Development of Prediction Regression Equations for Biomass Estimation in Eucalyptus Forest Plantations in the Punjab State of India
Deepak Kholiya1, Rakesh Chandra Bhadula2, Amit Kumar Mishra3, Ajay Sharma4, Satyajeet Singh5

1Deepak Kholiya, Department of Agriculture, Graphic Era Hill University, Dehradun.

2Rakesh Chandra Bhadula, Department of Mathematics, Graphic Era Hill University, Dehradun.

3Amit Kumar Mishra, Department of Computer Science & Engineering, Graphic Era Hill University, Dehradun.

4Ajay Sharma, Department of SOM Graphic Era Hill University, Dehradun.

5Dr Satyajeet Singh, Department of Mathematics, Graphic Era Deemed to be University, Dehradun.

Manuscript received on 13 October 2019 | Revised Manuscript received on 20 October 2019 | Manuscript Published on 29 June 2020 | PP: 20-32 | Volume-8 Issue-10S2 August 2019 | Retrieval Number: J100608810S219/2019©BEIESP | DOI: 10.35940/ijitee.J1006.08810S219

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Abstract: Prediction equations have been worked out on the basis of 17 trees felled for Eucalyptus hybrid for different tree components on the basis of diameter and height (D2 H) which was found to be best suited as depended variable over D & D2 (Diameter at Breast Height 1.37 m). The correlation coefficient (r2 ) values of all the tree components are significant where as these values for AGB (Above Ground Biomass), BGB (Below Ground Biomass) and Total Biomass (TB) is highly significant. These developed prediction equations are validated by comparing the predicted values of total biomass of overall average trees felled with their actual / calculated biomass. The differences of predicted and actual biomass ranged from 6.8 to 38.5 % of different diameter classes in the felled Eucalyptus trees. Generally differences between predicted and actual biomass in percentages of 10 – 30 % is universally acceptable in forest management.

Keywords: Eucalyptus tree, Prediction equation, Diameter class, Biomass etc.
Scope of the Article: