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Biomass and Bioenergy Article in Biomass and Bioenergy · December 2015 DOI: 10.1016/j.biombioe.2015.08.017





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Biomass and Bioenergy 83 (2015) 42e49

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Research paper

Allometric equations for estimating above- and belowground biomass in Tea (Camellia sinensis (L.) O. Kuntze) agroforestry system of Barak Valley, Assam, northeast India Rinku Moni Kalita, Ashesh Kumar Das*, Arun Jyoti Nath Department of Ecology and Environmental Science, Assam University, Silchar 788011, Assam, India

a r t i c l e i n f o

a b s t r a c t

Article history: Received 15 August 2014 Received in revised form 8 August 2015 Accepted 18 August 2015 Available online xxx

Tea (Camellia sinensis (L.) O. Kuntze) agroforestry has widespread implications for the earnings and food security for a large fraction of population in NorthEast India. It also has immense potentiality to act as a considerable reservoir of biomass carbon providing climate change mitigation options. In the present study an attempt was made to develop allometric equations for above- and belowground biomass estimation specific to Tea [C. sinensis (L.) O. Kuntze] in Barak Valley of northeast India. Relationships were developed through destructive sampling and regressing diameter alone and along height, wood density, crown area, branch count with biomass. Allometric power function equation and linear equivalents have been developed. Diameter singly could predict significantly aboveground biomass (AGB) root biomass (BGB) and total Tea biomass (TB) with over 95% accuracy. Whereas incorporation of height, crown area, wood density, branch count with diameter influenced the model in terms of modified coefficient of determination and minimized estimation errors. Branches, stem and leaves accounted 50, 21 and 6% of AGB respectively. Root biomass (BGB) contributed 23% of the total Tea bush biomass. The samples exhibited overall BGB/AGB ratio of 0.30 ± 0.08 and biomass expansion factor (BEF) by 4.23 ± 1.6. Biomass of different components significantly differs in varied diameter sizes. © 2015 Elsevier Ltd. All rights reserved.

Keywords: Allometric equation Biomass Tea agroforestry NorthEast India

1. Introduction Tea agroforestry have the ability to couple economic gains with environmental benefits. Tea (Camellia sinensis (L.) O. Kuntze) is a perennial evergreen tree intensively managed as shrub for continuous growth of young shoots. Tea is one of the most popular beverages in the world. It is consumed as a beverage throughout the world and grown widely in countries of Asia, Africa and the Near East. Owing to its increasing demand, Tea is considered to be one of the major components of world beverage market. Tea cultivation is confined only to certain specific regions of the world due to its specific requirements of climate and soil. Tea is indigenous to India and production of Tea is an area where the country can be proud of. This is mainly because of its pre-eminence as a foreign exchange earner and its contribution to the country's Gross National Product (GNP). In all aspects of Tea production, consumption and export, India has emerged to be the world leader,

* Corresponding author. E-mail address: [email protected] (A.K. Das). 0961-9534/© 2015 Elsevier Ltd. All rights reserved.

mainly because it accounts for 25% of global production. It is perhaps the only industry where India has retained its leadership over the last 150 years. Tea plantations in India are concentrated in Assam, West Bengal, and Himachal Pradesh, regions of Kerala, Karnataka and Tamil Nadu. Tea plantations in India occupy a large area of agricultural land measuring over 5640 km2 and accounting over 1.209 Tg of annual Tea production [1]. Over one million workers are employed by the Tea industry. Assam with 54% of area accounts for 52% of total Tea production. The state of Assam is known worldwide for the dominant role it has played in the field of Tea production. It has suitable agro climatic conditions necessary for Tea plantations and as such the contribution of Tea towards state domestic product is very high in this state. Assam is the largest Tea producing state in India. The best quality Tea in India pours chiefly from Assam. Assam has over 800 Tea plantations that are of medium to large size. There are also over 200,000 small-scale cooperative and individual Tea farms. On an average, Assam produces over 0.63 Tg of Tea per year, making it the largest Tea growing region in the world [1]. No studies assessing carbon and nutrients allocation and stocks in Tea plantations have been carried out in the region, yet these stocks could be an

