Browsing by Author "Pawan Kumar Singh"

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A new grey system approach to forecast closing price of Bitcoin, Bionic, Cardano, Dogecoin, Ethereum, XRP Cryptocurrencies
(Springer Science and Business Media B.V., 2023) Pawan Kumar Singh; Alok Kumar Pandey; S.C. Bose
The current study uses the grey forecasting model, EGM (1, 1, α, θ), a generalized form of the classical, even form of grey forecasting approach, to forecast the closing price of Bitcoin (BTC), Bionic (BNC), Cardano (ADA), Dogecoin (DOGE), Ethereum (ETH), XRP (XRP) of cryptocurrencies based on the data from September 19, 2021, to September 29, 2021. The forecast was generated for September 30, 2021–October 07, 2021. Study revealed that the generalized model’s forecast accuracy is generally better than that of the classical model. The results are also compared with Linear Regression and Exponential Regression. This superiority results from using real past data in long-term forecasting, while the iterative forecasting approach uses the predicted values. Since forecast values are important in guiding future investments, decision-makers must consider various forecasting methods and select the best forecast performance after analyzing the comparative performance. © 2022, The Author(s), under exclusive licence to Springer Nature B.V.
A SWOT analysis of groundnut farm households: Evidence from Mirzapur district in India
(Agricultural Academy, Bulgaria, 2021) Mosab I. Tabash; Pawan Kumar Singh; Rajiv Kumar Bhatt; Alok Kumar Pandey
In this study, SWOT analysis has been used to understand the safety precautions, cost-benefit measures, farmers’ skill, and few eco-friendly indicators. Generally, socio-economic characteristics of an agriculture farm community illustrate pro-duction, investment, educational status, farmers’ skill, their lifestyle, and the overall development scenario and prospects. To understand the status of these indicators a cross-sectional study was conducted in the Sikhar block of Mirzapur District, Uttar Pradesh, India. Data was collected through face to face interviews with the help of a pre-structured schedule. This work has found farmers’ awareness and application of herbicides are the major strengths in solving existing issues. Weaknesses include lack of latest information, skill in farms households, and inconsistencies in the application of a divergent range and scientific suggestions. Opportunities include alignment with farmers using strategies and existing tools with the application of herbicides as cost-effective and also helpful in reducing irrigation requirements. Threats consider that the application of herbicides to remove unwanted plants is one of the best and more effective but it should be applied in judicial form and farm households should have proper training and scientific recommendations about its application procedure. The present study will help in making strategies for farm households to improving decision-making to solve major issues, but also widely interpreting and communicating to select cost-effective methods. Policymakers should also be careful about weaknesses and it can be mini-mized by facilitating with proper infrastructure, awareness campaigns, interdisciplinary research, and institutional support to farm households. © 2021, Agricultural Academy, Bulgaria. All rights reserved.
Advancements in the physiological and biochemical characterization of the cyanobionts from the aquatic pteridophyte azolla
(Nova Science Publishers, Inc., 2017) Ravindra Kumar Yadav; Gerard Abraham; Keshawanad Tripathi; Pawan Kumar Singh; Pramod Wasudeo Ramteke
The Azolla- Anabaena system is important agronomically due to its capacity to fix atmospheric nitrogen. In addition to the use as biofertilizer the system has multifaceted uses as green manure, bioremediator, cattle and poultry feed etc. The nitrogen fixing capacity of the system is due to the presence of a symbiotic cyanobacterium Anabaena azollae which occurs in the dorsal leaf cavities of the host Azolla plant. This symbiosis is referred to as perpetual symbiosis due to the tight coupling between the cyanobiont and host which is different from other cyanobionts reported so far. There are many similarities as well as dissimilarities between the cyanobiont and free living cyanobacteria. Despite advancements in Azolla biology, the interaction between the host and its cyanobiont has not been elucidated in considerable detail. This has been attributed to the difficulties encountered in the isolation as well as culturing of the cyanobionts. In spite of these constraints we still have some leads on its physiological and biochemical aspects of the cyanobionts. Characterization of the cyanobiont is therefore important to further understand its interaction with the host and advancement in molecular biology tools and protocols may help to better understand the intricacies of the complex system. This may pave ways for the manipulation of the symbiosis to enhance the agricultural utility of the system. Therefore the present article highlights some of the important developments in the characterization of the cyanobiont associated with Azolla. © 2017 by Nova Science Publishers, Inc. All rights reserved.
