Relationship between Rainfall Variability and Millet (Pennisetum americanum L.) and Sorghum (Sorghum bicolor (L) moench.) Yields in the Sudan Savanna Ecological Zone of Nigeria: A Modelling Approach

Saleh, Haruna and Rilwanu, Tasi’u Yalwa (2021) Relationship between Rainfall Variability and Millet (Pennisetum americanum L.) and Sorghum (Sorghum bicolor (L) moench.) Yields in the Sudan Savanna Ecological Zone of Nigeria: A Modelling Approach. In: Cutting-edge Research in Agricultural Sciences Vol. 10. B P International, pp. 66-76. ISBN 978-93-91215-17-0

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Abstract

This study explores the relationship between rainfall variability parameters and millet (Pennisetum americanum L.) and sorghum (Sorghum bicolor (L) moench.) yields in the Sudan Savanna ecological zone of Nigeria. Daily rainfall, millet and sorghum yield data recorded by the nearby stations for the period between 1981 and 2010 used as input in the model. It attempts to develop a model that can estimate millet and sorghum yields based on rainfall variables. Analytical tools that were utilised to develop and test the model's performance include ogive of cumulative pentad rainfall, product - moment correlation coefficient (r), stepwise multiple regression analysis and coefficient of determination (R2). The research resulted in four yield forecast models: Three for millet in Kano, Katsina, and Potiskum, and another for sorghum in Potiskum. In may assume the best-fitted yield forecast models, the model accounted for 61.7% of variation in millet yield related to total yearly rainfall and 68.1% of variation in sorghum yield related to total rainfall in the month of May. The unaccounted variation in millet yield of 38.3 percent and 31.9 percent in sorghum yield indicate that other factors may influence the yield variability of the two crops. It is recommend that the two best-fitted crop yield models be used for planning and forecasting millet and sorghum yields in the study area, with annual and may totals rainfall held constant.

Item Type: Book Section
Subjects: STM Repository > Agricultural and Food Science
Depositing User: Managing Editor
Date Deposited: 28 Oct 2023 12:38
Last Modified: 28 Oct 2023 12:38
URI: http://classical.goforpromo.com/id/eprint/4391

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