Performance evaluation of a machine vision system for insect pests identification of field crops using artificial neural networks

Feature extraction is a crucial part of advanced image recognition systems. In this research, an autonomous detection device was designed and developed for insect pest detection to improve the ability of intelligent systems in order to annihilate harmful insect pests in agricultural crop fields. Device included a dark chamber, a CCD digital camera, a LDR lightening module and a personal computer. The proposed programme for precise insect pest detection was based on an image processing algorithm and artificial neural networks (ANNs). After image acquisition, the insect pests’ images were extracted from original images with Canny filtration. Afterwards, four morphological and three textural features from the obtained images were measured and normalised. Performance of ANN model was tested successfully for Beet armyworm (Spodoptera exigua) recognition in images using back-propagation supervised learning method and inspection data. Results showed that proposed system was able to identify S. exigua in the images from other species. Such this machine vision system can be used in autonomous field robots to achieve a modern farmer’s assistant.     

An artificial neural network approach to identify fungal diseases of cucumber (Cucumis sativus L.) plants using digital image processing

Nowadays, artificial intelligence solutions such as digital image processing and artificial neural networks (ANN) have become important applicable techniques in phytomonitoring and plant health detection systems. In this research, an autonomous device was designed and developed for detecting two types of fungi (Pseudoperonospora cubensis, Sphaerotheca fuliginea) that infect the cucumber (Cucumis sativus L.) plant leaves. This device was able to recognise the fungal diseases of plants by detecting their symptoms on plant leaves (downy mildew and powdery mildew). For leaves of cucumber inoculated with different spores of the fungi, it was possible to estimate the amount of hour post inoculation (HPI) by extracting leaves’ image parameters. Device included a dark chamber, a CCD digital camera, a thermal camera, a light dependent resistor lightening module and a personal computer. The proposed programme for precise disease detection was based on an image processing algorithm and ANN. Three textural features and two thermal parameters from the obtained images were measured and normalised. Performance of ANN model was tested successfully for disease recognition and detecting HPI in images using back-propagation supervised learning method and inspection data. Such this machine vision system can be used in robotic intelligent systems to achieve a modern farmer’s assistant in agricultural crop fields.     

Selective bactericidal activity of nanopatterned superhydrophobic cicada Psaltoda claripennis wing surfaces

The nanopattern on the surface of Clanger cicada (Psaltoda claripennis) wings represents the first example of a new class of biomaterials that can kill bacteria on contact based solely on its physical surface structure. As such, they provide a model for the development of novel functional surfaces that possess an increased resistance to bacterial contamination and infection. Their effectiveness against a wide spectrum of bacteria, however, is yet to be established. Here, the bactericidal properties of the wings were tested against several bacterial species, possessing a range of combinations of morphology and cell wall type. The tested species were primarily pathogens, and included Bacillus subtilis, Branhamella catarrhalis, Escherichia coli, Planococcus maritimus, Pseudomonas aeruginosa, Pseudomonas fluorescens, and Staphylococcus aureus. The wings were found to consistently kill Gram-negative cells (i.e., B. catarrhalis, E. coli, P. aeruginosa, and P. fluorescens), while Gram-positive cells (B. subtilis, P. maritimus, and S. aureus) remained resistant. The morphology of the cells did not appear to play any role in determining cell susceptibility. The bactericidal activity of the wing was also found to be quite efficient; 6.1?±?1.5?×?10⁶ P. aeruginosa cells in suspension were inactivated per square centimeter of wing surface after 30-min incubation. These findings demonstrate the potential for the development of selective bactericidal surfaces incorporating cicada wing nanopatterns into the design.     

A Precisely Designed Immunotoxin Against VCAM1 Consisting of a Humanized Antibody Variable Domain Fused to Granzyme: An In Silico Approach

International Journal of Peptide Research and Therapeutics - Atherosclerosis is a complex disease related to cardiovascular disorders and is one of the most considerable causes of mortality...     

