Evaluation and application of the CROPGRO-soybean model for determining optimum sowing windows of soybean in the Nigeria savannas

Author:

Bebeley J. F.,Kamara A. Y.,Jibrin J. M.,Akinseye F. M.,Tofa A. I.,Adam A. M.,Kamai N.,Solomon R.

Abstract

AbstractSoybean production is limited by poor soil fertility and unstable rainfall due to climate variability in the Nigeria savannas. There is a decline in the amount and duration of rainfall as one moves from the south to north of the savanna zones. The use of adapted soybean varieties and optimum sowing windows are avenues to increase productivity in the face of climate variability. Crop simulation models can be used as tools for the evaluation of alternative management options for a particular location, including fertilizer application rates, plant density, sowing dates and land use. In this study, we evaluated the performance of the Cropping System Model (CSM)-CROPGRO-Soybean to determine optimum sowing windows for three contrasting soybean varieties (TGX1835-10E, TGX1904-6F and TGX1951-3F) cultivated in the Nigeria savannas. The model was calibrated using data from ten field experiments conducted under optimal conditions at two sites (BUK and Dambatta) in Kano in the Sudan savanna (SS) agro-ecology over four growing seasons. Data for model evaluation were obtained from independent experiment for phosphorus (P) response trials conducted under rainfed conditions in two locations (Zaria and Doguwa) in the northern Guinea savanna (NGS) zone. The model calibration and evaluation results indicated good agreement between the simulated and observed values for the measured parameters. This suggests that the CROPGRO-Soybean model was able to accurately predict the performance of soybean in the Nigeria savannas. Results from long-term seasonal analysis showed significant differences among the agro-ecologies, sowing windows and the soybean varieties for grain yield. Higher yields are simulated among the soybean varieties in Zaria in the NGS than in Kano the SS and Jagiri in the southern Guinea savanna (SGS) agro-ecological zones. Sowing from June 1 to July 5 produced optimal yield of TGX1951-3F and TGX1835-10E beyond which yield declined in Kano. In Zaria and Jagiri the simulated results show that, sowing from June 1 to July 12 are appropriate for all the varieties. The variety TGX1951-3F performed better than TGX1904-6F and TGX1835-10E in all the agro-ecologies. The TGX1951-3F is, therefore, recommended for optimum grain yield in the savannas of northern Nigeria. However, the late maturing variety TGX1904-6F is not recommended for the SS due to the short growing season in this zone.

Funder

Bill and Melinda Gates Foundation

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Reference63 articles.

1. Sanginga, N., Okogun, J., Vanlauwe, B. & Dashiell, K. The contribution of nitrogrn by promiscuous soybeans to maize based cropping in the moist savanna of Nigeria. Plant Soil. 241, 223–231 (2002).

2. Ugbabe, O. O., Abdoulaye, T., Kamara, A. Y., Mbava, J. & Oyinbo, O. Profitability and technical efficiency of soybean production in Northern Nigeria. Tropicultura 35, 203–214 (2017).

3. FAOSTAT. Food and Agriculture Organization of the United Nations. http://faostat.fao.org. (2019). (accessed 22 May 2020).

4. Edema, M. O., Sanni, L. O. & Sanni, A. I. Evaluation of maize-soybean flour blends for sour maize bread production in Nigeria. Afr. J. Biotechnol. 4, 911–918 (2005).

5. Okogun, J. A., Otuyemi, B. T. & Sanginga, N. Soybean yield determinants and response to rhizobial inoculation in an on-farm trial in the Northern Guinea Savanna of Nigeria. West Afr. J. Appl. Ecol. 6, 30–39 (2004).

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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