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

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          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.

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          Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement

          Systematic reviews should build on a protocol that describes the rationale, hypothesis, and planned methods of the review; few reviews report whether a protocol exists. Detailed, well-described protocols can facilitate the understanding and appraisal of the review methods, as well as the detection of modifications to methods and selective reporting in completed reviews. We describe the development of a reporting guideline, the Preferred Reporting Items for Systematic reviews and Meta-Analyses for Protocols 2015 (PRISMA-P 2015). PRISMA-P consists of a 17-item checklist intended to facilitate the preparation and reporting of a robust protocol for the systematic review. Funders and those commissioning reviews might consider mandating the use of the checklist to facilitate the submission of relevant protocol information in funding applications. Similarly, peer reviewers and editors can use the guidance to gauge the completeness and transparency of a systematic review protocol submitted for publication in a journal or other medium.
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            The DSSAT cropping system model

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              An overview of APSIM, a model designed for farming systems simulation

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                Author and article information

                Contributors
                Journal
                Heliyon
                Heliyon
                Heliyon
                Elsevier
                2405-8440
                31 August 2023
                September 2023
                31 August 2023
                : 9
                : 9
                : e19639
                Affiliations
                [a ]Department of Agronomy, Faculty of Agriculture, Universitas Gadjah Mada, Yogyakarta, Indonesia
                [b ]Department of Accounting, Faculty of Economics and Business, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
                [c ]Department of Agricultural Engineering, Faculty of Agriculture, University of Lampung, Bandar Lampung, Indonesia
                [d ]Agrotechnology Innovation Center, Universitas Gadjah Mada, Yogyakarta Indonesia
                [e ]Department of Agricultural and Biosystems Engineering, Faculty of Agricultural and Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia
                Author notes
                []Corresponding author. andrianto.ansari@ 123456mail.ugm.ac.id
                Article
                S2405-8440(23)06847-0 e19639
                10.1016/j.heliyon.2023.e19639
                10558879
                37809882
                94f48f30-6c73-497d-9a87-4ce0a9e8066f
                © 2023 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 21 June 2022
                : 22 August 2023
                : 29 August 2023
                Categories
                Review Article

                rice production,climate model,weather generator,hydrological model,crop model,food security

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