Claim · model-written summary
Biomass models could apply to other areas with similar conditions but should be validated before use in new sites.
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionValueQualifier
Verbatim
e0“Biomass regression models are presented describing total above-ground biomass, stem wood, branch wood, foliage and bark production for Tejpat (Cinnamomum tamala), a multipurpose tree”
e7“Biomass models developed could be applied to obtain biomass of different tree components of Tejpat grown in the study area and could even be applied to other areas which have similar conditions; but it should be validated before using them in new sites and conditions”
Title
BS Poudel; SK Gautam; DN Bhandari Banko Janakari 2013. doi:10.3126/banko.v21i1.9058
Other claims from this paper (8)
- Method / resource Regression models for Tejpat biomass were statistically significant, with R2 from 0.64 to 0.83.
- Method / resource The linear model had the least error among the five regression models tested for Tejpat biomass.
- Method / resource RMSE percentage of the best-fit equation for Tejpat biomass varied between 16.64% and 44.82%.
- Observation Stem held 47.24% tree-1 of biomass allocation, more than foliage.
- Observation Foliage held 22.75% tree-1 of biomass allocation.
- Observation Branch held 19.69% tree-1 of biomass allocation.
- Observation Bark held 10.31% tree-1 of biomass allocation.
- Association Tejpat biomass has a positive, strongly linear relationship with DBH.