An initiative from Central Luzon State University (CLSU) is set to mitigate pest infestations and outbreaks in corn and onion through PEST D-Tech, a crop monitoring system enabled by drones. The project will later establish data integration and cooperation between UGV of Taiwan and UAV or drone of the Philippines.
Led by Dr. Gella Patria L. Abella and Dr. Elaida R. Fiegalan, the project integrates drone technology with agriculture through normalized difference vegetation index (NDVI) analysis using unmanned aerial vehicles (UAV) imagery to enable precise monitoring of crop health of corn and onion.
The project is supported by the Department of Science and Technology through the Manila Economic and Cultural Office – Taipei Economic and Cultural Office (MECO-TECO) Joint Research Program and monitored by the Philippine Council for Agriculture, Aquatic and Natural Resources Research and Development of the Department of Science and Technology (DOST-PCAARRD).
To capture high-resolution images of corn and onion fields and to gather multispectral data of vegetation vigor and stress, CLSU deployed UAV equipped with powerful multispectral cameras and sensors in selected municipalities of Tarlac and Nueva Ecija.
The mapping of NDVI results are being done through the use of the Quantum Geographic Information System (QGIS) which supports the viewing, editing, and analysis of geospatial data. These maps serve as crucial tools for targeted intervention strategies, allowing for efficient allocation of resources and proactive management efforts in vulnerable zones.
With two comprehensive pest and disease infestation maps already developed by the project team, farmers and agricultural officers are provided spatially explicit maps that provide a detailed visual representation of the distribution and intensity of key pests and diseases affecting their agricultural areas.
Unmanned ground vehicles (UGV) are also going to be explored and deployed by the project in its third implementation year. Through this, farmers and other stakeholders can quickly and efficiently assess large fields, detect early signs of diseases or nutrient deficiency, and make data-driven decisions for targeted irrigation, fertilization, and pest control.
Set to be completed by March 2026, the project will be creating tailored strategies for managing crop pests and diseases for corn and onion. The development of this initiative is expected to benefit municipal agricultural officers, cooperatives, and non-government stakeholders as it can proactively prevent widespread infestations and outbreaks through the timely release of pest and disease advisories for farmers.