The Philippine government’s effort to transcend agriculture as an industry requires precision agriculture. Remote- and proximal-sensing technologies help to identify what is needed, when, and where it is needed in the farm. This paper proposes the use of vision-based indicators captured using a low-altitude unmanned aerial vehicle (UAV) to estimate weed and pest damages. Coverage...
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Coffee Leaf Rust Detection Using Convolutional Neural Network
Rust is a severe disease affecting many productive coffee regions. It is caused by a pathogenic fungi that attacks the underside of coffee leaves and it is characterized by the presence of yellow-orange and powdery points. If not treated, rust can cause a drop in coffee production of up to 45%. In this sense, this...
Threats on Natural Stand of Philippine Teak along Verde Island Passage Marine Corridor (VIPMC), Southern Luzon, Philippines.
This study documents the threats of the critically endangered Tectona philippinensis in the backdrop of the past conservation policies and projects. Twelve 20m x 50m plots were distributed in three altitudinal strata (S1= 50 – 100 m asl, S2= 150 to 200 m asl, and S3= 250 – 300 m asl) using stratified random sampling. Every tree was examined...
Bitter Melon Crop Yield Prediction using Machine Learning Algorithm
This research paper aimed to determine the crop bearing capability of bitter melon or bitter gourd more commonly called “Ampalaya” in the Filipino language. Images of bitter melon leaves were gathered from Ampalaya farms and these were used as main data of the research. The leaves were classified as good and bad through their description....
