GEOGRAPHIC INFORMATION SYSTEMS AS KEY TOOLS IN THE PHYTOSANITARY MANAGEMENT OF MEZCAL AGAVE (Agave angustifolia Haw) IN THE STATE OF MEXICO, MEXICO

Authors

  • Atenas Tapia-Rodríguez
  • José Francisco Ramírez-Dávila UAEM
  • Agustin David Acosta-Guadarrama
  • Alfredo Ruiz-Orta

DOI:

https://doi.org/10.47163/agrociencia.v60i3.3540

Keywords:

Scyphophorus acupunctatus, Fusarium oxysporum, geospatial analysis, integrated pest management, Agave tequilana Weber, YOLO algorithms, drone, precision agriculture.

Abstract

Mezcal agave (Agave angustifolia Haw.) is a key resource for the economy and culture of the State of Mexico. However, it faces a phytosanitary crisis due to pests such as the agave weevil (Scyphophorus acupunctatus Gyllenhaal, 1838) and diseases such as Fusarium oxysporum wilt, causing losses of up to 50 % in production. The lack of efficient monitoring systems justifies the development of a Geographic Information System (GIS) to optimize phytosanitary management. This study aimed to design a GIS that integrates biophysical and management variables to identify risk zones and facilitate integrated management strategies. Four plots were monitored in the municipalities of Malinalco and Zumpahuacán in 2024, with 100 plants per plot georeferenced. The incidence of S. acupunctatus and F. oxysporum was assessed monthly, along with environmental and management variables. Data were processed using QGIS 3.24, generating risk maps through interpolation (Inverse Distance Weighted (IDW) and Kriging) and spatial correlation analysis (Moran’s I). Statistical analyses included analysis of variance (ANOVA) and multiple regression. The results demonstrated that GIS-generated risk maps allow highly accurate identification of infestation hotspots. In Malinalco Centro, weevil incidence was positively correlated with accumulated precipitation (r = 0.65, p < 0.05) and clay soils, exhibiting a spatial aggregation pattern (Moran’s I = 0.42, p < 0.01). For F. oxysporum, soil moisture (>60 %) was the most influential factor (β = 0.62; p = 0.002), with critical zones expanding radially at 15 m per month. The Random Forest model predicted weevil incidence with 88.2 % accuracy (AUC-ROC = 0.91). This integrated approach, replicable in other agave-growing regions, would contribute to crop sustainability by enabling spatially targeted interventions, optimizing resources, and reducing input use.

Additional Files

Published

11-05-2026

Issue

Section

Plant Protection