COVID-19 and prices of pulses in Major markets of India: Impact of nationwide lockdown

Paul, Ranjit Kumar; Yeasin, Md

doi:10.1371/journal.pone.0272999

Cited by 10 publications

(5 citation statements)

References 27 publications

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“…Many research compares prediction model usage, assumptions, and limits. According to research, simpler models perform better for short-term forecasting [ 15 ]. Madhya Pradesh is anticipated to produce the most pulses in India by the year 2030.…”

Section: Discussionmentioning

confidence: 99%

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An Overview of Pulses Production in India: Retrospect and Prospects of the Future Food with an Application of Hybrid Models

Mishra

Khatib

Lal

et al. 2023

Natl. Acad. Sci. Lett.

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Forecasts are valuable to countries to make informed business decisions and develop data-driven strategies. The production of pulses is an integral part of agricultural diversification initiatives because it offers promising economic opportunities to reduce rural poverty and unemployment in developing countries. Pulses are the cheapest source of protein needed for human health. India's pulses production guidelines must be based on accurate and best forecast models. Comparing classical statistical and machine learning models based on different scientific data series is the subject of high-level research today. This study focused on the forecasting behaviour of pulses production for India, Karnataka, Madhya Pradesh, Maharashtra, Rajasthan and Uttar Pradesh. The data series was split into a training dataset (1950–2014) and a testing dataset (2015–2019) for model building and validation purposes, respectively. ARIMA, NNAR and hybrid models were used and compared on training and validation datasets based on goodness of fit (RMSE, MAE and MASE). This research demonstrates that due to the diverse agricultural conditions across different provinces in India, there is no single model that can accurately predict pulse production in all regions. This study’s highest accuracy model is ARIMA. ARIMA outperforms NNAR, a machine learning model. Pulse production in India, Rajasthan, and Madhya Pradesh will expand by 26.11%, 12.62%, and 0.51% from 2020 to 2030, whereas it would decline by − 6.5%, − 6.21%, and − 6.76 per cent in Karnataka, Maharashtra, and Uttar Pradesh, respectively. The current forecast results could allow policymakers to develop more aggressive food security and sustainability plans and better Indian pulses production policies in the future.

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Section: Discussionmentioning

confidence: 99%

“…We compared models created from whole and training datasets using MAE, RMSE, and MASE [ 14 , 15 ]. MAPE could not be calculated because several months of time-series data had zero counts.…”

Section: Methodsmentioning

confidence: 99%

An Overview of Pulses Production in India: Retrospect and Prospects of the Future Food with an Application of Hybrid Models

Mishra

Khatib

Lal

et al. 2023

Natl. Acad. Sci. Lett.

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show abstract

“…Firstly, the role of the South Asian Association for Regional Cooperation (SAARC) Food Bank should be strengthened [48] to provide grain reserves and buffers, as well as guarantee to the regional grain security, in the short term. Secondly, active efforts should be made to achieve legally effective trade agreements with grain exporters to overcome grain trade barriers in order to maintain long-term, stable grain trade relations [49]. Therefore, efforts should be made to expand import channels and avoid dependence on imports from individual countries in order to enhance the stability of national grain trades, guarantee uninterrupted supply chains of staple food grains, and guard against grain shortages and soaring prices [45].…”

Section: Discussionmentioning

confidence: 99%

Combined Impacts of COVID-19 Pandemic and Locust Plague on Grain Production and Trade Patterns in South Asia

Zhou

Zhang

2023

Agriculture

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The COVID-19 pandemic and the outbreak of the locust plague in Pakistan have severely impacted grain production and trade in South Asia, thereby posing serious threats to global grain security. This study formulated a comprehensive analysis of crop yield and trade restrictions consequent to the combined impact of COVID-19 and the locust plague with the GTAP model and quantitatively simulated the characteristics and mechanisms of changes in the production and trade patterns of major grain crops (paddy rice and wheat) in South Asia. Results indicate that COVID-19 and the locust plague affected global grain production and imports and exports to varying degrees. Grain production was reduced by 15% and global trade shrank sharply, with total imports and exports shrinking by 5.79% and 1.41%, respectively. This also led to international food prices changing significantly, which further influenced the food affordability and accessibility, especially for developing countries that are heavily dependent on imports. Nepal, Sri Lanka, and Bangladesh were the regions that experienced the highest rises in grain import prices, which caused the processed rice imports of Sri Lanka, Nepal, Bhutan and Maldives, and Bangladesh to drop by 81%, 77%, 80%, and 89%, respectively. Furthermore, the global grain trade patterns were also severely affected. South Asian countries’ grain trade links with China, Europe, Africa, and Latin America were weakened. Grain exports mainly converged in Africa, with Australia, the United States, and Latin America being the main exporters. The findings of this paper are helpful to identify countries facing high grain security risks and can shed light on policy measures to address the dual challenge for guaranteeing global grain security in the post-epidemic era.

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“…Paul et al [42] pointed out impact of covid-19 shocks on vegetable prices and tried to predict daily price of brinjal in 17 markets of Odisha, India. Paul and Yeasin [43] also applied Generalized Autoregressive Conditional Heteroscedastic (GARCH) model to investigate the effects of covid-19 pandemic on prices of major pulses in India. Tiwari et al [44] employed a new technique related to Variance Autoregressive (VAR) model to measure the spillover effect between energy and agricultural commodity prices.…”

Section: Introductionmentioning

confidence: 99%

Spillover Effects of Covid-19 Induced Lockdown on Onion Prices in India

Garai,

Paul,

Paul

2024

JSRR

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In a normal situation onion prices vary in a highly unprecedented way in India. So, it is worth noticing the effect of an uncertain situation on onion prices. In this article an efficient Artificial Intelligence (AI) tool, i.e., Support Vector Regression (SVR) has been used to predict the price fluctuation of onion over the lockdown period, unlock condition and the period including the pre-pandemic situation. Results obtained are compared with prediction of traditional Multiple Linear Regression (MLR) model. Several metrices such as , Root Mean Squared Error (RMSE), Mean Absolute Deviation (MAD), and Relative Mean Absolute Percentage Error (RMAPE) have been used for this purpose. The result of Machine Learning (ML) algorithm indicates that in the nationwide lockdown condition pandemic indicator variables are having more than 70% influence on the onion price variability. The effect is reduced to near about 60% in unlock condition and if considering the whole year data this effect is near about 45%. The results also indicate that ML algorithm is more efficient to capture the variability than the traditional model.

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COVID-19 and prices of pulses in Major markets of India: Impact of nationwide lockdown

Cited by 10 publications

References 27 publications

An Overview of Pulses Production in India: Retrospect and Prospects of the Future Food with an Application of Hybrid Models

An Overview of Pulses Production in India: Retrospect and Prospects of the Future Food with an Application of Hybrid Models

Combined Impacts of COVID-19 Pandemic and Locust Plague on Grain Production and Trade Patterns in South Asia

Spillover Effects of Covid-19 Induced Lockdown on Onion Prices in India

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