Agrochemicals influencing nitrogenase, biomass of N2-fixing cyanobacteria and yield of rice in wetland cultivation
(Elsevier Ltd, 2017) Nalinaxya Prasad Dash; Ajay Kumar; Manish Singh Kaushik; Gerard Abraham; Pawan Kumar Singh
Cyanobacteria maintain soil fertility by performing N2-fixation and act as a key biocatalyst in nitrogen cycle. Chemical N-fertilizers and pesticides as agrochemicals are intensively being used in rice farming to boost rice production, this work deals with the first hand information on their influence on native N2-fixing cyanobacteria, which play an important role in maintaining soil health. A field study was conducted for three consecutive seasons in water logged rice field to observe the influence of agrochemicals, urea, benthiocarb and carbofuran in isolation and in combinations on biomass, acetylene reduction activity (ARA) and N-yield of native cyanobacteria as well as, on growth and yield of rice. The ARA and N-yield followed almost same trend. It is discernible that both urea and benthiocarb had deleterious effects whereas, carbofuran was promoting effects on cyanobacterial growth, ARA and N-yield. The combination of all the three above agrochemicals was found inhibitory, but inhibition was comparatively less than that of urea or benthiocarb in isolation or urea plus benthiocarb treatments. It is concluded that the combination of agrochemicals was toxic, in comparison to the control, but was better than application of urea N or benthiocarb alone or with their combinations. It was recorded that along with rice straw and gain yields, panicle numbers were the maximum at the combination with treatments of benthiocarb+carbofuran. Adverse effects of used agrochemicals on cyanobacteria in wetland rice cultivation could be avoided by a prudent use of chemical N-fertilizers and pesticide(s) in combination. © 2016
Azolla (Azolla microphylla) Supplementation Improves Nutrient Utilization in Lactating Murrah buffaloes
(Department of Science and Technology, 2022) Vishal Mudgal; Pranita Jaiswal; Gerard Abraham; Yudhvir Singh; Pawan Kumar Singh; Satbir Singh Dahiya
Balanced feeding of dairy animals is a costly affair in developing countries due to a lack of sufficient resources. A feeding cum digestion trial was conducted to evaluate the effect of dried green Azolla (Azolla microphylla) incorporation in lactating Murrah buffalo’s diet. Multiparous Murrah buffaloes (n = 10) with an average of 30 d in milk and yielding 11.29 kg/d were distributed randomly into two equal groups. The control group of buffaloes was fed a concentrated mixture prepared with commonly available feed ingredients – including maize grain, wheat bran, cottonseed cake, groundnut cake, mustard cake, mineral mixture, and salt – whereas the concentrate mixture of the treatment group was prepared, including 10% of the dried Azolla, by keeping both the concentrate mixtures iso-nitrogenous and iso-caloric. After 3 wk of preliminary feeding, a digestion trial was conducted for the assessment of nutrient utilization in two groups. Results indicated a positive response on the digestibility of dry matter (P < 0.05), organic matter (P < 0.05), neutral detergent fiber (P = 0.01), and acid detergent fiber (P = 0.015), whereas the digestibility of crude protein and ether extract remained unaffected (P > 0.05). Improvement in the digestibility of different nutrients without influencing the intake of nutrients indicated the importance of dried Azolla in the ration of lactating Murrah buffaloes. © 2022, Department of Science and Technology. All rights reserved.
Biotic stress management in rice (Oryza sativa L.) through conventional and molecular approaches
(Springer Singapore, 2020) Prakash Singh; Ram Lakhan Verma; Ravi S. Singh; Ravi P. Singh; H.B. Singh; Pandurang Arsode; Manish Kumar; Pawan Kumar Singh
The rice (Oryza sativa L.) productivity is often adversely disturbed by several abiotic and biotic stresses such as drought, submergence, fungal, bacterial, and nematode oriented biotic diseases and pest like brown plant hopper (BPH) and stem borer (SB). The major biotic stresses such as bacterial leaf blight (BLB), sheath blight (ShB), blast, brown spot (BS), false smut (FS), brown plant hopper (BPH), yellow stem borer (YSB), and gall midge (GM) play crucial roles in decreasing the productivity and quality of rice grains. Among the several breeding procedures and various control measures available for mitigating the biotic stresses/factors, the host plant resistance is most effective, economic and eco-friendly which is basically developed by traditional breeding approaches. The related species of rice and wild sources are important for identification of many resistance genes/QTLs, which are successfully introgressed or deployed or pyramided in numerous breeding lines through resistance breeding program and various molecular approaches. In this chapter, an inclusive valuation of the conventional and molecular approaches for mitigating the biotic stresses in rice by imparting major resistance sources has been presented. © Springer Nature Singapore Pte Ltd. 2020. All rights reserved.
