Response of drip irrigated Broccoli (Brassica oleracea var. italica) in different irrigation levels and frequencies at field level

Geometric increase in population coupled with rapid urbanization, industrialization and agricultural development are causing increased pressure on global water resources. Agriculture is the largest consumer of fresh water resources, thus the scope of enhancing water productivity in agriculture is taken to be the priority area of research. The right amount and frequency of irrigation is essential for optimum use of limited water resources for crop production as well as management. A field experiment with split plot design was carried out during November to February 2015-16 at PFDC (Precision Farming Development Centre), Water Technology Centre, IARI, New Delhi to study the effect of different irrigation levels and frequencies on Broccoli (Brassica oleracea var. italica) under drip irrigation. The experiment included three levels of irrigation frequencies: N1 (once every day), N2 (once every 2 days) and N3 (once every 3 days) with different irrigation levels of 100, 80 and 60 % of crop evapotranspiration (ETc). Results revealed that drip irrigation frequency significantly (p<0.05) affected the broccoli yield. The maximum yield (24.46±0.18 t/ha) was obtained with 80% of ETc with once in 2 days irrigation followed by 100% of ETc with once in 2 days. Lowest yield (16.53±0.1 t/ha) was obtained at 60% of ETc at once in 3 days irrigation. Overall, it was observed that irrigation on 80% of ETc with once in two days is an appropriate cycle for optimum yield of broccoli

An advance extended binomial GLMBoost ensemble method with synthetic minority over-sampling technique for handling imbalanced datasets

Classification is an important activity in a variety of domains. Class imbalance problem have reduced the performance of the traditional classification approaches. An imbalance problem arises when mismatched class distributions are discovered among the instances of class of classification datasets. An advance extended binomial GLMBoost (EBGLMBoost) coupled with synthetic minority over-sampling technique (SMOTE) technique is the proposed model in the study to manage imbalance issues. The SMOTE is used to solve the proposed model, ensuring that the target variable's distribution is balanced, whereas the GLMBoost ensemble techniques are built to deal with imbalanced datasets. For the entire experiment, twenty different datasets are used, and support vector machine (SVM), Nu-SVM, bagging, and AdaBoost classification algorithms are used to compare with the suggested method. The model's sensitivity, specificity, geometric mean (G-mean), precision, recall, and F-measure resulted in percentages for training and testing datasets are 99.37, 66.95, 80.81, 99.21, 99.37, 99.29 and 98.61, 54.78, 69.88, 98.77, 96.61, 98.68, respectively. With the help of the Wilcoxon test, it is determined that the proposed technique performed well on unbalanced data. Finally, the proposed solutions are capable of efficiently dealing with the problem of class imbalance

Post COVID-19 Symptoms: A Neglected Domain

Background: COVID -19 is the most important public health problem of recent time. Most people who have COVID-19 recovers completely within a few weeks but some people continue to have symptoms after initial recovery. Objective: To assess the prevalence of Post COVID symptoms, to assess requirement of treatment and to make recommendation for Post COVID care. Methods: Present cross sectional study was done among patients who recovered from COVID-19 in Meerut district. Mobile numbers of COVID patients were obtained from records, Total 100 randomly selected patients were contacted using google form and information regarding post covid symptoms in between 6 weeks to 12 weeks after recovery from COVID was obtained. Result: 87%patients developed one or more post covid symptoms. Weakness was reported to be most common problem (55%), followed by body ache (26%) and neuropsychiatric symptoms such as difficulty in concentration and insomnia (22%). Every fifth patient reported that symptoms persisted for more than 1 month. Though most of the respondents classified their symptoms as mild and moderate (52.5% and 37.9% respectively), 47% of the symptomatic patients have to take some treatment for these symptoms. Conclusion: Post COVID symptoms are common but usually less severe . Some form of treatment was required to deal with problem. Almost one in five patients reported that symptoms persisted for more than one month. The results highlight the need for post Covid care for COVID recovered patients

A Comprehensive Survey of Data Mining Techniques on Time Series Data for Rainfall Prediction

Time series data available in huge amounts can be used in decision-making. Such time series data can be converted into information to be used for forecasting. Various techniques are available for prediction and forecasting on the basis of time series data. Presently, the use of data mining techniques for this purpose is increasing day by day. In the present study, a comprehensive survey of data mining approaches and statistical techniques for rainfall prediction on time series data was conducted. A detailed comparison of different relevant techniques was also conducted and some plausible solutions are suggested for efficient time series data mining techniques for future algorithms.

