Background and Objective The Coronavirus 2019, or shortly COVID-19, is a viral disease that causes serious pneumonia and impacts our different body parts from mild to severe depending on patient’s immune system. This infection was first reported in Wuhan city of China in December 2019, and afterward, it became a global pandemic spreading rapidly around the world. As the virus spreads through human to human contact, it has affected our lives in a devastating way, including the vigorous pressure on the public health system, the world economy, education sector, workplaces, and shopping malls. Preventing viral spreading requires early detection of positive cases and to treat infected patients as quickly as possible. The need for COVID-19 testing kits has increased, and many of the developing countries in the world are facing a shortage of testing kits as new cases are increasing day by day. In this situation, the recent research using radiology imaging (such as X-ray and CT scan) techniques can be proven helpful to detect COVID-19 as X-ray and CT scan images provide important information about the disease caused by COVID-19 virus. The latest data mining and machine learning techniques such as Convolutional Neural Network (CNN) can be applied along with X-ray and CT scan images of the lungs for the accurate and rapid detection of the disease, assisting in mitigating the problem of scarcity of testing kits. Methods Hence a novel CNN model called CoroDet for automatic detection of COVID-19 by using raw chest X-ray and CT scan images have been proposed in this study. CoroDet is developed to serve as an accurate diagnostics for 2 class classification (COVID and Normal), 3 class classification (COVID, Normal, and non-COVID pneumonia), and 4 class classification (COVID, Normal, non-COVID viral pneumonia, and non-COVID bacterial pneumonia). Results The performance of our proposed model was compared with ten existing techniques for COVID detection in terms of accuracy. A classification accuracy of 99.1% for 2 class classification, 94.2% for 3 class classification, and 91.2% for 4 class classification was produced by our proposed model, which is obviously better than the state-of-the-art-methods used for COVID-19 detection to the best of our knowledge. Moreover, the dataset with x-ray images that we prepared for the evaluation of our method is the largest datasets for COVID detection as far as our knowledge goes. Conclusion The experimental results of our proposed method CoroDet indicate the superiority of CoroDet over the existing state-of-the-art-methods. CoroDet may assist clinicians in making appropriate decisions for COVID-19 detection and may also mitigate the problem of scarcity of testing kits.

CoroDet: A deep learning based classification for COVID-19 detection using chest X-ray images.

Continuous increase in global human population and depletion of natural resources of energy posing threat to environment needs, sustainable supply of food and energy. The most ecofriendly approach 'green technology' has been exploited for biofertilizer preparation. Cyanobacteria are the most successful and sustained prokaryotic organism during the course of evolution. They are considered as one of the primitive life forms found on our planet. Cyanobacteria are emerging candidates for efficiently conversion of radiant energy into chemical energy. This biological system produces oxygen as a by-product. Cyanobacterial biomass can also be used for the large scale production of food, energy, biofertilizers, secondary metabolites, cosmetics and medicines. Therefore, cyanobacteria are used in ecofriendly sustainable agricultural practice for production of biomass of very high value and decreasing the level of CO2. This review article describes the methods of mass production of cyanobacterial biofertilizers and their applications in agriculture and industrial level.

Cyanobacteria as a source of biofertilizers for sustainable agriculture.

Continuous decline of earth’s natural resources and increased use of hazardous chemical fertilizers pose a great concern for the future of agriculture. Biofertilizers are a promising alternative to hazardous chemical fertilizers and are gaining importance for attaining sustainable agriculture. Biofertilizers play a key role in increasing crop yield and maintaining long-term soil fertility, which is essential for meeting global food demand. Microbes can interact with the crop plants and enhance their immunity, growth, and development. Nitrogen, phosphorous, potassium, zinc, and silica are the essential nutrients required for the proper growth of crops, but these nutrients are naturally present in insolubilized or complex forms. Certain microorganisms render them soluble and make them available to the plants. The potential microbes, their mode of action, along with their effect on crops, are discussed in this review. Biofertilizers, being cost effective, non-toxic, and eco-friendly, serve as a good substitute for expensive and harmful chemical fertilizers. The knowledge gained from this review can help us to understand the importance of microbes in agriculture and the ways to formulate these microbes as biofertilizers for sustainable crop production.

Microbes as Biofertilizers, a Potential Approach for Sustainable Crop Production

Industrialization, population burst, and changing lifestyles have resulted in the genesis of non-degradable pollutants languishing the environment and human health. Biological approaches using microorganisms are gaining importance as an eco-friendly and cost-effective substitute to mitigate the pollution load. Microorganisms can survive in a divergent environment and produce metabolites that can degrade and transform pollutants making it possible to revive contaminated sites naturally. Modern omics technologies like metagenomics, transcriptomics, proteomics, etc. have been used nowadays design strategies to study ecology and diversity of microorganisms and their application in environmental monitoring and bioremediation. The present article will focus on the omics techniques reportedly used in environmental monitoring to tackle the pollution load.

