GEOSPATIAL MAPPING OF MANGO ORCHARDS FOR FRUIT FLY PEST RISK ANALYSIS IN NEGROS OCCIDENTAL
Authors: Ma. Theresa M. Jurilla and Dr. Angelita P. Caña
Ma. Theresa M. Jurilla: State University of Northern Negros, Philippines.
Dr. Angelita P. Caña: State University of Northern Negros, Philippines.
ABSTRACT
This study aims to develop a geospatial mapping approach for identifying and assessing fruit fly pest risks in mango orchards in Negros Occidental. By integrating uncrewed aerial vehicle (UAV) data, specifically drone imagery, with field survey observations, the research aims to delineate mango orchard distribution and evaluate spatial patterns associated with pest incidence. Aerial imagery from unmanned aerial vehicles (UAVs) was utilized to classify land use and accurately map mango-growing areas. At the same time, environmental variables such as temperature, humidity, elevation, vegetation cover, proximity to water sources, and other significant factors-including terrain characteristics (e.g., open fields, flat, rolling, and mountainous areas)-were incorporated to model pest suitability. The results demonstrate that geospatial methods can detect areas with increased fruit fly risk and locate mango orchards with high accuracy. Spatial analyses revealed that the fruit fly infestations are strongly correlated with specific environmental conditions, particularly warmer temperatures, moderate humidity, and areas with dense vegetation cover. Risk maps generated from the model identified several high-vulnerability clusters, thereby facilitating targeted monitoring and intervention. Validation using field data confirmed the reliability of the mapping outputs, demonstrating consistency between predicted and observed pest occurrences. The study concludes that geospatial mapping is a valuable tool for fruit fly pest risk analysis in mango production, providing a cost-effective and scalable approach for early detection, surveillance planning, and resource allocation. Furthermore, the integration of spatial data and environmental factors enhances the predictive capability of pest management strategies, thereby contributing to improved crop protection and reduced economic losses. Thus, the potential economic consequences can be effectively assessed by considering the direct and indirect effects of fruit fly pests, the probability of their spread within the province of Negros Occidental, the measures that may be applied, and the associated biological impacts. Future work should focus on incorporating temporal data for dynamic risk forecasting and expanding the model to include other pest species.
Keywords: Fruit fly, fruit fly incidence, geospatial mapping, mango orchard, pest risk analysis