Browsing by Author "Saurav Singla"

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A Bayesian network study of water conflict between Punjab and Haryana
(DAV College, 2020) Saurav Singla; M.R. Duraisamy; P.G. Saravanan
Rivers are vital water resource for every State and conflicts around water sharing is a common issue. Water Conflict Management becomes important to study both scientific and policy making aspects. The conflict over the waters of Beas, Ravi and Sutlej began in 1966 when Haryana was carved out of Punjab and the former demanded its share of water. Despite numerous interventions the Sutlej Yamuna Link canal (SYL) remains incomplete and general stalemate prevails. Bayesian Networks (BNs) are data driven tools helping policy makers to predict the foreseeable outcome before taking any further step, for the similar purpose of predicting the type of resolution of water conflict a BN was estimated based on ICOW dataset. BN learnt, were then applied to Punjab scenario. The study shows that there is a greater chance of third-party involvement in military dispute between the stakeholders. There are high chances of occurring bilateral when conflict is of longer duration. Bilateral negotiations are successful in ending water conflicts with a bilateral agreement. If a bilateral is not possible then the challenger is likely to drop the claims. The study further shows that if a bilateral resolution has occurred then the river is of high value to the States. Bilateral negotiation is one of the most probable solutions towards a peaceful negotiation of SYL water sharing conflict. The study concludes that BN models are adequate for predicting the events in a water conflict. © 2020 DAV College. All rights reserved.
An assessment of serum oxidative stress and antioxidant parameters in patients undergoing treatment for cervical cancer
(Elsevier Inc., 2021) Anju Shrivastava; Surendra Pratap Mishra; Satyajit Pradhan; Sunil Choudhary; Saurav Singla; Kulsoom Zahra; Lalit Mohan Aggarwal
Objectives: Oxidative stress and antioxidants are involved in all aspects of cervical cancer. The present study evaluated serum levels of oxidative stress and antioxidant biomarkers in cervical cancer patients and healthy controls. Moreover, the effect of Concurrent chemoradiotherapy (CCRT) on these biomarkers and their association with treatment outcome was investigated. Design: This study included ninety-seven cervical cancer patients and thirty controls. Three oxidative stress parameters (8-hydroxy-2-deoxyguanosine, Protein Carbonyl, and Malondialdehyde) and four antioxidant parameters (Superoxide Dismutase, Catalase, Glutathione Peroxidase, and Total Antioxidant Status) were measured. The analysis was conducted using repeated measures ANOVA for comparing among the phases (before, during, and follow-up) of treatment. The control group was compared using the Dunnet test. Logistic regression analysis was also conducted between oxidative stress and antioxidant parameters to study their association. Results: Significant rises in oxidative damage markers were observed in cervical cancer patients of all stages, compared to controls. There was a further increase in oxidative stress markers during CCRT among complete responders. However, among non-responders, the oxidative stress biomarkers like Protein Carbonyl and Malondialdehyde were unaltered during CCRT. Simultaneously, there was a significant decrease in antioxidant parameters in cervical cancer patients of all stages compared to controls. During CCRT, antioxidant levels continuously depleted among complete responders. Nevertheless, in non-responders, antioxidant parameters like Superoxide Dismutase and Total Antioxidant Status were consistent. The oxidative stress markers and antioxidant parameters normalized among complete responders at six months follow up. While in non-responders, the normalization of these parameters was not observed. Conclusion: Our results indicate that increased oxidative stress and diminished antioxidants among patients were associated with carcinoma cervix. Induced oxidative stress and decreased antioxidant parameters during CCRT among the complete responders show the treatment's efficacy. Oxidant-antioxidant profile merits investigation as markers of diagnosis, treatment response, survival, and recurrence in extensive prospective studies. © 2021 Elsevier Inc.