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Table 1 Descriptive statistics for variables analyzed for biomass estimation in Tea. Variables/Statistics





CV (%)

Number of observations

Diameter (cm) Height (m) Crown area (m2) Wood density (g cm3) Branch count BEF R/S

10.90 0.95 0.54 0.55 3.84 4.23 0.30

1.69 0.67 0.03 0.41 2 2.17 0.20

22.27 1.06 1.11 0.75 6 8.76 0.54

5.70 0.09 0.28 0.07 1.11 1.56 0.08

52.27 9.61 50.76 13.08 28.92 36.76 25.13

31 31 31 31 31 31 31

BEF e Biomass Expansion Factor, R/S- Root-to-shoot ratio.

important carbon and nutrient source for maintaining crop productivity under variable weather conditions. The vulnerability of the Tea industry in Sri Lanka to global warming and climate change has been reported [2]. It is postulated that aging of Tea plantations can enhance adaptation of bushes to abiotic stress conditions. Quantifying budgets for carbon stocks will assist to explore the response of Tea plantations to such abiotic stresses, and offer new insights for management interventions. Carbon stock potential of Tea plantations in Sri Lanka and China have been reported [3,4]. More information is needed on carbon storage by Tea agroforestry, which would fill the gap in the comparison with native forest vegetation and changes in agricultural land use. Allometric equations for biomass estimation are developed from a sample of trees and generalized for wider applications. Allometric equations published so far includes landuse systems such as Tea [5], coffee [6,7], shrub species [8,9] forest plantations [10,11] and various forest types [12] among other vegetation types. Existing allometric equations for Tea is based on the age of the individuals rather than more simplified dendrometric parameters. Diameter at breast height is commonly used for aboveground biomass (AGB) estimation because it can easily be measured with high accuracy, repetitively and generally follows commonly acknowledged forestry conventions [13]. Even so, the relationship between biomass and tree dimensions differs among species and may also be affected by site characteristics and climatic conditions [14]. Management practices like cutting and pruning can change biomass without changing diameter. As such, allometric equations based on diameter can be refined by including height, wood density, or crown area to improve accuracy [15,16]. In the vegetation type like Tea agroforestry system, extensive management practices can influence the growth and development of Tea bushes. This leads us to the assumption that biomass accumulation and allocation in different plant parts differs from other natural and planted vegetative entities. Despite the acknowledged importance, there is little knowledge about the amount of biomass accumulated in the Tea bushes contributing towards climate change mitigation as carbon sink. We hypothesized that the total biomass (above- and belowground) of Tea bushes increases with stem diameter. This study aims to (i) develop allometric equations relating stem diameter and Tea (C. sinensis (L.) O. Kuntze) biomass grown in

3044 km2 in Assam in NorthEast Indian agricultural landscapes, and (ii) determine the distribution of biomass in different aboveand belowground components based on various structural characteristics influenced by management practices and micro-climatic conditions. 2. Materials and methods 2.1. Study site Barak Valley region, which forms the southern part of Assam, covers an area of 6922 km2. The study was conducted in Tea growing areas of Cachar District (latitude 24 220 and 25 80 N; longitude 92 240 and 93150 E) of Barak Valley. The topography of the terrain is of highly undulating characterized by hills, hillocks, wide plains and low lying waterlogged areas. Most of the hills have a north south spread interspersed by strips of plain areas. The region is flanked by southern belt of Borail range. The study site experiences sub-tropical, warm and humid climate with average rainfall of 2390 mm, most of which is received during the southwest monsoon season (MayeSeptember). The mean maximum temperature ranges from 25.4  C (January) to 33.5  C (August). The mean minimum temperature ranges from 11.2  C (January) to 25.3  C (August). The soils of Barak Valley possess silty clay and loamy soil while coarse sandy loamy is found in hillock land. In fact the soil of the region is mixture of alluvial, sandy loam, muddy loam superimposed upon stones, gravels and conglomerates. Agriculture is the economic mainstay in the area, with land-use systems varying from mainly smallholder agroforestry (Homegardens) to cash croporiented farms like Bamboo (Bambusa sp.) and Rubber (Hevea brasiliensis). Rice and Tea are the major cash crops, while vegetables are grown for subsistence. 2.2. Biomass sampling A destructive sampling of 31 individual Tea bushes with a wide range of stem girth (15e25, >25e35, >35e45, >45e55 and >55 cm) at 5 cm height from the base was used for this study. Tea bushes were selected randomly irrespective of variety, and

