Using the CROPGRO Model to Predict Phenology of Cowpea under Rain-fed Conditions

Lomeling, David and Kenyi, Mustafa Mogga and Abass, Abdelrahman Abakr and Otwari, Sebit Mathew and Khater, Yahya Mohammed (2014) Using the CROPGRO Model to Predict Phenology of Cowpea under Rain-fed Conditions. International Journal of Plant & Soil Science, 3 (7). pp. 824-844. ISSN 23207035

[thumbnail of Lomeling372014IJPSS9491.pdf] Text
Lomeling372014IJPSS9491.pdf - Published Version

Download (1MB)

Abstract

Field experiments were conducted in November of 2012 at the University of Juba demonstration farm on cowpea cultivar UCR 368 and local variety JUBA1. In this study, the DSSAT Cropping System Model, CROPGRO-Cowpea, was employed to simulate and predict cowpea yield in a 3-year production period under rain-fed conditions. The treatments selected were then subjected to sensitivity analysis under varied irrigation levels and seed planting dates. The model showed that the grain weight under default rain-fed conditions was on average at 111 kg/ha in all three years while this was between 250-300 kg/ha after varied planting date and over 1000 kg/ha after increased irrigation schedules in Years 2 and 3. For the three years, the model adequately simulated vegetative weight (RMSE=25.03, r²=0.92, d=0.72) and grain weight (RMSE= 20.93, r²=0.99, d=0.99) as well as Leaf Area Index (LAI) (RMSE=0.04, r²=0.92, d=0.61) under the combined treatment effects of varied planting date and increased irrigation schedules. However, increased irrigation frequencies during pre- and post a thesis tended to increase Water Stress in Photosynthesis Days (WSPD) to between 0.7-0.8 but did not negatively influence the total grain weight and biomass. Phenology and yield were lowest under rain-fed conditions but increased with an integrated irrigation management option. The results in our study shows that the model could be used to improve our understanding of the long-term effects of management practices on cowpea yield under varied planting dates and water supply.

Item Type: Article
Subjects: Open Article Repository > Agricultural and Food Science
Depositing User: Unnamed user with email support@openarticledepository.com
Date Deposited: 04 Jul 2023 04:15
Last Modified: 18 May 2024 07:29
URI: http://journal.251news.co.in/id/eprint/1685

Actions (login required)

View Item
View Item