HR Process Automation: A Bibliometric Analysis

Automation is interpreted as the replacement of manual operations by electronics and computer-controlled systems. Human resource management is an indispensable part of every firm be it the space of retail, healthcare, education or any other sector. Activities such as hiring new workers, training, or making sure that local labour laws are obeyed with HR processes and are a crucial part of every organisation. HR has typically been believed of as an extremely manual department procedure. Employees are accustomed to doing this manually and getting the job done themselves. But everything around the HR processes are changing rapidly. HR Automation is a tool for increasing the efficiency of an employment organisation by freeing employees from tedious repetitive tasks and allowing them to focus on more complex assignments such as decision-making and strategy creation. Automation is interpreted as the replacement of manual operations by electronics and computer-controlled systems. By automating regular and routine HR tasks, organisations may lead to significant savings and resources they expend on manual HR processing and preparation. The HR space is being invaded by automation, and any automation that can be implemented will be implemented very quickly. This article is written with the help of Scopus, Web of Science, Google Scholar and Crossref databases. This article will be useful for upcoming researchers, students and managers in the field of HRM across the world

Development of synbiotic weaning food supplemented with spirulina grown under precise/mild stress conditions

For alleviating child malnutrition, functional food from natural resources such as microalgae predominantly cyanobacteria came into existence as consumers today are more health conscious. No work of technological or scientific significance has been reported on standardized method for development of pearl millet weaning food supplemented with Spirulina maxima. Therefore, feasibility trials were done on the basis of sensory attributes analysis. Spirulina powder grown in optimized laboratory conditions was screened for its phytochemical constituents. The standardized product consisted of one part of pearl millet grounded for 5 min cooked with eight parts of water, 5% salt and 0.8% of cumin powder. Cooked weaning food mixed with 1% curd culture, 1.5% Spirulina powder and incubated for 12 h (fermentation). Standardized product consisting of this formulation scored 8.13, 7.93, 7.88, 7.94, 7.30, 8.14 for colour and appearance, flavour, consistency, mouthfeel, acidity and overall acceptability, respectively on 9 points hedonic scale

Amplified fragment length polymorphism of clinical and environmental Vibrio cholerae from a freshwater environment in a cholera-endemic area, India

