*Result*: Assessing rice yield responses to climate change scenarios using a crop simulation model.

Title:
Assessing rice yield responses to climate change scenarios using a crop simulation model.
Authors:
Baydar A; Department of Biosystems Engineering, Faculty of Agriculture, Siirt University, Siirt, Türkiye.
Source:
PeerJ [PeerJ] 2026 Mar 12; Vol. 14, pp. e20965. Date of Electronic Publication: 2026 Mar 12 (Print Publication: 2026).
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: PeerJ Inc Country of Publication: United States NLM ID: 101603425 Publication Model: eCollection Cited Medium: Internet ISSN: 2167-8359 (Electronic) Linking ISSN: 21678359 NLM ISO Abbreviation: PeerJ Subsets: MEDLINE
Imprint Name(s):
Original Publication: Corte Madera, CA : PeerJ Inc.
Contributed Indexing:
Keywords: Climate change; Cultivar genetic coefficients; DSSAT crop simulation model; RCP 4.5–8.5; Rice
Entry Date(s):
Date Created: 20260317 Date Completed: 20260317 Latest Revision: 20260317
Update Code:
20260317
PubMed Central ID:
PMC12989151
DOI:
10.7717/peerj.20965
PMID:
41841122
Database:
MEDLINE

*Further Information*

*Climate change is considered one of the most significant global environmental challenges of the future, and it is expected to adversely affect crop production. Rice is one of the most widely consumed staple foods in the world. Crop simulation models are tools that help researchers to simulate crop production stages for the future at the selected regions. The aim of this study was to evaluate the accuracy of the DSSAT (Decision Support System for Agrotechnology Transfer) CERES (Crop Environment Resource Synthesis) Rice (DSSAT-CERES-Rice) crop simulation model during its calibration and validation stages, and to assess the impacts of climate change in the Mediterranean region of Türkiye. In the calibration stage, the results showed that the estimated phenological values were within an acceptable range, with an error percentage below 10%. The simulated and observed leaf area index (LAI) showed good agreement with normalized root mean square error (nRMSE) ranging from 17.40% to 28.44% and Willmott's d-index values of 0.59-0.79. Similarly, biomass simulations were consistent with observations (nRMSE: 5.60-18.52%) with satisfactory d-index values, except under I<subscript>1.50</subscript> treatment. Climate change scenarios indicated that average yields under irrigated conditions increased by up to 10% in the late-future period, while rainfed conditions showed decreases of 15-25% due to higher temperatures and shortened growth duration. The findings highlight that the crop simulation model offers a robust framework for evaluating the impacts of climate change and guiding the development of effective adaptation strategies.
(©2026 Baydar.)*

*The authors declare there are no competing interests.*