| Gaia: | The importance of estimating biomass volumes for the management of wood and non wood forest products has been recently recognized by the government of Mexico. This is partially recognized by the implementation of government programs for the payment of environmental services, by the Mexican Forestry Commission. This research was carried out at the Municipalities of Tezonapa and Uxpanapa, Veracruz, Mexico with the objective of estimating statistical coefficients with the least variance by comparing different additive techniques of biomass component estimation (stem, branch, and total) for the latex clon IAN-710 coming from commercial forest plantations for latex production. Field data collected were fresh and dry weight values. Coefficients of two biomass equations were evaluated: 1) the combined variable of Spurr (1952) and 2) the best regression model. Four ways of estimating parameters were tested: 1) conventional linear regression, 2) weighted linear regression, 3) seemingly unrelated linear regression, and 4) weighted seemingly unrelated linear regression. When comparing the t values of the coefficients, it was found that the least variance coefficients were estimated in weighted seemingly unrelated linear regression and the coefficients did not show significant change. Therefore, this equation is recommended for estimating coefficients of equations for biomass components and total for the latex clon IAN-710.
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