Comparison of ARIMA, SutteARIMA, and Holt-Winters, and NNAR Models to Predict Food Grain in India
(MDPI, 2023) Ansari Saleh Ahmar; Pawan Kumar Singh; R. Ruliana; Alok Kumar Pandey; Stuti Gupta
The agriculture sector plays an essential function within the Indian economic system. Food-grains provide almost all the calories and proteins. This paper aims to compare ARIMA, SutteARIMA, Holt-Winters, and NNAR models to recommend an effective model to predict foodgrains production in India. The execution of the SutteARIMA predictive model used in this analysis was compared with the established ARIMA, Neural Network Auto-Regressive (NNAR), and Holt-Winters models, which have been widely applied for time series prediction. The findings of this study reveal that both the SutteARIMA model and the Holt-Winters model performed well with real-life problems and can effectively and profitably be engaged for food grain forecasting in India. The food grain forecasting approach with the SutteARIMA model indicated superior performance over the ARIMA, Holt-Winters, and NNAR models. Indeed, the actual and predicted values of the SutteARIMA and Holt-Winters forecasting models are quite close to predicting foodgrains production in India. This has been verified by MAPE and MSE values that are relatively low with the SutteARIMA model. Therefore, India’s SutteARIMA model was used to predict foodgrains production from 2021 to 2025. The forecasted amount of respective crops are as follows (in lakh tonnes) 1140.14 (wheat), 1232.27 (rice), 466.46 (coarse), 259.95 (pulses), and a total 3069.80 (foodgrains) by 2025. © 2023 by the authors. Licensee MDPI, Basel, Switzerland.
COVID-19 pandemic and transmission factors: An empirical investigation of different countries
(John Wiley and Sons Ltd, 2021) Pawan Kumar Singh; Ravi Kiran; Rajiv Kumar Bhatt; Mosab I. Tabash; Alok Kumar Pandey; Anushka Chouhan
The present work evaluates the impact of age, population density, total population, rural population, annual average temperature, basic sanitation facilities, and diabetes prevalence on the transmission of COVID-19. This research is an effort to identify the major predictors that have a significant impact on the number of COVID-19 cases per million population for 83 countries. The findings highlight that a population with a greater share of old people (aged above 65) shows a higher number of COVID-19 positive cases and a population with a lower median age has fewer cases. This can be explained in terms of higher co-morbidities and the lower general immunity in the older age group. The analysis restates the widely seen results that a higher median age and greater prevalence of co-morbidities leads to higher cases per million and lesser population density and interpersonal contact helps in containing the spread of the virus. The study finds foundation in the assertion that a higher temperature might lower the number of cases, or that temperature in general can affect the infectivity. The study suggests that better access to sanitation is a certain measure to contain the spread of the virus. The outcome of this study will be helpful in ascertaining the impact of these indicators in this pandemic, and help in policy formation and decision-making strategies to fight against it. © 2021 John Wiley & Sons, Ltd
Cyanobacterial (unicellular and heterocystous) biofertilization to wetland rice influenced by nitrogenous agrochemical
(Springer Netherlands, 2016) N.P. Dash; Ajay Kumar; Manish Singh Kaushik; Pawan Kumar Singh
Comparative growth and N2-fixation of cyanobacteria, namely Aphanothece sp. (unicellular) and Gloeotrichia sp. (heterocystous, filamentous), were studied after their inoculation to rice crop in the absence and presence of urea nitrogen fertilizer. In the absence of N-fertilizer application (control), inoculation of both cyanobacterial species showed significant increase in growth and acetylene reduction activity (ARA), but gradual reduction in these parameters was observed at 30 and 60 kg N ha−1 of urea application. In inoculation of Gloeotrichia sp. at control, 30 and 60 kg N ha−1 increased grain yield significantly over uninoculated control in both wet and dry seasons, but grain yield with Aphanothece sp. inoculation was statistically similar to the control at N levels during both seasons. The inoculation study showed that heterocystous cyanobacteria contributed better than unicellular ones, and application of N-fertilizer adversely affected both growth and N2-fixation of native as well of inoculated cyanobacteria. © 2016, Springer Science+Business Media Dordrecht.