Diagnostic and prognostic application of Raman spectroscopy in carcinoma cervix: A biomolecular approach
(Elsevier B.V., 2021) Anju Shrivastava; Lalit Mohan Aggarwal; Chilakapati Murali Krishna; Satyajit Pradhan; Surendra Pratap Mishra; Sunil Choudhary; Chandan Bhai Patel; Saurav Singla; Ashish; Ranjan Kumar Singh
Blood serum samples from 63 cervical cancer patients and 30 controls were collected at three different phases of the treatment (i.e. before, during, and at follow up). The spectra of serum samples from control as well as patients were classified into different groups using principal component analysis (PCA) and linear discriminant analysis (LDA) based on different phases of treatment using R software. The spectra of blood serum samples have shown the distinct changes and differences compared with each other in the profile of various biochemical parameters. The sensitivity (92.5%) and specificity (85%) were observed maximum between control and cervical cancer patients (before treatment). Between different phases of treatment, the sensitivity and specificity were less but, all accuracies of detection and classification reached above 50%. This method can be considered as a screening method for detection and treatment monitoring. © 2020
Evaluation of mustard genotypes [Brassica juncea (L.) Czern and Coss] for quantitative traits and character association of seed yield and yield components at sub Himalayan region of West Bengal (India)
(Horizon e-Publishing Group, 2023) Bijaya Sur; Sanghamitra Rout; Saurav Singla; Rupsanatan Mandal; Sahanob Nath; Bilin Maying; Supratim Sadhu; Moumita Chakraborty; Lakshmi Hijam; Manoj Kanti Debnath; Suvendu Kumar Roy
Brassica juncea is an important industrial and commercial oilseed crop grown primarily in India. This study aimed to assess 56 genotypes of Indian mustard to quantify genetic diversity, which aids the breeder in identifying genetically divergent parents to evaluate the proportional contributions of various components towards overall divergence. All the 56 Indian mustard genotypes were tested in RBD with three replications for 2 consecutive years i.e. 2016-17 and 2017-18 during the rabi season. Observations were recorded for 11 yield and its attributing traits. The findings revealed that height up to first branching, aphid count, penetration force and seed yield per plant had maximum PCV and GCV signifying that genetic factors have a greater impact on the inflow of these traits. Height up to first branching, secondary branches per plant, primary branches per plant, siliquae per plant, aphid count and 1000 seed weight had strong heritability combined with GA as % of mean. These indicate that the traits were controlled by additive gene action. Seed yield per plant was significantly correlated with penetration force and siliquae per plant. As a result, it's reasonable to predict that improving these traits by selection, could lead to significant yield gains. Four of the eleven PCs had eigen values greater than 1.0, accounting for 69.94% of the variance. PC I, which explained 30.31% of the overall variance. Mahalanobis D2 statistics revealed considerable genetic diversity among the genotypes. 56 genotypes were distributed into 7 clusters. This is anticipated that genotypes within a cluster are almost genetically related to one another. Cluster VII and II showed maximum inter-cluster divergence. From a breeding perspective, a divergence analysis revealed that genotypes like SKJM-05, RNWR-09-3, RW-351, B-85, DRMR-4001, RGN-386, TM52 276 and SKM-1313 can be selected as genetically divergent parents for hybridization to obtain desirable segregants. Copyright: © The Author(s).
Genotype × environment interaction and selection of maize (Zea mays L.) hybrids across moisture regimes
(Elsevier B.V., 2021) Ashok Singamsetti; J.P. Shahi; P.H. Zaidi; K. Seetharam; M.T. Vinayan; Munnesh Kumar; Saurav Singla; Kumari Shikha; Kartik Madankar
Genotype × environment (GE) interaction effect is one of the major challenges in identifying cultivars with stable performance across environments and years. Objective of the present study was to identify maize hybrids with high and stable yields under different soil moisture regimes such as drought, waterlogged and well-watered conditions. The trials were carried out in subsequent winter (Rabi) and summer-rainy (Kharif) seasons of 2017 and 2018 totaling seven test environments at the two different locations of India viz, Banaras Hindu University, Varanasi and CIMMYT, Hyderabad. After observing substantial and statistically significant GE interaction for studied traits, the phenotypic stability of maize hybrids was analyzed by AMMI, GGE biplot and multi-trait stability index (MTSI) methods. The study emphasized on the significance of AMMI and GGE biplots in deciphering the GE interactions based on grain yield data. Estimation of stability indices, WAASB (Weighted Average of Absolute Scores from the singular value decomposition of the matrix of BLUPs) for the GE interaction effects and WAASBY (a combination of WAASB and yield) scores for identification of the best suitable genotypes with high stability and maximum yield potential was highlighted. The investigation delineated the applicability of MTSI that computed based on the genotype-ideotype distance considering the multiple variables. The methods studied were concordant in the identification of the promising maize hybrids with high mean performance and greater phenotypic stability across the different soil moisture conditions. © 2021 Elsevier B.V.