<p>Abstract</p> <p>Background</p> <p>The region around Chandigarh in India has witnessed a resurgence of cholera. However, isolation of <it>V. cholerae </it>O1 from the environment is infrequent. Therefore, to study whether environmental nonO1-nonO139 isolates, which are native to the aquatic ecosystem, act as precursors for pathogenic O1 strains, their virulence potential and evolutionary relatedness was checked.</p> <p>Methods</p> <p><it>V. cholerae </it>was isolated from clinical cases of cholera and from water and plankton samples collected from freshwater bodies and cholera-affected areas. PCR analysis for the <it>ctxA, ctxB, tcpA, toxT </it>and <it>toxR </it>genes and AFLP with six primer combinations was performed on 52 isolates (13 clinical, 34 environmental and 5 reference strains).</p> <p>Results</p> <p>All clinical and 3 environmental isolates belonged to serogroup O1 and remaining 31 environmental <it>V. cholerae </it>were nonO1-nonO139. Serogroup O1 isolates were <it>ctxA, tcpA </it>(ElTor), <it>ctxB </it>(Classical), <it>toxR </it>and <it>toxT </it>positive. NonO1-nonO139 isolates possessed <it>toxR</it>, but lacked <it>ctxA </it>and <it>ctxB</it>; only one isolate was positive for <it>toxT </it>and <it>tcpA</it>. Using AFLP, 2.08% of the <it>V. cholerae </it>genome was interrogated. Dendrogram analysis showed one large heterogeneous clade (n = 41), with two compact and distinct subclades (1a and 1b), and six small mono-phyletic groups. Although <it>V. cholerae </it>O1 isolates formed a distinct compact subclade, they were not clonal. A clinical O1 strain clustered with the nonO1-nonO139 isolates; one strain exhibited 70% similarity to the Classical control strain, and all O1 strains possessed an ElTor variant-specific fragment identified with primer ECMT. Few nonO1-nonO139 isolates from widely separated geographical locations intermingled together. Three environmental O1 isolates exhibited similar profiles to clinical O1 isolates.</p> <p>Conclusion</p> <p>In a unique study from freshwater environs of a cholera-endemic area in India over a narrow time frame, environmental <it>V. cholerae </it>population was found to be highly heterogeneous, diverse and devoid of major virulence genes. O1 and nonO1-nonO139 isolates showed distinct lineages. Clinical isolates were not clonal but were closely related, indicating accumulation of genetic differences over a short time span. Though, environment plays an important role in the spread of cholera, the possibility of an origin of pathogenic O1 strains from environmental nonO1-nonO139 strains seems to be remote in our region.</p

Novel application of Nerium leaf and Image J software in drop collapse assay for rapid screening of biosurfactant producing microorganisms

484-492Biosurfactants are attractive molecules with varied applicationsmainly oil degradation, emulsification, bioremediation, therapeutics and conjugation of nanoparticles. The existing screening methods for biosurfactants are inappropriate and too tedious. Here, we have explored a novel approach with drop collapse assay wherein we replaced the microtiter well plate with the naturally hydrophobic Nerium (Nerium oleander L.) leaf. The stability of beaded drops on the leaf indicates negative phenomenon, and spreading of drop indicates positive phenomenon for surfactant property, as confirmed by the measuring drop diameter using Image J software. Fifty five bacterial cultures isolated from oil contaminated site were screened through this novel approach which revealed that the isolates DNM49 (6.75±0.29 mm), DNM50 (7.45±0.19 mm) and DNM51 (6.14±0.82 mm) were the best in terms of surface tension reduction, although thirty other isolates were also found to be positive. A gradation of activity in terms of surface tension reduction was also established based on drop diameter. The results demonstrated promising application of Nerium leaf with Image J software in drop collapse assay as an eco-friendly and cost-effective and technically authenticated alternative to the existing assays

In silico motif diversity analysis of the glycon preferentiality of plant secondary metabolic glycosyltransferases

Abstract Glycosyltransferase are the class of enzymes which specifically glycosylate various natural and artificial substrate aglycons into their glycosidic linked compounds with enhanced water solubility and transport. In several instances, glycosylation is the last step in the biosynthesis of a number of secondary plant products involving flavonoids, terpenoids, steroidal alkaloids, and saponin biosynthetic pathway. The conjugation reactions catalyzed by UGTs may therefore are critical in regulating the levels of several secondary metabolites including signaling and hormonal compounds. In this work we have analyzed genes from the databases for the presence of GT&apos;s in diverse plant families. Considerable degree of homology was seen in alignment of all available GT sequences in dicot plants as revealed by ClustalW2 and other phylogenetic tree constructing tools. Also, a highly conserved motif in their C-terminus, named the PSPG box (Plant secondary product glycosyl transferase ) was found in all the sequences through motif discovery tools e.g. MEME. The motif discovery tool identified two other distinct motifs in GT sequences, however interestingly P. patens and a putative GT sequence from A. thaliana was found to be deficient in motif 3 at N terminal of the sequence. A wide range of gene sequences were analyzed in a systematic manner to determine the structure, function and evolution of PSPG box motif found at the C-terminal