Cyanobacterial bioactive molecules - An overview of their toxic properties
(2008) Pranita Jaiswal; Pawan Kumar Singh; Radha Prasanna
Allelopathic interactions involving cyanobacteria are being increasingly explored for the pharmaceutical and environmental significance of the bioactive molecules. Among the toxic compounds produced by cyanobacteria, the biosynthetic pathways, regulatory mechanisms, and genes involved are well understood, in relation to biotoxins, whereas the cytotoxins are less investigated. A range of laboratory methods have been developed to detect and identify biotoxins in water as well as the causal organisms; these methods vary greatly in their degree of sophistication and the information they provide. Direct molecular probes are also available to detect and (or) differentiate toxic and nontoxic species from environmental samples. This review collates the information available on the diverse types of toxic bioactive molecules produced by cyanobacteria and provides pointers for effective exploitation of these biologically and industrially significant prokaryotes. © 2008 NRC.
Discerning Genes to Deliver Varieties: Enhancing Vegetative- and Reproductive-Stage Flooding Tolerance in Rice
(Elsevier B.V., 2025) Sanchika Snehi; K. T. Ravi Kiran; Sanket R. Rathi; Sameer Upadhyay; Suneetha Kota; Satish Kumar Sanwal; B. M. Lokeshkumar; Arun Balasubramaniam; Nitish Ranjan Prakash; Pawan Kumar Singh
Flooding in rice fields, especially in coastal regions and low-lying river basins, causes significant devastation to crops. Rice is highly susceptible to prolonged flooding, with a drastic decline in yields if inundation persists for more than 7 d, especially during the reproductive stage. Although the SUB1 QTL, which confers tolerance to complete submergence during the vegetative stage, has been incorporated into breeding programs, the development of alternative sources is crucial. These alternatives would broaden the genetic base, mitigate the influence of the genomic background, and extend the efficacy of SUB1 QTL to withstand longer submergence periods (up to approximately 21 d). Contemporary breeding strategies predominantly target submergence stress at the vegetative stage. However, stagnant flooding (partial submergence of vegetative parts) during the reproductive phase inflicts severe damage on the rice crop, leading to reduced yields, heightened susceptibility to pests and diseases, lodging, and inferior grain quality. The ability to tolerate stagnant flooding can be ascribed to several adaptive traits: accelerated aerenchyma formation, efficient underwater photosynthesis, reduced radial oxygen loss in submerged tissues, reinforced culms, enhanced reactive oxygen species scavenging within cells, dehydration tolerance post-flooding, and resistance to pests and diseases. A thorough investigation of the genetics underlying these traits, coupled with the integration of key alleles into elite genetic backgrounds, can significantly enhance food and income security in flood-prone rice-growing regions, particularly in coastal high-rainfall areas and low-lying river basins. This review aims to delineate an innovative breeding strategy that employs genomic, phenomic, and traditional breeding methodologies to develop rice varieties resilient to various dimensions of flooding stress at both the vegetative and reproductive stages. © 2025 China National Rice Research Institute
Dissecting genomic regions and underlying sheath blight resistance traits in rice (Oryza sativa L.) using a genome-wide association study
(John Wiley and Sons Inc, 2023) R. Naveenkumar; Annamalai Anandan; Seenichamy Rathinam Prabhukarthikeyan; Anumalla Mahender; Ganesan Sangeetha; Shyam Saran Vaish; Pawan Kumar Singh; Waseem Hussain; Jauhar Ali