Impact assessment of natural variations in different weather factors on the incidence of whitefly, Bemisia tabaci Genn. and yellow vein mosaic disease in Abelmoschus esculentus (L.) Moench
(Academic Press Inc., 2023) Radheshyam Ramakrishna Dhole; Rajendra Nath Singh; Rajendran Dhanapal; Saurav Singla; Govindaraju Ramkumar; Ranganathan Muthuusamy; Saleh H. Salmen; Sulaiman Ali Alharbi; Mathiyazhagan Narayanan; Indira Karuppusamy
Bemisia tabaci Gennadius, also renowned as the silver leaf whitefly, is among the most damaging polyphagous insect pests in many commercially important crops and commodities. A set of field experiments were conducted for three consecutive years i.e., 2018–2020, to investigate the role of variations in rainfall, temperature, and relative humidity on the abundance of B. tabaci in okra (Abelmoschus esculentus L. Moench). In the first experiment, the variety Arka Anamika was cultivated twice a year to analyse the incidence of B. tabaci concerning the prevailing weather factors and the overall pooled incidence recorded during the dry and wet season was 1.34 ± 0.51 to 20.03 ± 1.42 and 2.26 ± 1.08 to 18.3 ± 1.96, respectively. Similarly, it was observed that the highest number of B. tabaci catch (19.51 ± 1.64 whiteflies/3 leaves) was recorded in morning hours between 08:31 to 09:30 a.m. The Yellow Vein Mosaic Disease (YVMD) is a devastating disease of okra caused by begomovirus, for which B. tabaci acts as a vector. In another experiment, screening was conducted to check the relative susceptibility of three different varieties viz., Arka Anamika, Pusa Sawani, and Parbhani Kranti against B. tabaci (incidence) and YVMD ((Percent Disease Incidence (PDI), Disease Severity Index (DSI), and Area Under the Disease Progress Curve (AUDPC)). The recorded data was normalized by standard transformation and subjected to ANOVA for population dynamics and PDI. Pearson's rank correlation matrix and Principal Component Analysis (PCA) have been used to relate the influences of various weather conditions on distribution and abundance. SPSS and R software were used to create the regression model for predicting the population of B. tabaci. Late sown Pusa Sawani evolved as a highly susceptible variety in terms of B. tabaci (24.83 ± 6.79 adults/3leaves; mean ± SE; N = 10) as well as YVMD i.e., PDI (38.00 ± 4.95 infected plants/50plants), DSI (71.6–96.4% at 30 DAS) and AUDPC (mean β-value = 0.76; R2 = 0.96) while early sown Parbhani Kranti least susceptible to both. However, the variety Arka Anamika was observed as moderately susceptible to B. tabaci and its resultant disease. Moreover, environmental factors were predominantly responsible for regulating the population of insect pests in the field and hence its productivity like rainfall and relative humidity were negative while the temperature was positively correlated with B. tabaci (incidence) and YVMD (AUDPC). The findings are helpful for the farmers to choose need-based IPM strategies than timing-based, which would fit perfectly with the present agro-ecosystems in all ways. © 2023 Elsevier Inc.
