PREDICTION OF THE VARIATION OF ABOVE GROUND BIOMASS AND CARBON CONTENT OF COCONUT TREES WITH AGE - Nanayakkara, P.S.S.; Subasinghe, S.M.C.U.P.; Peiris, V.R.S. (Uni-In Alliance 2016, 2016)
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Coconut (Cocos nucifera) is a monocotyledonous plant belongs to family Arecaccuc It is grown on about 11.8 million ha of lands in more than 92 countries. Coconut plantations occupy over 6% of the total land area of Sri Lanka and significantly contribute .• to the national economy of the country. Due to the recent trends in carbon trade, COCOIIIII plantations in Sri Lanka have a high potential to enter to the carbon market. Therefore this study attempted to build mathematical models to identify the :d)(\\ (' ground variation of biomass and Carbon contents in Coconut trees with the age. In order for data collection, 23 plantations of age classes varying from 5 to 50 wrr l' selected from the Kurunegala district of low country intermediate zone. 20 coconut tr l'\' were selected from each plantation and diameter and height were measured. Number III fronds was counted. Frond and stem samples were collected from the plantat ions :111<1 saw mills respectively for estimation of biomass and carbon. Frond biornasx \\ 11'1 estimated by weight-weight method and that of stem was estimated by volumc-wcruht method. Samples were oven dried at 1050 C for until a constant weight was obtained lilld the carbon content was estimated by Walkley-Black method. According to the rle'sldt>" diameter and height of coconut trees vary from 23.7cm to 29.5cm and 1.1m to I() \(1I1\ . ' from 5 to 50 years respectively. Tree biomass and carbon vary from 77.32() k,. 11\ 333.159 kg and 57.797 kg to 252.985 kg respectively for the same time period. Ill!ll\ biomass and carbon were modelled keeping age and height as explanatory Y<I,inhll';l. The resultant models are given below and the ~ values were 96.8 for both of models Tree Biomass = 53.9 - 3.03 Age + 27.3 H Tree Carbon = C = 39.5 - 2.28 Age + 20.7 H
Keywords: Coconut Biomass; Cocos nucifera; Carbon storage; Non-destructive sampling