Table 2 Correlation matrix for measurement variables of Tea harvested for the study. Variable

Diameter (cm)

Height (m)

Crown area (m2)

Wood density (g cm3)

Branch count



Diameter(cm) Height (m) Crown Area (m2) wood density(g cm3) Branch count BEF R/S

1 0.818** 0.958** 0.201 0.743** 0.383 0.074


e e

e e e

e e e e

e e e e e 1 0.028

e e e e e e 1

**Significant at p ¼ 0.01, * Significant at p ¼ 0.05.

1 0.904** 0.398* 0.739** 0.411 0.020

1 0.276 0.731** 0.383 0.080

1 0.292 0.133 0.121

1 0.210 0.147


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Fig. 1. (a) The relationship between diameter and the biomass of stem, branches, leaves and aboveground biomass (AGB), and (b) relationship between diameter and aboveground biomass (AGB), belowground biomass (BGB) and total biomass (TB) in Tea.

plantation ages, in order to capture a sample that is representative of bushes in the agroforestry system from the plantations situated between 24 390 27.700 e24 400 49.300 N latitudes and 92 390 49.900 e92 41046.800 E longitudes. The measurements of stem diameter at 5 cm from ground level D, bush height H, Crown diameter (mean of major and minor axes) was performed in 100 randomly placed quadrats of 5 m  5 m size to assess size distribution of Tea in the plantations. Depending on the sizes 6 (six) different girth classes were recognized representing the whole diameter range and from each girth class 5 (five) bushes were harvested (except < 15 cm girth class; where 6 bushes were harvested). Thus a total of 31 individual bushes were harvested for the present study. After harvesting, samples were divided into leaf; branch and stem components (aboveground) and their respective fresh weights were determined on-site by weighing on an electronic balance (20 kg) to the nearest 0.002 kg. For belowground compartment roots from individual Tea bushes were completely excavated to a depth of 1 m in square plots keeping the selected

bush at the center. Fresh weight of the root samples were measured removing embedded soil on root surfaces. Five sub-samples were collected from each component and transported in ziploc bags to the laboratory for biomass estimation. Labeled samples were ovendried for at 70  C till constant weight and their dry weight determined on a 1200 g (0.01 g) scale. Dry weight-to fresh weight ratio of different Tea components was multiplied with fresh weight to obtain biomass of the respective component. Summation of dry weights from the stems, branches and leaves yielded aboveground biomass (AGB) of individual Tea bushes. Total biomass of Tea was attained by aggregation of above- and belowground biomass. The biomass expansion factor (BEF) was calculated as a ratio between the total aboveground biomass and the biomass of the stem. The branch and stem samples collected for wood density measurement were dried (70  C until constant weight) and they were submerged in distilled water in a container placed on a pan balance. The volume of the sample was obtained using water displacement method [17]. Average wood

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Fig. 2. Parameter estimates (a) crown area, wood density, branch count, height and (b) biomass expansion factor (BEF) and root-to-shoot ratio (BGB/AGB) of different size class of Tea.

density value of both the compartment for the concerned Tea bush was considered for further appliance.

The models developed were evaluated in terms of bias and error. The quality of the estimate was expressed in terms of relative error (RE) determined as the relative difference between the predicted and the actual biomass (BM) through direct estimation [16].