Impact of climate change induced future rainfall variation on dynamics of arid-humid zone transition in the western province of India
(Academic Press, 2023) Kanhu Charan Panda; R.M. Singh; Vijay Kumar Singh; Saurav Singla; Pradosh Kumar Paramaguru
The transition of the Earth's climate from one zone to another is one of the major causes behind biodiversity loss, rural-urban migration, and increasing food crises. The rising rate of arid-humid zone transition due to climate change has been substantially visible in the last few decades. However, the precise quantification of the climate change-induced rainfall variation on the climate zone transition still remained a challenge. To solve the issue, the Representative Grid Location-Multivariate Adaptive Regression Spline (RGL-MARS) downscaling algorithm was coupled with the Koppen climate classification scheme to project future changes in various climate zones for the study area. It was observed that the performance of the model was better for the humid clusters compared to the arid clusters. It was noticed that, by the end of the 21st century, the arid region would increase marginally and the humid region would rise by 24.28–36.09% for the western province of India. In contrast, the area of the semi-arid and semi-humid regions would decline for the study area. It was observed that there would be an extensive conversion of semi-humid to humid zone in the peripheral region of the Arabian sea due to the strengthening of land-sea thermal contrast caused by climate change. Similarly, semi-arid to arid zone conversion would also increase due to the inflow of dry air from the Arabian region. The current research would be helpful for the researchers and policymakers to take appropriate measures to reduce the rate of climate zone transition, thereby developing the socioeconomic status of the rural and urban populations. © 2022 Elsevier Ltd
Impact of COVID-19 lockdown on prices of potato and onion in metropolitan cities of India
(Emerald Group Holdings Ltd., 2022) Kuldeep Rajpoot; Saurav Singla; Abhishek Singh; Shashi Shekhar
Purpose: This study focuses on accessing the impact of lockdown implemented to curb the pandemic of coronavirus disease 2019 (COVID-19) on prices of potato and onion crops using the time series analysis techniques. Design/methodology/approach: The present study uses secondary price series data for both crops. Along with the study of percent increase or decrease, the time series analysis techniques of autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroskedasticity (GARCH), as well as machine learning; neural network autoregressive (NNAR) models were used to model the prices. For the purpose of comparison, the data from past years were taken as the period of normalcy. The behaviour of the forecasts for the normal periods and during the pandemic based on respective datasets was compared. Findings: The results show that there was an unprecedented rise in prices during the months of lockdown. It could be attributed to the decline in arrivals due to several reasons like issues with transportation and labour availability. Also, towards the end of lockdown (May 2020), the prices seemed to decrease. Such a drop could be attributed to the relaxations in lockdown and reduced demand. The study also discusses that how some unique approaches like e-marketing, localized resource development for attaining self-sufficiency and developing transport chain, especially, for agriculture could help in such a situation of emergency. Research limitations/implications: A more extensive study could be conducted to mark the factors specifically that caused the increase in price. Originality/value: The study clearly marks that the prices of the crops increased more than expectations using time series methods. Also, it surveys the prevailing situation through available resources to link up the reasons behind it. © 2021, Emerald Publishing Limited.
Modelling price volatility in onion using wavelet based hybrid models
(The Society of Economics and Development, 2021) Saurav Singla; Ranjit Kumar Paul; Shashi Shekhar
The performance of wavelet-based hybrid models using different combinations of wavelet filters was compared to that of other conventional models to model volatility in the onion prices and arrivals at the Lasalgaon market of Maharashtra, which is known to be one of the largest markets in terms of arrivals. Monthly data of more than twenty-three years from 1996 onwards were taken into account. The results of hybrid models were compared to that of the ARIMA model. A normality test was conducted for both data series, and both of them were found to be non-normal. Therefore, a suitable nonparametric approach, namely wavelet decomposition of the data, was called for. For the price data, too, the wavelet-GARCH model with LA8 filter at five-level decomposition performed best for single value forecast, whereas the ARIMA performed well at expanded horizons. For the arrivals data, the Wavelet-GARCH model with LA8 filter at four level decomposition outperformed all models for single value forecasts. However, the wavelet-ANN model was able to perform better as the horizon expanded to twelve months. The study concluded that the wavelet hybrid models do pretty well for single value forecast, but as the horizon expands, the accuracy of the models decreases. ©2021 The Society of Economics and Development, except certain content provided by third parties.
Weather based prediction model for green leafhopper (GLH), Nephotettix virescens distant of rice in middle gangetic plains
(Malhotra Publishing House, 2021) Kamal Ravi Sharma; S.V.S. Raju; R.S. Meena; S. Ramesh Babu; Saurav Singla
The GLH Nephotettix virescens Distant occurrence began to increase during the 33rd SMW (3.0 GLH/15 sweeps) and peaked during the 40th SMW (19 GLH/15 sweeps). The GLH sweep net catches revealed maximum and significant positive correlation with sun shine hours of current week, and showed a significant negative correlation with evening relative humidity and wind speed of 2-lag week and current week. On the other hand, GLH catches revealed a positive correlation with maximum temperature and morning relative humidity of current, 1-lag as well as 2-lag week. Minimum temperature and rainfall of current, 1-lag, 2-lag week and current, 1-lag week, respectively, were negatively correlated with GLH catches. Tmax, Tmin, and SSH were found to be the most significant weather influences that affected GLH sweep net catches. With pest and weather data obtained during Kharif 2019, the model was validated (R2 = 0.92, RSME = 0.218, and MAE = 0.303). © 2021. MPH J. ent. All Rights Reserved.