The study presents a plant recognition system that uses image and data processing techniques for recognition. A lot of research has been going on to identify plants by their leaves and one of the features that is used is the shape of the leaf but the accuracy is not high and therefore other features should also be considered to increase the accuracy. This system designed has three main steps which are image pre-processing, feature extraction and matching. Image pre-processing performs basic operations on the leaf image for segmentation which helps in making feature extraction easy. Seven (7) leaf features derived from geometric parameters of leaf shape were extracted from the pre-processed image and the simple principle of minimum Euclidean distance was used for finding the closest match to the input leaf image. The system used 10 species of leaves with a total of 50 leaf images from the flavia dataset for testing and obtained an accuracy above 90%. The algorithm is accurate and is easy to implement. However, it is slow and not tested on a large dataset. It is hoped that this proposed system will be exploited further and the speed will be improved and will also be able to give more information on the plant.
<abstract>
<p>Heavy metal contamination of the environment is a primary concern in Bangladesh. This study aims to characterize a novel heavy metal tolerant strain, <italic>Bacillus anthracis</italic> FHq, isolated from the tannery effluents of Savar, Bangladesh. The strain could tolerate up to 5 mM of lead nitrate, 2.5 mM of sodium arsenate, chromium chloride, cobalt chloride, 1.5 mM cadmium acetate, and 1 mM of sodium arsenite. Whole-genome sequencing analysis revealed that the genome of the strain is around 5.2 Mbp long, and the G + C content is 35.4%. Besides, FHq has genes c<italic>adC, zntA, arsCR, czcD</italic>, and c<italic>hrA</italic>, which confer lead, arsenic, cobalt, and chromium resistance, respectively. A total of nineteen other closely related and completely sequenced <italic>B. anthracis</italic> strains were selected based on average nucleotide identity along with the FHq strain for phylogenomic and pan-genome analysis. The phylogenomic analysis predicted the inter-genomic evolutionary relationship of the strain isolated from Bangladesh, and it was closely related to a strain isolated from China. Pan-genome analysis revealed that the FHq strain possesses 6045 pan genes, 3802 core genes, and 152 unique genes in its genomic content. Hence, the genetic information and comparative analysis of the FHq strain might facilitate identifying the mechanisms conferring high resistance to lead in <italic>B. anthracis</italic> strains isolated from Bangladesh.</p>
</abstract>
Citrobacter freundii SRS1, Gram-negative bacteria, were isolated from Savar, Bangladesh. The strain could tolerate up to 80 mM sodium arsenite, 400 mM sodium arsenate, 5 mM manganese sulfate, 3 mM lead nitrate, 2.5 mM cobalt chloride, 2.5 mM cadmium acetate, and 2.5 mM chromium chloride. The whole-genome sequencing revealed that the genome size of C. freundii SRS1 is estimated to be 5.4 Mbp long, and the G+C content is 51.7%. The genome of C. freundii SRS1 contains arsA. arsB, arsC, arsD, arsH, arsR and acr3 genes for arsenic resistance; czcA, czcD, cbiN, and cbiM genes for cobalt; chrA, and chrB genes for chromium; mntH, sitA, sitB, sitC, and sitD genes for manganese; and zntA genes for lead and cadmium resistance. This novel acr3 gene has never previously been reported in any C. freundii strain except SRS1. A set of 130 completely sequenced strains of C. freundii were selected for phylogenomic analysis. The phylogenetic tree showed that the SRS1 strain is closely related to the C. freundii 62 strain. Further analyses of the genes involved in metal and metalloid resistance might facilitate identifying the mechanisms and pathways involved in high metal resistance in the C. freundii SRS1 strain.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.