Due to the struggles of developing countries in coping with widespread coffee leaf diseases and infestations, the quality and quantity of coffee-based commodities have reduced significantly. This paper proposes a solution to this problem using Deep Convolutional Neural Networks (DCNN) that classifies seven coffee leaf conditions. Unlike other studies, this work proposed a novel Triple-DCNN...
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Nanotechnology for Clean and Safe Water: A Review
The demand for clean and safe water together with increasingly strict environmental regulations in both developed and developing countries has necessitated the need for a highly efficient yet low-cost water treatment technology to prevent the negative effects of pollutants on the human health and the environment. Nanotechnology holds great potential as a novel and promising...
An overview of remote monitoring methods in biodiversity conservation
Conservation of biodiversity is critical for the coexistence of humans and the sustenance of other living organisms within the ecosystem. Identification and prioritization of specific regions to be conserved are impossible without proper information about the sites. Advanced monitoring agencies like the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) had accredited that the...
Fusing compressed deep ConvNets with a self-normalizing residual block and alpha dropout for a cost-efficient classification and diagnosis of gastrointestinal tract diseases
The challenging task of diagnosing gastrointestinal (GI) tracts recently became a popular research topic, where most researchers performed extraordinary feats using numerous deep learning (DL) and computer vision techniques to achieve state-of-the-art (SOTA) diagnostic performance based on accuracy. However, most proposed methods relied on combining complex computational methods and algorithms, causing a significant increase in...
Weedy Rice Conserved Ex Situ Characterized Using Morphological and Simple Sequence Repeat (SSR) Markers
A clear understanding of genetic diversity in weedy rice is important in improving protocols for its conservation, ex situ. To this end, Asian collections of weedy rice together with accessions of the wild AA genome species Oryza nivara Sharma et Shastry and Oryza rufipogon Griffith, and the cultivated species, Oryza sativa L. were characterized using...
Kinetics and Isotherm Studies on Adsorption of Hexavalent Chromium Using Activated Carbon from Water Hyacinth
The present study is focused on the use of activated carbon derived from water hyacinth (WH-AC) as adsorbent for the removal of Cr(VI) from aqueous solution. The optimized WH-AC was found to be mesoporous and considered as granular. The surface area of 11.564 m2/g was found to have a good adsorption capacity. The adsorption data...
Integrated Weed Estimation and Pest DamageDetection in Solanum melongena Plantationvia Aerial Vision-based Proximal Sensing
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...
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....
