| Resumo: | Statistical analysis between three weighted additive biomass equations are presented for planted pine species typical of the coniferous forests of the Western Sierra Madre mountain range of Durango, Mexico. Statistical and graphical analyses were used to select the best single and multiple individual biomass component equation. Linear equations better fitted the biomass components. Therefore, three linear additive procedures were tested: (i) the conventional, (ii) a harmonization, and ( iii) the seemingly-unrelated regression in two types of equations of component biomass estimation using both simple regression and multiple regression techniques. These tests were performed at two scales: (a) each of three pine species and (b) all three species. For both the simple linear and best multiple regression equation, the seemingly-unrelated equations provided more precise biomass component estimates, with tendencies consistent with the conventional non-additive non-linear regression procedures, and provided average biomass component estimates when equations were applied to a data set of 23 sample quadrants.
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