Allometric Equations to Estimate Sugarcane Aboveground Biomass
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Sugarcane harvest implies in the movement of very large amounts of biomass and, therefore, demands careful planning of logistics. Accurate pre-harvest estimation of sugarcane field productivity provides useful data to plan harvest, transportation, selling and industrial processing activities. Currently, the estimation of sugarcane biomass in the field is based on destructive techniques. The use of allometric equations is an adequate, nondestructive tool to provide this information, but these equations are scarcely available for sugarcane. We created regression models to estimate stem fresh (SFB, kg) and total aboveground dry biomass (AB, kg) based on plant height (H, cm) and diameter (D, cm), for different Brazilian sugarcane varieties. The models adequately estimated biomass for all sugarcane varieties. Based on that, we developed two general equations valid for all varieties: SFB = 0.046 H × D1.5647 and AB = 0.4001 H × D1.0743. To calculate biomass per hectare, SFB and AB must be multiplied by the average number of stems in the row (N) and divided by row spacing (S). In our study site, N was adequately estimated counting stems in four 100-m row segments. Overall, precise estimates of stem and whole plant biomass for sugarcane can be obtained using the general equations and the number of stems per area. We believe these equations are also useful to estimate biomass for other sugarcane varieties around the world, considering the simplicity of sugarcane plant structure.
KeywordsStem diameter Plant height Number of stems Cane weight Dry biomass
The authors of this paper thank CNPq, Capes and Facepe for the scholarships to students and research scientists and also for financial support through the following research grants: “Consolidation of the Research Center on Water and Carbon Dynamics in Ecosystems in the State of Pernambuco” (Edital 08/2014 Facepe Pronem, APQ-0532-5.01/14); and also for the project “Data generation and modeling to support policies for adaptation to climatic variability in agricultural systems in the Northeast region” (CNPq Edital 37/2013–Climatic Changes, Proc. 403129/2013-3).
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