Emmanuel Donkor, Stephen Adu-Bredu, Edward Matthew Osei Jnr, Samuel A. Andam-Akorful, Yakubu Mohammed
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Destructive sampling was carried out on 110 cocoa trees obtained from the cocoa rehabilitation exercise for the development of the allometric models. Diameter at breast height (D), total tree height (H) and wood density (ρ) were used as predictors to develop seven models. The best model was selected based on coefficient of determination (R2), index of agreement (IA), root mean squared error (RMSE), bias (E%), mean absolute error (MAE) and corrected akaike information criterion (AICC) and percentage relative standard error (PRSE) of the estimated parameters. The selected model, which was the one with the predictors D and ρ, was given as; AGB = 0.7217ρ(D2)0.921. It was compared with the Yuliasmara et al. (2009) cocoa model using equivalence test and paired sample t-test. The two models were found to be equivalent within ±10% of their mean predictions (p < 0.0001) for one-tailed tests for both lower and upper limits, while the paired sample t-test rejected the null hypothesis with mean difference of 14.16 kg between the two models. 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Diameter at breast height (D), total tree height (H) and wood density (ρ) were used as predictors to develop seven models. The best model was selected based on coefficient of determination (R2), index of agreement (IA), root mean squared error (RMSE), bias (E%), mean absolute error (MAE) and corrected akaike information criterion (AICC) and percentage relative standard error (PRSE) of the estimated parameters. The selected model, which was the one with the predictors D and ρ, was given as; AGB = 0.7217ρ(D2)0.921. It was compared with the Yuliasmara et al. (2009) cocoa model using equivalence test and paired sample t-test. The two models were found to be equivalent within ±10% of their mean predictions (p < 0.0001) for one-tailed tests for both lower and upper limits, while the paired sample t-test rejected the null hypothesis with mean difference of 14.16 kg between the two models. 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引用次数: 0
摘要
可可系统在减缓和适应气候变化方面的作用已经大大增强,因为它们能够从大气中捕获二氧化碳,并以碳的形式沉积在可可树中。开发可可种植园的地上生物量(AGB)模型对于准确估算可可系统中的碳储量至关重要,然而,用于估算可可种植园的地上生物量(AGB)的异速生长模型仍然是撒哈拉以南非洲可可生产国(特别是加纳)面临的一个挑战。本研究的目的是开发可用于估计加纳以及西非可可种植园AGB的异速生长模型。为了建立异速生长模型,对110棵可可树进行了破坏性采样。以胸径(D)、总树高(H)和木材密度(ρ)作为预测因子,建立了7个模型。根据估计参数的决定系数(R2)、一致性指数(IA)、均方根误差(RMSE)、偏倚(E%)、平均绝对误差(MAE)、修正后的赤池信息准则(AICC)和相对标准误差百分比(PRSE)选择最佳模型。所选择的模型,即具有预测因子D和ρ的模型,给出如下;Agb = 0.7217ρ(d2)0.921。采用等价检验和配对样本t检验与Yuliasmara et al.(2009)可可模型进行比较。在单侧检验中,两个模型的下限和上限在平均预测值的±10%以内是相等的(p < 0.0001),而配对样本t检验拒绝了原假设,两个模型之间的平均差为14.16 kg。这项研究具有重要意义,因为它提供了一个模型来估计加纳可可种植园的AGB,这对加纳可可森林REDD+计划非常重要,也可以被其他西非可可生产国使用。
Biomass Estimation Models for Cocoa (<i>Theobroma cacao</i>) Plantations in Ghana, West Africa
The role of cocoa systems for climate change mitigation and adaptation has increased substantially because of their capability to trap carbon dioxide from the atmosphere and deposited in the cocoa trees as carbon. Development of aboveground biomass (AGB) models for cocoa plantations is crucial for accurate estimation of carbon stocks in the cocoa systems, however, allometric models for estimating AGB for cocoa plantations remain a challenge for cocoa producing countries in Sub-Saharan Africa especially Ghana. The aim of this study is to develop allometric model that can be used for the estimation of AGB for cocoa plantations in Ghana, as well as West Africa. Destructive sampling was carried out on 110 cocoa trees obtained from the cocoa rehabilitation exercise for the development of the allometric models. Diameter at breast height (D), total tree height (H) and wood density (ρ) were used as predictors to develop seven models. The best model was selected based on coefficient of determination (R2), index of agreement (IA), root mean squared error (RMSE), bias (E%), mean absolute error (MAE) and corrected akaike information criterion (AICC) and percentage relative standard error (PRSE) of the estimated parameters. The selected model, which was the one with the predictors D and ρ, was given as; AGB = 0.7217ρ(D2)0.921. It was compared with the Yuliasmara et al. (2009) cocoa model using equivalence test and paired sample t-test. The two models were found to be equivalent within ±10% of their mean predictions (p < 0.0001) for one-tailed tests for both lower and upper limits, while the paired sample t-test rejected the null hypothesis with mean difference of 14.16 kg between the two models. This study is significant because it has provided a model to estimate AGB for the cocoa plantations in Ghana which is very important for the Ghana Cocoa-Forest REDD+ Programme and also can be used by other West African cocoa producing countries.