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Microbial Biodiversity and Bioremediation Assessment Through Omics Approaches

Plant growth-promoting rhizobacteria (PGPR) are diverse groups of plant-associated microorganisms, which can reduce the severity or incidence of disease during antagonism among bacteria and soil-borne pathogens, as well as by influencing a systemic resistance to elicit defense response in host plants. An amalgamation of various strains of PGPR has improved the efficacy by enhancing the systemic resistance opposed to various pathogens affecting the crop. Many PGPR used with seed treatment causes structural improvement of the cell wall and physiological/biochemical changes leading to the synthesis of proteins, peptides, and chemicals occupied in plant defense mechanisms. The major determinants of PGPR-mediated induced systemic resistance (ISR) are lipopolysaccharides, lipopeptides, siderophores, pyocyanin, antibiotics 2,4-diacetylphoroglucinol, the volatile 2,3-butanediol, N-alkylated benzylamine, and iron-regulated compounds. Many PGPR inoculants have been commercialized and these inoculants consequently aid in the improvement of crop growth yield and provide effective reinforcement to the crop from disease, whereas other inoculants are used as biofertilizers for native as well as crops growing at diverse extreme habitat and exhibit multifunctional plant growth-promoting attributes. A number of applications of PGPR formulation are needed to maintain the resistance levels in crop plants. Several microarray-based studies have been done to identify the genes, which are associated with PGPR-induced systemic resistance. Identification of these genes associated with ISR-mediating disease suppression and biochemical changes in the crop plant is one of the essential steps in understanding the disease resistance mechanisms in crops. Therefore, in this review, we discuss the PGPR-mediated innovative methods, focusing on the mode of action of compounds authorized that may be significant in the development contributing to enhance plant growth, disease resistance, and serve as an efficient bioinoculants for sustainable agriculture. The review also highlights current research progress in this field with a special emphasis on challenges, limitations, and their environmental and economic advantages.

PGPR-mediated induction of systemic resistance and physiochemical alterations in plants against the pathogens: Current perspectives.

COVID-19 is a disease caused by the novel coronavirus (SARS-CoV-2). Positive-sense ssRNA viruses are about 30 kb long. Coronaviruses have a broad spectrum of action and affect multiple organisms. The disease outbreak has been initiated in Wuhan, China, in December 2019. The disease has been originated from the wet animal market of Wuhan City, where a large number of peoples have come in contact with animals. It is known to infect the neurological, respiratory, enteric, and hepatic systems. SARSCoV-2 is highly infectious, and its outbreak is worldwide (national and international level) and becomes pandemic. Presently, the number of cases continues to rise at a global level, and it is clear that these viruses pose a significant threat to public health. Consequently, extensive treatments, vaccines, and drugs have been developed by researchers to control the transmission of infection. This led to the isolation of patients that were administered a variety of treatments. Special attention and guidelines have been given by various government organizations to protect or reduce transmission between children, healthcare providers, and old-aged peoples.

Updates of COVID-19

Solid Waste : Characterization, Assessment, Monitoring, and Remediation

Alternaria solani, a plant pathogenic fungus causes significant economical losses of potato crop. The disease is controlled primarily through some traditional methods and most commonly via the application of chemical fungicides. Fungicides treatment is not protected as chemicals pollute environment, effect health vulnerability in humans and when these harmful chemicals enter into the food chain become hazardous to all living entities. Recent efforts have focused on developing environmentally safe, long-lasting, and effective biocontrol methods for the management of plant diseases. Present research focus on screening of crude and partially purified leaf extract of Thevetia peruviana for the presence of antifungal efficacy against Alternarai solani. It was observed that 100% alcoholic crude and alcoholic fraction of partially purified extract showed maximum inhibitory activity which is due to the presence of different secondary metabolites, revealed by phytochemical screening. Active column fraction (possess best antifungal activity against Alternaria solani) was subjected to Gas Chromatography-Mass Spectrometry (GS-MS) analysis. On the basis of peaks matching of GC-MS chromatogram with available data base showed the presence of benzoic acid and oxo-benzoate in active fraction of Thevetia peruviana leaf extract which is already known chemical among the phytochemicals described for antimicrobial activity. Further research on development of herbal formulation from the same would be very helpful environment friendly approach to manage concern crop disease.

Antifungal efficacy of Thevetia peruviana leaf extract against Alternaria solani and characterization of novel inhibitory compounds by Gas Chromatography-Mass Spectrometry analysis.

Deepali Chittora

Papers

Cyanobacteria as a source of biofertilizers for sustainable agriculture.

Updates of COVID-19

Solid Waste : Characterization, Assessment, Monitoring, and Remediation

Antifungal efficacy of Thevetia peruviana leaf extract against Alternaria solani and characterization of novel inhibitory compounds by Gas Chromatography-Mass Spectrometry analysis.

Biocontrol Efficacy of Thevetia Peruviana Bioformulations Against Early Blight Disease of Potato