Saurav Singla

Dr. Saurav Singla

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2021 in Field Crops Research
Verified
Journal Article
Closed access
ASAshok Singamsetti
Ashok Singamsetti
JSJ.P. Shahi
J.P. Shahi
PZP.H. Zaidi
P.H. Zaidi
KSK. Seetharam
K. Seetharam
MVM.T. Vinayan
M.T. Vinayan
KMKartik Madankar
Kartik Madankar

1 May 2021 in Free Radical Biology and Medicine
Verified
Journal Article
Closed access
ASAnju Shrivastava
Anju Shrivastava
SMSurendra Pratap Mishra
Surendra Pratap Mishra
SPSatyajit Pradhan
Satyajit Pradhan
SCSunil Choudhary
Sunil Choudhary
SSSaurav Singla
Saurav Singla
LALalit Mohan Aggarwal
Lalit Mohan Aggarwal

4 November 2022 in Journal of Environmental Management
Verified
Journal Article
Closed access
KPKanhu Charan Panda
Kanhu Charan Panda
RSR.M. Singh
R.M. Singh
VSVijay Singh
Vijay Singh
SSSaurav Singla
Saurav Singla
PPPradosh Kumar Paramaguru
Pradosh Kumar Paramaguru

1 April 2021 in Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
Verified
Journal Article
Closed access
ASAnju Shrivastava
Anju Shrivastava
LALalit Mohan Aggarwal
Lalit Mohan Aggarwal
MCMurali Krishna Chilakapati
Murali Krishna Chilakapati
SPSatyajit Pradhan
Satyajit Pradhan
SMSurendra Pratap Mishra
Surendra Pratap Mishra
RSRanjan Kumar Singh
Ranjan Kumar Singh

11 October 2021 in Journal of Agribusiness in Developing and Emerging Economies
Verified
Journal Article
Closed access
KRKuldeep Rajpoot
Kuldeep Rajpoot
SSSaurav Singla
Saurav Singla
ASAbhishek Singh
Abhishek Singh
SSShashi Shekhar
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.

29 December 2022 in Ecohydrology & Hydrobiology
Verified
Journal Article
Closed access
SKsaswat kumar Kar
saswat kumar Kar
SPSridhar Patra
Sridhar Patra
RSR.M. Singh
R.M. Singh
SMSANKAR MARIAPPAN
SANKAR MARIAPPAN
SKSuresh Kumar
Suresh Kumar
SSSaurav Singla
Saurav Singla