Abstract
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 which is found abundantly distributed and grown in western hill districts of Nepal. A total of 56 Tejpat trees between 6.2 and 16.5 cm diameter at breast height (DBH) from farmers’ farmland and marginal land in Arghakhanchi, Gulmi and Palpa districts were sampled and harvested. Mean fresh weight of total above-ground biomass, stem wood, branch wood, foliage and bark was 77.03, 36.39, 15.16, 17.53 and 8.2 kg tree -1, respectively. Allocation of biomass was more in stem (47.24% tree-1) than in foliage (22.75% tree-1), branch (19.69% tree-1) and bark (10.31% tree-1). Weight of tree component was estimated as a function of DBH. After removal of the outliers, data were randomly divided into two datasets: 70% for model calibration and another 30% for model validation. Correlation analysis showed positive stronger linear relationship between DBH and biomass. Five regression models (linear, logarithmic, quadratic, power and exponential) were developed. All models were statistically significant, with R2 ranging from 0.64 to 0.83. Model validation was based on root mean square error (RMSE). RMSE percentage for the best-fit equation varied between 16.64% and 44.82%. Linear model resulted in the least error and was selected as the best-fit model for prediction of biomass of bark, foliage, branch, stem and total above ground tree biomass. 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. DOI: http://dx.doi.org/10.3126/banko.v21i1.9058 Banko Janakari, Vol. 21, No. 1 2011; 3-12
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Claims 9
Claim · model-written summary
Regression models for Tejpat biomass were statistically significant, with R2 from 0.64 to 0.83.
- Taxon
- Cinnamomum tamala
Cinnamomum tamalae0 - Outcome
- R2e1
- Value
- 0.64 to 0.83e1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
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”
e1“All models were statistically significant, with R2 ranging from 0.64 to 0.83”
Claim · model-written summary
The linear model had the least error among the five regression models tested for Tejpat biomass.
- Taxon
- Cinnamomum tamalaCinnamomum tamalae0
- Outcome
- least errore3
- Comparator
- logarithmic, quadratic, power and exponentiale2
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
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”
e2“Five regression models (linear, logarithmic, quadratic, power and exponential) were developed”
e3“Linear model resulted in the least error and was selected as the best-fit model for prediction of biomass of bark, foliage, branch, stem and total above ground tree biomass”
Claim · model-written summary
RMSE percentage of the best-fit equation for Tejpat biomass varied between 16.64% and 44.82%.
- Taxon
- Cinnamomum tamalaCinnamomum tamalae0
- Outcome
- RMSE percentagee4
- Value
- 16.64% and 44.82%e4
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
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”
e4“RMSE percentage for the best-fit equation varied between 16.64% and 44.82%”
Claim · model-written summary
Stem held 47.24% tree-1 of biomass allocation, more than foliage.
- Taxon
- Cinnamomum tamalaCinnamomum tamalae0
- Organ / stage
- steme5
- Outcome
- Allocation of biomasse5
- Direction
- moree5
- Value
- 47.24% tree-1e5
- Comparator
- foliagee5
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
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”
e5“Allocation of biomass was more in stem (47.24% tree-1) than in foliage (22.75% tree-1), branch (19.69% tree-1) and bark (10.31% tree-1)”
Claim · model-written summary
Foliage held 22.75% tree-1 of biomass allocation.
- Taxon
- Cinnamomum tamalaCinnamomum tamalae0
- Organ / stage
- foliagee5
- Outcome
- Allocation of biomasse5
- Value
- 22.75% tree-1e5
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
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”
e5“Allocation of biomass was more in stem (47.24% tree-1) than in foliage (22.75% tree-1), branch (19.69% tree-1) and bark (10.31% tree-1)”
Claim · model-written summary
Branch held 19.69% tree-1 of biomass allocation.
- Taxon
- Cinnamomum tamalaCinnamomum tamalae0
- Organ / stage
- branche5
- Outcome
- Allocation of biomasse5
- Value
- 19.69% tree-1e5
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
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”
e5“Allocation of biomass was more in stem (47.24% tree-1) than in foliage (22.75% tree-1), branch (19.69% tree-1) and bark (10.31% tree-1)”
Claim · model-written summary
Bark held 10.31% tree-1 of biomass allocation.
- Taxon
- Cinnamomum tamalaCinnamomum tamalae0
- Organ / stage
- barke5
- Outcome
- Allocation of biomasse5
- Value
- 10.31% tree-1e5
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
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”
e5“Allocation of biomass was more in stem (47.24% tree-1) than in foliage (22.75% tree-1), branch (19.69% tree-1) and bark (10.31% tree-1)”
Claim · model-written summary
Tejpat biomass has a positive, strongly linear relationship with DBH.
- Taxon
- Cinnamomum tamalaCinnamomum tamalae0
- Treatment
- DBHe6
- Outcome
- linear relationshipe6
- Direction
- positivee6
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
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”
e6“Correlation analysis showed positive stronger linear relationship between DBH and biomass”
Claim · model-written summary
Biomass models could apply to other areas with similar conditions but should be validated before use in new sites.
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”