Modeling performances of maize cultivars under current and future climate scenarios in southern central Ethiopian rift valley

Author:

Markos Daniel,Worku Walelign,Mamo Girma

Abstract

Abstract Background In southern central rift valley of Ethiopia, maize is an important crop because of its adaptation to wider agro-ecologies and higher yield potential. However, most cultivars were not parameterized to include in the database of Decision Support System for Agro-technology Transfer (DSSAT). As a result simulation of growth and yield of those cultivars was not possible under changing climate. Methods Two set of independent crop, management and soil data were used for calibration and validation of genetic coefficients of maize cultivars (BH-540, BH-546, BH-547, Shala and Shone) under condition of historic weather (1990–2020). Later, we simulated the growth and yield of maize using twenty multimodel climate ensembles across RCP 4.5 and 8.5 during early, medium and late century across Shamana, Bilate, Hawassa and Dilla clusters using DSSATv4.8 model. Results Cultivars BH-540, BH-546, BH-547, Shala and Shone produced yields of 5.7, 5.4, 5.2, 6.9 and 7.4 t ha−1 with the corresponding error percentage of − 0.1, − 0.8, − 1.0, − 6.1 and 2.6%. The results of normalized root mean square were 1.14–4.2 and 3.0–3.9%, for grain yield during calibration and validation, respectively showing an excellent rating. The simulation experiment produced 5.4–9.2 t ha−1 for grain yield of maize cultivars across the study areas, which is likely to fall close to 63.3% by 2070 if right adaptation options are not introduced necessitating switch in cultivars and production areas. Conclusions There is critical need for reduction of GHGs emissions, generation of innovative adaptation strategies, and development of drought and heat stress tolerant maize cultivars. Hence, researchers and policy makers shall act with utmost urgency to embark with breeding programs that target climate change adaptation traits in maize crop.

Publisher

Springer Science and Business Media LLC

Reference75 articles.

1. Abedinpour M, Sarangi A. Evaluation of DSSAT- Ceres model for maize under different water and nitrogen levels. Pertanika J Sci Technol. 2018;26(4):1605–18.

2. Abera K, Crespo O, Seid J, Mequanent F. Simulating the impact of climate change on maize production in Ethiopia, East Africa. Environ Syst Res. 2018;7(4):1–12.

3. Adnan AA, Jibrin MJ, Kamara AY, Abdulrahman BL, Shuaibu AS, Garba LL. CERES-Maize model for determining the optimum planting dates of early maturing maize cultivars in northern Nigeria. Front Plant Sci. 2017;8:1–18.

4. Aggarwal PK, Banerjee B, Daryaei MG, Bhatia A, Bala A, Rani S, Chander S, Pathak H, Kalra N. Infocrop: A dynamic simulation model for the assessment of crop yields, losses due to pests and environmental impact of agro-ecosystems in tropical environments. II. Performance of the model. Agric Sys. 2006;89:47–67.

5. Alexandratos N, Bruinsma J. World Agriculture towards 2030/2050: The 2012 Revision. Rome: Food Agriculture Organization of the United Nations; 2012.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3