ArticleHeliyon2023
Modelling climate variabilities and global rice production: A panel regression and time series analysis.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 26 citations in OpenAlex.
- A CNN-Based Image Detection System for Full-Surface Defects in Brown Rice.Foods (Basel, Switzerland) · 2026Article
- Frog Density and Growth Stage of Rice Impact Paddy Field and Gut Microbial Communities in Rice-Frog Co-Cropping Models.Microorganisms · 2025Article
- Characterizing Droughts During the Rice Growth Period in Northeast China Based on Daily SPEI Under Climate Change.Plants (Basel, Switzerland) · 2024Article
- Enhanced forecasting of rice price and production in Malaysia using novel multivariate fuzzy time series models.Scientific reports · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Climate change threatens agriculture and it remains a present global challenge to food security and Sustainable Development Goals. The potential impact on the supply of crops such as rice is seen as a major food security issue that requires intervention on several fronts. The literature on rice production, climate variations and climate change show several studies outlining various impacts on rice supply as a result of variations in temperature and rainfall. This study intends to further explore the impacts on rice production caused by temperature changes and rainfall variation by analyzing and modelling the production of rice by the top rice-producing countries globally. A time series of the national rice production and yield along with national average annual temperature and rainfall were sourced for 15 major rice-producing countries. The trends of the time series were then compared between the rice productivity variables and temperature and rainfall. A panel regression model was also developed to further assess the relationship between rice production and temperature and rainfall. The time series showed that rice production and yield are increasing for the majority of the countries analyzed. The panel regression model however showed that continued increase in temperature can result in decreased production of rice and that rainfall volume directly impacts rice output and therefore shows rice production is highly susceptible to flooding and drought events caused by climate variabilities.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.