2.3. Allometric equations for biomass estimation Biomass equations were developed by sharing data from destructively sampled Tea bushes. Prior to analysis it was assumed that Tea bushes exhibit similar growth and Tea biomass growing under similar conditions and management practices do not differ significantly. Scatter plots were used to check the dataset for outliers and that assisted also to assess the relationship between biomass and predictor variables. Analysis of variance (ANOVA) was carried out to evaluate the variation in the parameters considered among different size classes. Biomass values of different components and compartments were regressed on diameter (D) alone, and also on diameter in combination with height (H), wood density (WD), crown area (CA) or number of branches (NB) to obtain allometric coefficients for biomass equations. Allometric power function equation in the form y ¼ axb was used to predict biomass from diameter where y is the dependent variable and x is the independent variable, and a, the coefficient and b the allometric constant. The linear transformed form of this equation is

lnðyÞ ¼ lnðaÞ þ b  lnðxÞ where y is the dependent variable and x is the independent variable, a, and b are the intercept and slope of the regression line respectively [11,15,18]. To avoid the problem of back transformation a generalized linear model with log link function was used [15]. Developed equations were validated using cross validation with multiple sample holdouts [19]. Each individual was used both in the training set and also in the validation set. This process led to optimal assessment of bias and prediction error. All data were analyzed using Microsoft Excel 2010 version and Origin pro 8.5. Equations were built using generalized linear models in SPSS 15.0 for windows (SPSS Inc., Chicago, IL, U.S.A.). Besides D alone, several combinations of allometric relationships of dendrometric variables (H, WD, CA and NB) as supporting parameters to D were tested (equations and parameter estimates are available as supplementary material). Single easy to measure parameter D exhibited high R2 value in the regression recommending utility towards biomass prediction. The equation fitted by including ln (D) as predictor is:

lnðyÞ ¼ a þ b  lnðDÞ

2.4. Bias and error of allometric equations


where D is the diameter at 5 cm height in the Tea bush, a and b are the allometric coefficients.

RE% ¼

. o n BMactual  100 BMpredicted  BMactual

Akaike information criterion, AIC [20], was used for worthy model selection. Lower AIC value [20], and an RE close to zero [16,15] urged preferability of the model. The coefficient of determination (R2), adjusted determination coefficient (Adj. R2), root mean square error (RMSE) and the Akaike information criterion, AIC were considered as model selection criteria. 3. Results 3.1. Relationship of dendrometric variables Descriptive statistics for variables analyzed for biomass estimation in Tea are presented in Table 1. The samples cover a wide range of diameter distribution. Among different parameters considered Tea height, wood density and root-to-shoot ratio exhibited lower variations among sampled Tea bushes. BEF values estimated within the range of 2.17e8.76 and R/S ranged between 0.20 and 0.54 in the dataset. The parameters taken into consideration for analyzing allometric relationship showed significant relationship. Diameter showed strong relationship with height, crown area and branch count whereas height showed significant relationship with crown area, branch count and wood density. Besides diameter and height crown area shows relationship with branch count (Table 2). Regression of diameter with biomass of different component and compartment of Tea revealed that it has strong correlation with aboveground biomass, branch biomass, stem biomass and

Table 3 Allometric power function equations (y ¼ axb) for estimation of aboveground biomass (AGB) and the biomass of the stem, branches, leaves, roots (BGB) and total biomass. Allometeic coefficients (a, b), coefficient of determination (R2) and model bias (RE) are displayed. Component




RE (%)

AGB Stem Branches Leaves BGB TB

0.047 0.008 0.024 0.019 0.014 0.062

1.878 2.033 1.965 1.248 1.870 1.877

0.967 0.907 0.951 0.849 0.952 0.969

2.79 11.46 4.71 6.03 3.57 2.55


R.M. Kalita et al. / Biomass and Bioenergy 83 (2015) 42e49

moderate relationship with leaf biomass (Fig. 1a). Similarly the regression of root (BGB) and total biomass (TB) as a function of diameter showed significance (p < 0.0001) (Fig. 1b). Parameters like height, crown area, wood density, branch count, biomass expansion

factor, root e shoot ratio reflects differences within different size classes in Tea (Fig. 2). ANOVA showed that mean values of height, crown area, branch count, biomass expansion factor and root - toshoot ratio differed significantly in different size classes.

