Abstract

GONZALEZ LOPEZ, Héctor Darío et al. Biomass and dry leaf yield of Lippia graveolens Kunth. Rev. mex. de cienc. forestales [online]. 2025, vol.16, n.92, pp.160-178.  Epub Feb 06, 2026. ISSN 2007-1132.  https://doi.org/10.29298/rmcf.v16i92.1577.

Mexican oregano (Lippia graveolens) is a non-timber forest product of nutritional interest and pharmaceutical use. There is a lack of precise quantitative information on harvesting in natural populations and their response to exploitation. The objective of this study was to adjust regression models for estimating the fresh leaf weight (flw) and dry leaf weight (dlw) in order to generate biomass yield tables for fresh and dry leaves in wild populations of Melchor Ocampo, Zacatecas. In the field, the following morphometric variables were measured: height (h, cm) and average canopy diameter (acd, cm) per plant, fresh leaf weight (flw, g) and dry leaf weight (dlw, g). To estimate the flw and dlw, regression models were adjusted by the probability of committing a type I error (P<0.01) in the regression, the highest adjusted Coefficient of determination value ($R_{aj}^2$), and minimum values for the Root mean square error (RMSE) and Coefficient of variation (CV). On average, the flw per plant was 149.4±62.9 g and the dlw was 31.1±13.8 g. The density was 8 272 plants ha-1. The fresh weight was estimated using the $flw=\left(22.063\right){\left(1.050\right)}^{acd}$ model, which was highly significant (P<0.01) and exhibited very good fits ($R_{aj}^2$=0.979, RMSE=0.064, CV=1.29 %). The model utilized for the dry weight was $dlw=\left(10.933\right){\left(1.027\right)}^{acd}$, with $R_{aj}^2$=0.909, RMSE=0.075 and CV=2.21 %. The selected models showed that the morphometric variable acd of L. graveolens predicts more than 90 % of the variation in flw and dlw in the study area.

Keywords : Correlation analysis; nonlinear model; regression models; oregano; dry leaf yield table; morphometric variables.

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