The use of medicinal plants represents an alternative method for bacterial control due to their chemical compositions. This study’s objective was to determine the inhibitory capacity of Larrea tridentata extracts against microbial strains of clinical interest. Four extracts were prepared, their phytochemical profiles were determined, and their antioxidant capacities were quantified. Additionally, the minimum concentrations of hemolysis were determined using human blood erythrocytes. For the extracts’ growth inhibitory capacity, six bacterial and two fungal strains were evaluated using the disk diffusion test. Commercial medications specific for each strain were used as controls. The ethanolic extracts registered the greatest diversity of metabolites related to antibacterial activity. The inhibitory activities of the ethanolic extract and the Cedax^® control were similar for Enterococcus faecalis. A principal component analysis was performed with X² and ANOVA tests to identify the relationships and the effects of the extracts on bacterial inhibition, obtaining p > 0.05 with a confidence level of 95%. This research highlights the potential of L. tridentata extracts as an alternative treatment and to mitigate the growing problem of resistance to traditional antibiotics.

Secondary metabolites (SM) in plants play crucial pharmacological, ecological, and nutritional roles for humans, wildlife, and livestock. Environmental Heterogeneity (EH) encompasses the variability of biotic and abiotic factors that influence biological responses of plant species. Advancements in remote sensing have enhanced the ability to assess plant functional traits more affordably and comprehensively by integrating spectral reflectance data with detailed plant metabolomics. However, studies investigating the relationship between EH—quantified using Rao’s Q heterogeneity index from remote sensing data—and SM diversity remain limited. Here, we present the first report demonstrating that the biotic component of EH, measured as Rao’s Q, is positively associated with SM diversity in mesquite pod extracts—higher Rao’s Q values correspond to greater SM diversity. Generalized additive models (GAMs) revealed that Rao’s Q contributed the most explanatory power, accounting for 21.2% of the deviance, compared to pod weight (13.7%) and pod length (2.03%). However, only the relationship between Rao’s Q and SM diversity was statistically significant (p = 0.029). The Rao’s Q index derived from remote sensing serves as a scalable proxy for identifying SM hotspots, facilitating the targeted discovery of regions with high pharmacological or nutritional value.

La cerveza es una bebida natural obtenida por fermentación alcohólica de un extracto acuoso de cebada malteada. Las materias son sólo cuatro; malta de cebada, agua, levadura y lúpulo. En México, la cerveza es la que domina el mercado de bebidas alcohólicas, a partir del 2011 se observa un crecimiento sostenido de la cerveza artesanal en este país. Para la presente investigación, se recolectaron 23 muestras de cerveza artesanal y 7 industrializadas en su mayoría del estado de Zacatecas, se clasificaron según su color, se les determinó el porcentaje de alcohol en volumen, metanol mediante cromatografía de gases, grados Brix, % acidez, pH, extracto seco, cenizas, se aplicó la técnica de UV-Vis y se analizaron los espectros con el método de análisis multivariante no supervisado conocido como PCA (Principal Component Analysis) por sus siglas en inglés. Las bebidas alcohólicas, se catalogaron por color (clara, semi obscura y obscura) basándose en la malta que se usa para su elaboración, los resultados del porcentaje de alcohol de las cervezas están dentro de lo establecido por la Norma Oficial Mexicana NOM-199-SCFI-2017, en cuanto a los valores de metanol obtenidos por el método de cromatografía, se encuentran muy por debajo de los límites establecidos. Las muestras se analizaron con espectroscopía UV-Vis, obteniendo señales analíticas propias, observándose una buena discriminación entre los tipos de cervezas. Utilizando el análisis de PCA para la técnica de UV-Vis, se pudo reducir las variables y ubicar las muestras en una zona característica de acuerdo con el tipo de cerveza, obteniendo agrupaciones características de los diferentes tipos.