3 research outputs found
Plant disease detection using ensembled CNN framework
No full textAgriculture exhibits the prime driving force for growth of agro-based economies globally. In the field of agriculture, detecting and preventing crops from attacks of pests is the major concern in today\u27s world. Early detection of plant disease becomes necessary to prevent the degradation in the yield of crop production. In this paper, we propose an ensemble based Convolutional Neural Network (CNN) architecture that detects plant disease from the images of the leaves of the plant. The proposed architecture takes into account CNN architectures like VGG-19, ResNet-50, and InceptionV3 as its base models, and the prediction from these models is used as an input for our meta-model (Inception-ResNetV2). The approach helped us in building a generalized model for disease detection with an accuracy of 97.9 % under test conditions
Mechanism of anti-angiogenic property of gold nanoparticles: role of nanoparticle size and surface charge
No full textEvaluation of metal contamination and phytoremediation potential of aquatic macrophytes of East Kolkata Wetlands, India
No full textObjectives The present study analyzes metal contamination in sediment of the East Kolkata Wetlands, a Ramsar site, which is receiving a huge amount of domestic and industrial wastewater from surrounding areas. The subsequent uptake and accumulation of metals in different macrophytes are also examined in regard to their phytoremediation potential. Methods Metals like cadmium (Cd), copper (Cu), manganese (Mn), and lead (Pb) were estimated in sediment, water and different parts of the macrophytes Colocasia esculenta and Scirpus articulatus. Results The concentration of metals in sediment were, from highest to lowest, Mn (205.0±65.5 mg/kg)>Cu (29.9±10.2 mg/kg)>Pb (22.7±10.3 mg/kg)>Cd (3.7±2.2 mg/kg). The phytoaccumulation tendency of these metals showed similar trends in both native aquatic macrophyte species. The rate of accumulation of metals in roots was higher than in shoots. There were strong positive correlations (p<0.001) between soil organic carbon (OC) percentage and Mn (r =0.771), and sediment OC percentage and Pb (r=0.832). Cation exchange capacity (CEC) also showed a positive correlation (p<0.001) with Cu (r=0.721), Mn (r=0.713), and Pb (r=0.788), while correlations between sediment OC percentage and Cu (r=0.628), sediment OC percentage and Cd (r=0.559), and CEC and Cd (r=0.625) were significant at the p<0.05 level. Conclusions Bioaccumulation factor and translocation factors of these two plants revealed that S. articulatus was comparatively more efficient for phytoremediation, whereas phytostabilization potential was higher in C. esculenta