The productivity of rice is greatly affected by the infection of the plant pathogenic fungus Rhizoctonia solani, which causes a significant grain yield reduction globally. There exist a limited number of rice accessions that are available to develop sheath blight resistance (ShB). Our objective was to identify a good source of the ShB resistance, understand the heritability, and trait interactions, and identify the genomic regions for ShB resistance traits by genome-wide association studies (GWAS). In the present study, a set of 330 traditional landraces and improved rice varieties were evaluated for ShB resistance and created a core panel of 192 accessions used in the GWAS. This panel provides a more considerable amount of genetic variance and found a significant phenotypic variation among the panel of rice accessions for all the agro-morphological and disease-resistance traits over the seasons. The infection rate of ShB and disease reaction were calculated as percent disease index (PDI) and area under the disease progress curve (AUDPC). The correlation analysis showed a significant positive association between PDIs and AUPDC and a negative association between PDI and plant height, flag leaf length, and grain yield. The panel was genotyped with 133 SSR microsatellite markers, resulting in a genome coverage of 314.83 Mb, and the average distance between markers is 2.53 Mb. By employing GLM and MLM (Q + K) models, 30 marker–trait associations (MTAs) were identified with targeted traits over the seasons. Among these QTLs, eight were found to be novel and located on 2, 4, 8, 10, and 12 chromosomes, which explained the phenotypic variation ranging from 5% to 15%. With the GWAS approach, six candidate genes were identified. Os05t0566400, Os08t0155900, and Os09t0567300 were found to be associated with defense mechanisms against ShB. These findings provided insights into the novel donors of IC283139, IC 277248, Sivappuchithirai Kar, and Bowalia. The promising genomic regions on 10 of 12 chromosomes associated with ShB would be useful in developing rice varieties with durable disease resistance. © 2023 The Authors. Plant Direct published by American Society of Plant Biologists and the Society for Experimental Biology and John Wiley & Sons Ltd.
Estimation of reservoir properties using pre-stack seismic inversion and neural network in mature oil field, Upper Assam basin, India
(Elsevier B.V., 2024) Pawan Kumar Singh; Uma Shankar
The mature oil fields require comprehensive characterization for enhanced hydrocarbon production, and subsequently demands estimation of reservoir properties. The key properties viz. volume of clay, effective-porosity, hydrocarbon-saturation has been evaluated for an aging Oligocene reservoir of Upper Assam basin, located in northeastern India from seismic and well log data. Elastic properties (acoustic and shear impedance) and density are derived from pre-stack inversion of 3D seismic data. These elastic properties are analyzed for their sensitivity for discrimination of lithology and fluid-content, and many derived attributes are computed from elastic properties. These attributes are assessed for their predictability to predict the target reservoir properties using multi-attribute analysis. For each of the target property neural network is trained with the most predictable attributes, and multi-dimensional, non-linear neural network models are created using multilayered feed forward neural network (MLFN), followed by Probabilistic neural network (PNN). The specific neural network models for each target property are employed for quantitative estimate of volume of clay, effective-porosity, hydrocarbon-saturation in inter-well regions. The estimated properties leverage the identification of untapped oil reserves and provide promising opportunity for enhanced production through drilling of infill wells. © 2024 Elsevier B.V.
Evaluating the potential of N. calcicola and its bicarbonate resistant mutant as bioameleorating agents for 'usar' soil
(2010) Pranita Jaiswal; Ajai Kumar Kashyap; Radha Prasanna; Pawan Kumar Singh
The potential of Nostoc calcicola and its bicarbonate resistant mutant as bioameleorating agent was investigated, using laboratory simulation experiments, in terms of their growth potential, glutamine synthetase (GS) activity, heterocyst frequency and effect on pH of soil. Nostoc calcicola, exhibited a tendency to lower the pH of 'usar' soil significantly and showed better growth and pigment content at 20% soil extract as compared to basal medium. The bicarbonate resistant mutant (HCO3-R) exhibited a better ability to grow at higher percentage of soil extract (60%), besides bringing about a more significant change in soil pH as compared to wild type. The heterocyst frequency was much higher in the mutant strain, which was not significantly affected by growth in various concentrations of soil extract. The mutant strain holds promise as a potential bioameliorant for 'usar' soil after further evaluation of its reclamative properties at field level. © 2010 Association of Microbiologists of India.