Fig. 3. Observed and predicted values (with 95% confidence interval) using diameter as predictor variable (Eq. (1)) and standardized residuals vs. predicted biomass values for aboveground biomass (aeb), stem biomass (ced), branch biomass (eef), leaf biomass (geh), belowground (root) biomass (iej).

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Fig. 4. Relative error (%) for different girth class of Tea bush accompanying the equations developed for estimation of (a) aboveground biomass, (b) stem biomass, (c) branch biomass, (d) leaf biomass, (e) belowground (root) biomass and (f) total biomass using diameter. Standard error of the average relative error is indicated by the error bars.

3.2. Biomass equations Observational allometric coefficients for estimating biomass of different components based on diameter applying allometric power function equation is presented in Table 3. Linear equivalent of the power equation (Eq. (1)) disclosed diameter as a significant (P < 0.0001) predictor variable for all components. Observed and predicted values (with 95% confidence interval) and standardized residuals and predicted biomass values for above- and belowground compartments depicted the utility of the equation (Fig. 3). Eq. (1) estimated AGB with a small relative error (2.4%). Stem biomass exhibited comparatively higher overestimation (10.4%) than branches (4.1%) leaves (5.7%). The equation for root biomass (BGB) and total biomass (TB) showed low RE (3.2% and 2.1% respectively) across the girth classes considered (Fig. 4). Equations incorporating D for estimating AGB and TB showed underestimation between >15 and 45 cm girth size up to 27% and 22%. Stem biomass showed high and variable RE across tree size whereas branch and leaf biomass presented moderate underestimation in >15e35 cm size range. BGB exhibited higher deviation in the >15 25 cm size class followed by smaller RE values in other categories. Except BGB and stem biomass all estimations showed higher RE values in >55 cm girth class. Height and crown area was a significant predictor variable for biomass, but wood density was not a

significant predictor variable for any of the biomass components. Incorporation of H with D improved the models (Adjusted R2 ¼ 0.985, 0.969 and 0.987 for AGB, BGB and TB estimation) compared to models with D alone (Adjusted R2 ¼ 0.966, 0.951 and 0.968 for AGB, BGB and TB estimation). Different combinations with more than two variables also showed marginal improvement of the model (incorporated as supplementary information) (Table 4). 3.3. Biomass estimates The contribution of different components to the total tree biomass varied considerably. AGB accounted for most of the total tree biomass (77%), with the stems, branches and leaves contributing 25.5%, 64.1%, and 10.4% to AGB. Much of the tree biomass is held in the branches, followed by stem and leaves respectively (Fig. 5). While the proportion of stem biomass on average, an increase with tree size, although the trend was not continuous, the percentage of branch biomass was almost constant except a considerably higher value in >25e35 cm size category. Changes in biomass allocated to leaves inversely along size. The proportion of foliage declined from 12.7% in small Tea (diameter < 15 cm) to 4.2% in high biomass trees (diameter > 55 cm). (Fig. 6) The BGB of the harvested trees accounted for 23% of the total tree biomass and the


R.M. Kalita et al. / Biomass and Bioenergy 83 (2015) 42e49

Stem; 20.59

Roots ; 23.04

Leaves; 6.24 Branches; 50.13

Fig. 5. Proportion of biomass allocation in different components of Tea bushes (%).





Girth class (cm)

15-25 >25-35 >35-45 >45-55 >55 0%


40% 60% Proportion of biomass



Fig. 6. The fraction of dry mass allocated in root, stem, branch and leaves per Tea bush in different girth classes.

proportion remained almost constant across different size classes of Tea bushes. 4. Discussion Diameter alone emerged as the best independent variable for describing the different components biomass and total Tea biomass with higher accuracy. From the functional relationship it is clearly known that diameter influenced Tea biomass significantly (R2 > 0.95) with low (

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