Molecular Organization of the Nanoscale Surface Structures of the Dragonfly Hemianax papuensis Wing Epicuticle

The molecular organization of the epicuticle (the outermost layer) of insect wings is vital in the formation of the nanoscale surface patterns that are responsible for bestowing remarkable functional properties. Using a combination of spectroscopic and chromatographic techniques, including Synchrotron-sourced Fourier-transform infrared microspectroscopy (FTIR), x-ray photoelectron spectroscopy (XPS) depth profiling and gas chromatography-mass spectrometry (GCMS), we have identified the chemical components that constitute the nanoscale structures on the surface of the wings of the dragonfly, Hemianax papuensis. The major components were identified to be fatty acids, predominantly hexadecanoic acid and octadecanoic acid, and n-alkanes with even numbered carbon chains ranging from C₁₄ to C₃₀. The data obtained from XPS depth profiling, in conjunction with that obtained from GCMS analyses, enabled the location of particular classes of compounds to different regions within the epicuticle. Hexadecanoic acid was found to be a major component of the outer region of the epicuticle, which forms the surface nanostructures, and was also detected in deeper layers along with octadecanoic acid. Aliphatic compounds were detected throughout the epicuticle, and these appeared to form a third discrete layer that was separate from both the inner and outer epicuticles, which has never previously been reported.     

In silico experiment with an-antigen-toll like receptor-5 agonist fusion construct for immunogenic application to Helicobacter pylori

BACKGROUNDS:

Helicobacter pylori colonize the gastric mucosa of half of the world''s population. Although it is classified as a definitive type I carcinogen by World Health Organization, there is no effective vaccine against this bacterium. H. pylori evade the host immune response by avoiding toll-like detection, such as detection via toll-like receptor-5 (TLR-5). Thus, a chimeric construct consisting of selected epitopes from virulence factors that is incorporated into a TLR-5 ligand (Pseudomonas flagellin) could result in more potent innate and adaptive immune responses.

MATERIALS AND METHODS:

Based on the histocompatibility antigens of BALB/c mice, in silico techniques were used to select several fragments from H. pylori virulence factors with a high density of B- and T-cell epitopes.

RESULTS:

These segments consist of cytotoxin-associated geneA (residue 162-283), neutrophil activating protein (residue 30-135) and outer inflammatory protein A (residue 155-268). The secondary and tertiary structure of the chimeric constructs and other bioinformatics analyses such as stability, solubility, and antigenicity were performed. The chimeric construct containing antigenic segments of H. pylori proteins was fused with the D3 domain of Pseudomonas flagellin. This recombinant chimeric gene was optimized for expression in Escherichia coli. The in silico results showed that the conserved C- and N-terminal domains of flagellin and the antigenicity of selected fragments were retained.

DISCUSSION:

In silico analysis showed that Pseudomonas flagellin is a suitable platform for incorporation of an antigenic construct from H. pylori. This strategy may be an effective tool for the control of H. pylori and other persistent infections.     

Analysis of microRNA signatures using size-coded ligation-mediated PCR

The expression pattern and regulatory functions of microRNAs (miRNAs) are intensively investigated in various tissues, cell types and disorders. Differential miRNA expression signatures have been revealed in healthy and unhealthy tissues using high-throughput profiling methods. For further analyses of miRNA signatures in biological samples, we describe here a simple and efficient method to detect multiple miRNAs simultaneously in total RNA. The size-coded ligation-mediated polymerase chain reaction (SL-PCR) method is based on size-coded DNA probe hybridization in solution, followed-by ligation, PCR amplification and gel fractionation. The new method shows quantitative and specific detection of miRNAs. We profiled miRNAs of the let-7 family in a number of organisms, tissues and cell types and the results correspond with their incidence in the genome and reported expression levels. Finally, SL-PCR detected let-7 expression changes in human embryonic stem cells as they differentiate to neuron and also in young and aged mice brain and bone marrow. We conclude that the method can efficiently reveal miRNA signatures in a range of biological samples.     

Protein,fatty acid,and pigment content of <Emphasis Type="Italic">Chlorella vulgaris</Emphasis> under different light regimes

The effects of irradiance and photoperiod on growth rates, chlorophyll a, β-carotene, total protein, and fatty acid content of Chlorella vulgaris were determined. The maximum growth rate (1.13 day⁻¹) was at 100 μmol photons m⁻² s⁻¹ and 16:8-h light/dark photoperiod. Chlorophyll a and β-carotene contents significantly differed under different light regimes with chlorophyll a content lower at high irradiance and longer light duration, while β-carotene showed the inverse trend. The total protein and fatty acid content also significantly differed in different light regimes; the maximum percentage of protein (46%) was at 100 μmol photons m⁻² s⁻¹ and 16:8 h photoperiod, and minimum (33%) was at 37.5 μmol photons m⁻² s⁻¹ and 8:16 h photoperiod; the total saturated fatty acids increased, while monounsaturated and polyunsaturated fatty acids decreased with increasing irradiance and light duration.