Field evaluations of agrochemical toxicity to cyanobacteria in rice field ecosystem: a review
(Springer Netherlands, 2019) Manish Singh Kaushik; Ajay Kumar; Gerard Abraham; Nalinaxya Prasad Dash; Pawan Kumar Singh
The adverse effects of chemical nitrogen fertilizers affecting soil fertility, water pollution and native microorganisms, particularly cyanobacteria, in wetland rice cultivation have drawn global attention towards the use of alternative sources like N 2 -fixing cyanobacteria as a biofertilizer for sustainable rice farming. Although chemical nitrogen fertilizers are extensively used for obtaining higher rice yield, they are likely to have a deleterious effect on the growth and N 2 -fixation of diazotrophs, including cyanobacteria. In addition, biocides (herbicides and insecticides) are widely being used in rice cultivation for optimizing crop yield, but these chemicals also affects non-target organisms adversely. There are several reports indicating impacts of these agrochemicals on cyanobacteria, but most such studies were carried out under laboratory conditions. This article reviews information from different field evaluations on the impact of agrochemicals on cyanobacteria along with rice crop in wetland rice field ecosystem. © 2018, Springer Nature B.V.
Forecasting global plastic production and microplastic emission using advanced optimised discrete grey model
(2023) Subhra Rajat Balabantaray; Pawan Kumar Singh; Alok Kumar Pandey; Bhartendu Kumar Chaturvedi; Aditya Kumar Sharma
Plastic pollution has become a prominent and pressing environmental concern within the realm of pollution. In recent times, microplastics have entered our ecosystem, especially in freshwater. In the contemporary global landscape, there exists a mounting apprehension surrounding the manifold environmental and public health issues that have emerged as a result of the substantial accumulation of microplastics. The objective of the current study is to employ an enhanced grey prediction model in order to forecast global plastic production and microplastic emissions. This study compared the accuracy level of the four grey prediction models, namely, EGM (1,1, α, θ), DGM (1,1), EGM (1,1), and DGM (1,1, α) models, to evaluate the accuracy levels. As per the estimation of the study, DGM (1,1, α) was found to be more suitable with higher accuracy levels to predict microplastic emission. The EGM (1,1, α, θ) model has slightly better accuracy than the DGM (1,1, α) model in predicting global plastic production. Various accuracy measurement tools (MAPE and RMSE) were used to determine the model's efficiency. There has been a gradual growth in both plastic production and microplastic emission. The current study using the DGM (1,1, α) model predicted that microplastic emission would be 1,084,018 by 2030. The present study aims to provide valuable insights for policymakers in formulating effective strategies to address the complex issues arising from the release of microplastics into the environment and the continuous production of plastic materials. © 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Forecasting of non-renewable and renewable energy production in India using optimized discrete grey model
(Springer Science and Business Media Deutschland GmbH, 2023) Alok Kumar Pandey; Pawan Kumar Singh; Muhammad Nawaz; Amrendra Kumar Kushwaha
Renewable energy delivers reliable power supplies and fuel diversification, enhancing energy security and lowering fuel spill risk. Renewable energy also helps conserve the nation’s natural resources. Solar and other renewable energy sources have become increasingly prominent in recent years. India has achieved the 20 GW capacity solar energy production target before 2022. It is presently producing the lowest-cost solar power at the global level. Thermal energy has dominated the energy market. Countries have decided on energy generation from renewable sources and adopting green energy. This study forecasted non-renewable and renewable energy from multiple sources (hydropower, solar, wind and bioenergy) using grey forecasting model DGM (1,1,α). The comparative analyses with the classical models DGM (1,1) and EGM (1,1) revealed the superiority of the DGM (1,1,α). We also used CAGR for 2009–2019 to compare the actual and predicted data growth rate. The results show that non-renewable and renewable energy production is expected to increase. However, renewable energy generation wind sources continue to increase faster than hydropower, solar and bioenergy. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Genetic diversity of sweet corn inbreds using agro-morphological traits and microsatellite markers
(Springer Verlag, 2018) Anima Mahato; Jai Prakash Shahi; Pawan Kumar Singh; Monu Kumar
