Skripsi
MODEL PENDUGAAN CARBON STORAGE PADA TANAMAN KOPI VARIETAS ROBUSTA.
The combination of allometric, Gompertz, and exponential models based on proximate-ultimate analysis serves as a tool to estimate carbon storage capacity in Robusta coffee (Coffea canephora) plants in South Sumatra, Indonesia. This study aims to compare the accuracy of these three models with the SNI 7724:2011 standard and analyze the potential of Robusta coffee as a nature-based solution (NbS) for climate change mitigation. The research was conducted from November 2024 onward at the Biosystems Laboratory, Sriwijaya University, using a Completely Randomized Design (CRD) with four levels of stem diameter (5–25 cm). Data were measured through proximate analysis (ASTM D3178) and ultimate analysis (elemental analyzer), validated using R², RMSE, and MAPE metrics. This tool can predict carbon stocks in real-time based on stem diameter (DBH), with the highest accuracy achieved by the Gompertz model (R² = 0.9888). Analytical results show that the actual carbon content in Robusta coffee biomass is 36.96–38.16% (AR), 15% lower than the SNI 7724:2011 assumption (47%). Robusta coffee agroforestry systems can store 12.76–13.46% fixed carbon (AR) while enhancing ecosystem resilience. Location coordinates of coffee plantations were monitored with an average deviation of 2.9 meters from actual data. Recommendations include integrating the Gompertz model into carbon certification policies, training farmers for DBH monitoring, and expanding research to environmental variables (rainfall, temperature). This tool can be implemented portably in remote areas without internet connectivity, supporting sustainable agriculture and SDG 13 targets.
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