Fractal Branching Model for Non-Destructive Biomass Estimation inTerminalia chebulaandEmblica officinalisAgroforestry Plantations

Abstract

Fractal branching model is a non-destructive tool for biomass estimation. In the present paper we compared estimates of above ground tree biomass of Terminalia chebula and Emblica officinalis using usual method of biomass estimates and by employing Fractal Branching Analysis (FBA) model. Allometric equations were developed through FBA for above ground biomass of Terminalia chebula (B=0.1296D 2.0827 ), branch biomass (B=0.0103D 2.5388 ) and leaves+twig biomass (B=0.0529D 1.3269 ). Similarly, equations were developed for Embilica officinalis for above ground biomass B=0.0655 D 2.4042 ), branch biomass (B=0.0007 D 3.35108 ) and for leaves+twig (B=0.0656 D 1.621 ) (where B is Biomass and D is diameter of tree at breast height). While comparing the biomass estimate of both the methods using different descriptive statistics it was found that biomass equations developed through FBA model can fairly estimate the biomass as Maximum Error (ME) values ranged from 0.1 to 0.385 in Terminalia and from 0.068 to 0.289 in Embilica. The Coefficient of Residual Mass (CRM) values for both the species were also less than and near to one signifying good prediction by the FBA model. The experiment also showed that the method is fairly accurate and estimation for large number of trees, with different diameters, can be generated through the model thus saving precious time and resources.

Residual Agroforestry Biomass Supply Chain Simulation Insights and Directions: A Systematic Literature Review

“…The analysis of complex systems is made possible by simulation methods and models, which give information on how the system would behave in various scenarios. Various companies, notably the bioenergy sector, have made extensive use of simulation tools to optimize their supply chains [23][24][25][26][27]. Simulation is a crucial tool for creating planning and exploratory models in order to maximize decision-making as well as the design and operation of complex and intelligent manufacturing processes [28].…”