Assessment of genetic diversity is a pre-requisite to broaden the genetic background of cultivated base of sweet corn, an endosperm mutant of field corn that alters starch biosynthesis pathway in endosperm. In the current investigation, genetic divergence among 39 inbred lines was assessed on the basis of 14 agro-morphological traits, two quality parameters and 63 microsatellite markers, selected on the basis of their association with QTLs affecting kernel quality. The cluster analysis based on unweighted pair-group method using arithmetic averages for agro-morphological and quality traits grouped the 39 inbreds into three clusters with 5, 14 and 20 genotypes, respectively. The unweighted neighbor-joining method for microsatellite markers also categorized the inbred lines into three major clusters grouping 10, 9 and 20 genotypes in cluster I, II and III, respectively. The two cluster distribution patterns showed approximately 36 percent similarity. The assay of 30 microsatellite repeats identified 82 alleles with allele size ranging from 80 to 400 bp. The major allele frequency and PIC value of the markers ranged from 0.42 to 0.79 and 0.27 to 0.63, respectively, which suggested the presence of high amount of polymorphism among the inbreds. The average heterozygosity was recorded to be 0.19 which signifies proper maintenance of inbred population. Principle co-ordinate analysis also depicted diverse nature of inbred lines and agreed well with the previously determined clustering pattern. This study has identified several inbreds, having good yield and high sugar content which will not only enhance the genetic background of sweet corn germplasm but will also lead to development of high-yielding hybrids with improved quality. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
Heterologous expression and characterization of ToxA1 haplotype from India and its interaction with Tsn1 for spot blotch susceptibility in spring wheat
(Springer Science and Business Media B.V., 2023) Ranjan Kumar Chaubey; Dharamsheela Thakur; Sudhir Navathe; Sandeep Sharma; Vinod Kumar Mishra; Pawan Kumar Singh; Ramesh Chand
Background: ToxA, a necrotrophic effector protein, is present in the genome of fungal species like Parastagnospora nodorum, Pyrenophora tritici-repentis and Bipolaris sorokiniana. Tsn1 is the sensitivity gene in the host whose presence indicates more susceptibility to ToxA carrying pathogen, and ToxA-Tsn1 interaction follows an inverse gene-for-gene relationship. Methods and results: The present study involved cloning and expressing the ToxA1 haplotype from B. sorokiniana. It was found that the amplicon exhibited an expected product size of 471 bp. Sequence analysis of the ToxA1 nucleotide sequence revealed the highest identity, 99.79%, with P. tritici-repentis. The protein expression analysis showed peak expression at 16.5 kDa. Phylogenetic analysis of the ToxA1 sequence from all the Bipolaris isolates formed an independent clade along with P. tritici-repentis and diverged from P. nodorum. ToxA-Tsn1 interaction was studied in 18 wheat genotypes (11 Tsn1 and 7 tsn1) at both seedling and adult stages, validating the inverse gene-for-gene relationship, as the toxin activity was highest in the K68 genotype (Tsn1) and lowest in WAMI280 (tsn1). Conclusion: The study indicates that the haplotype ToxA1 is prevailing in the Indian population of B. sorokiniana. It would be desirable for wheat breeders to select genotypes with tsn1 locus for making wheat resistant to spot blotch. © 2023, The Author(s), under exclusive licence to Springer Nature B.V.
Identification of bacterial leaf blight resistance genes in wild rice of eastern India
(Turkiye Klinikleri Journal of Medical Sciences, 2015) Anil Kumar Singh; Ekta Dharmraj; Rohini Nayak; Pawan Kumar Singh; Nagendra Kumar Singh
An experiment was conducted during the 2013 monsoon season to screen 35 wild rice accessions against the BX043 strain of Xanthomonas oryzae pv. oryzae and identify the presence of bacterial blight resistance genes Xa21, xa13, xa5, Xa4, and Xa2. Among the accessions the area under the disease progress curve ranged from 174.88 (NKSWR-65) to 680.54 (NKSWR-34) compared with resistant controls RP bio-226 (93.92), CRMAS 2231-37 (097.28), CRMAS 2232-71 (098.58), and Tetep (178.62) and susceptible control PB-1 (1065.56). On the basis of disease severity 11 accessions showed moderate resistance, 21 were moderately susceptible, and 3 accessions showed susceptible response to the BX043 strain of Xanthomonas oryzae pv. oryzae, while none of the accessions were found to be resistant. The genetic frequency of the 5 resistance genes varied from 00.00% to 45.71%. The accession NKSWR-25 harbored 3 resistance genes, xa5, Xa4, and Xa2, while accessions NKSWR-16, NKSWR-32, NKSWR-36, NKSWR-41, NKSWR-42, NKSWR-53, NKSWR-64, NKSWR-97, and NKSWR-99 each possessed 2 resistance genes of those 3 (xa5, Xa4, and Xa2). Therefore, these accessions could be used for the transfer of specific bacterial leaf blight resistance genes into well-adapted high-yielding rice cultivars. © TÜBİTAK.