 수종을 대상으로 탄소 배출 계수를 산정하고, 수목 부위별 바이오매스 상대생장식을 개발하였다. 메타세쿼이아 20본, 양버즘나무 25본을 벌채하여 주간, 가지, 잎, 뿌리 (>5 mm)의 건중량과 줄기 재적을 산출하였다. 메타세쿼이아와 양버즘나무의 목재 기본 밀도 0.293±0.008 g cm^-3, 0.509± 0.018 g cm^-3이었으며, 바이오매스 확장계수는 1.738±0.031, 1.561±0.035였다. 마지막으로 뿌리 대 지상부 비율은 0.446± 0.009, 0.402±0.012이었다. 각각의 불확도 검사(CV, %)를 진행하여 목재 기본 밀도 2.8%, 3.5%, 바이오매스 확장계수 1.8%, 2.3%, 뿌리 대 지상부 비율 2.1%, 2.9%로 계산되었다. 개발된 상대생장식은 흉고직경을 활용한 Model I이 적합하였다. 이에, 메타세쿼이아와 양버즘나무의 지상부는 Y=1.679(DBH)^1.315, Y=0.505(DBH)^1.896, 뿌리 Y=0.746(DBH)^1.315, Y=0.301(DBH)^1.751이었으며, 전체는 Y=2.422(DBH)^1.316, Y=0.787(DBH)^1.858이었다. 산정된 탄소 배출 계수와 개발된 세 개 모델의 상대생장식을 활용하여 정주지 수목의 탄소저장량과 바이오매스를 산정한다면, 고정계수의 사용과 환경적 차이에 따라 발생하는 오차를 줄일 수 있을 것이다.

• 한국산림과학회지
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• 제110권4호
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• pp.569-576
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• 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
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• 제37권5호
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• pp.817-825
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• 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 Ecology and Environment
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• 제48권2호
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• pp.196-206
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• 2024

Background: Most of the biomass equations were developed using sample trees collected mainly from pan-tropical and tropical regions that may over- or underestimate biomass. Site-specific models would improve the accuracy of the biomass estimates and enhance the country's measurement, reporting, and verification activities. The aim of the study is to develop site-specific biomass estimation models and validate and evaluate the existing generic models developed for pan-tropical forest and newly developed allometric models. Total of 140 trees was harvested from each diameter class biomass model development. Data was analyzed using SAS procedures. All relevant statistical tests (normality, multicollinearity, and heteroscedasticity) were performed. Data was transformed to logarithmic functions and multiple linear regression techniques were used to develop model to estimate aboveground biomass (AGB). The root mean square error (RMSE) was used for measuring model bias, precision, and accuracy. The coefficient of determination (R² and adjusted [adj]-R²), the Akaike Information Criterion (AIC) and the Schwarz Bayesian information Criterion was employed to select most appropriate models. Results: For the general total AGB models, adj-R² ranged from 0.71 to 0.85, and model 9 with diameter at stump height at 10 cm (DSH₁₀), ρ and crown width (CW) as predictor variables, performed best according to RMSE and AIC. For the merchantable stem models, adj-R² varied from 0.73 to 0.82, and model 8) with combination of ρ, diameter at breast height and height (H), CW and DSH₁₀ as predictor variables, was best in terms of RMSE and AIC. The results showed that a best-fit model for above-ground biomass of tree components was developed. AGB_Stem = exp {-1.8296 + 0.4814 natural logarithm (Ln) (ρD²H) + 0.1751 Ln (CW) + 0.4059 Ln (DSH₃₀)} AGB_Branch = exp {-131.6 + 15.0013 Ln (ρD²H) + 13.176 Ln (CW) + 21.8506 Ln (DSH₃₀)} AGB_Foliage = exp {-0.9496 + 0.5282 Ln (DSH₃₀) + 2.3492 Ln (ρ) + 0.4286 Ln (CW)} AGB_Total = exp {-1.8245 + 1.4358 Ln (DSH₃₀) + 1.9921 Ln (ρ) + 0.6154 Ln (CW)} Conclusions: The results demonstrated that the development of local models derived from an appropriate sample of representative species can greatly improve the estimation of total AGB.

• 한국산림과학회지
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• 제78권3호
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• pp.323-330
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• 1989

한국산(韓國産) 소나무천연림(天然林)의 효과적인 현존량(現存量) 추정식(推定式)을 파악하기 위하여 4개(個) 지역형별(地域型別) 전형적인 수형을 가지는 임분(林分)을 대상으로 임분별(林分別) 10주(株)씩 총 40주(株)의 표본목(標本木)을 선정(選定) 벌목(伐木)하여 임분별(林分別), 부위별(部位別) 현존량(現存量) 추정식(推定式)을 3개(個) 상대성장식(相對成長式)(logWt=A+BlogD, logWt=A+B $1ogD^2H$, logWt=A+BlogD+ClogH)에 의하여 유도한 결과 전반적으로 logWt=A+BlogD-ClogH 식의 적합도(適合度)가 높았다. 그러나 고사지(故死枝)와 모구(毬果)의 경우 흉고직경(胸高直徑)과 수고(樹高) 즉, 개체목(個體木)의 크기 인자와의 관계(關係)가 적은 것으로 나타났다. 실용성(實用性)을 고려하여 4개(個) 임분(林分) 전체의 표본목(標本木) 40주(株)에 대한 일괄상대성장식(一括相對成長式)을 유도하고 임분별(林分別) 회귀식간(回歸式間)의 분산(分散), 기울기, 절편(截片)의 차이 유무를 검정한 결과 흉고직경(胸高直徑)만을 독립변수(獨立變數)로 하는 경우 보다 흉고직경(胸高直徑)과 수고(樹高)를 독립변수(獨立變數)로 할 경우 지성형간(地城型間)의 차이를 어느정도 배제할 수 있었으나, 임분별(林分別) 회귀식간(回歸式間)의 분산(分散) 절편(截片)에서 유기적(有機的)인 차이를 보임으로써 4개(個) 임분(林分)에 대한 일괄상대성장식(一括相對成長式)의 작용은 적합하지 않은 것으로 나타났다.

• 한국수산과학회지
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• 제52권6호
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• pp.719-724
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• 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.