Predictive models for dry biomass and carbon stock estimation in Litchi chinensis under hot and dry sub-humid climate. Issue 10 (24th August 2018)

• Record Type: Journal Article
• Authors: Naik, Sushanta Kumar; Sarkar, Pradip Kumar; Das, Bikash; Singh, Arun Kumar; Bhatt, Bhagwati Prasad
• Is Part Of: Archives of agronomy and soil science. Volume 64:Issue 10(2018)
• Page Start: 1366
• Page End: 1378
• Publication Date: 2018-08-24
• Subjects: Biomass -- Carbon -- Litchi chinensis -- Predictive models -- Richard's model; Horticulture -- Periodicals; Soils -- Periodicals; 630.5
• DOI: 10.1080/03650340.2018.1434718
• Languages: English
• ISSNs: 0365-0340

Abstract

ABSTRACT: Accurate and reliable predictive models are necessary to estimate above and below ground biomass of plant and biomass carbon stock non-destructively. Different growth models namely viz, Linear, Allometric, Logistic, Gompertz, Richard's, Negative exponential, Monomolecular, Mitcherlich and Weibull were fitted to the relationship between dry biomass of litchi tree components with collar diameter. Richard's model outperformed the others and fulfilled the validation criterions to the best possible extent with lowest Akaike information criteria ( AICc ) of 90.47 and root mean square error (RMSE) of 1.79. The value of adjusted R 2 ranged from 0.947 to 0.971 for the Richard's models fitted on various biomass components and the 't' values for all the components was found non-significant (p > 0.05) indicating the validation of the model. The estimated total dry biomass varied from 0.50 Mg ha −1 in two year to 5.71 Mg ha −1 in 10 year old litchi orchards. The estimated stored biomass carbon stock in litchi orchards (branches, bole and roots) varied from 0.10 Mg ha −1 in two year to 1.85 Mg ha −1 in 10 year orchards with CO2 sequestration potential from 0.19–4.63 Mg ha −1 .