Evidence map›Paper›PMID 37809882›Full record

ReviewHeliyon2023

Evaluating the effect of climate change on rice production in Indonesia using multimodelling approach.

Andrianto Ansari, Arin Pranesti, Mareli Telaumbanua, Taufan Alam, Taryono, Rani Agustina Wulandari, Bayu Dwi Apri Nugroho, Supriyanta

Abstract readReview
In one paragraph

Review in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Andrianto AnsariDepartment of Agronomy, Faculty of Agriculture, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Arin PranestiDepartment of Accounting, Faculty of Economics and Business, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia.
Mareli TelaumbanuaDepartment of Agricultural Engineering, Faculty of Agriculture, University of Lampung, Bandar Lampung, Indonesia.
Taufan AlamDepartment of Agronomy, Faculty of Agriculture, Universitas Gadjah Mada, Yogyakarta, Indonesia.
TaryonoDepartment of Agronomy, Faculty of Agriculture, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Rani Agustina WulandariDepartment of Agronomy, Faculty of Agriculture, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Bayu Dwi Apri NugrohoDepartment of Agricultural and Biosystems Engineering, Faculty of Agricultural and Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia.
SupriyantaDepartment of Agronomy, Faculty of Agriculture, Universitas Gadjah Mada, Yogyakarta, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Achieving global food security in the face of climate change is a critical challenge, particularly in vulnerable countries like Indonesia. To effectively address this challenge, a systems-based approach utilizing climate-hydrological-crop models has emerged as an integral approach. These models integrate climate, hydrological, and crop components to understand and predict the complex interactions within agricultural systems and their responses to climate variables. By employing this approach, policymakers, researchers, and stakeholders can gain comprehensive insights into the potential consequences of climate change on crop growth, water availability, soil fertility, and overall crop yield. However, challenges exist in the implementation of this approach, including data reliability; scarcity of complete long-term data; lack of experimental information about crop species, especially local varieties; inadequate research resources; lack of expertise concerning modeling approaches; lack of testing; inaccurate testing; calibration; and model uncertainties. Furthermore, to address limitations and challenges in implementing this approach, improving the availability and reliability of data, collection method, and data quality should be conducted to ensure the accuracy of simulation and prediction. Finally, climate-hydrological-crop models, alongside improved data collection and modelling techniques, serve as essential tools for guiding the development of effective adaptation measures to mitigate the impacts of climate change on rice production in Indonesia.

Indexed as

Climate modelCrop modelFood securityHydrological modelRice productionWeather generator

Identifiers

PMID37809882
PMCPMC10558879

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.