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Forecast Models for the Yield of Millet and Sorghum in the Semi Arid Region of Northern Nigeria Using Dry Spell Parameters

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Author(s): B.A. Sawa | A.A. Ibrahim

Journal: Asian Journal of Agricultural Sciences
ISSN 2041-3882

Volume: 3;
Issue: 3;
Start page: 187;
Date: 2011;
Original page

Keywords: Coefficient of determination | double log function | dry spells | forecast model

ABSTRACT
This study aims at presenting models for the prediction of millet and sorghum yields in the face of occurrence of dry spells of 5, 7, 10 and equal to or greater than 15 consecutive days during the growing season. Daily rainfall records and crop yield per hectare for three decades (1976-2005) were used to develop forecast models for the yield of millet and sorghum in the semi arid region of Northern Nigeria on the basis of dry spell parameters. Frequencies of dry spells of 5, 7, 10 and equal to or greater than 15 consecutive days were determined. Bivariate correlation analysis, stepwise regression (forward selection) and double log multiple regression were then used to develop models for the prediction of the yield of the two crops. Results of the analyses show that of the twenty-one (21) dry spell parameters, only one (total dry spells in the growing season) indicated significant correlation with millet at 0.01 levels. Except 7-day dry spells in May and 5-day dry spells in September, sorghum show significant correlation with the remaining nineteen (19) dry spell parameters. Stepwise multiple regression identified total dry spells during the growing season as being critical to millet yield while 5-day dry spells in May and total dry spells in the growing season were picked for sorghum. The model for millet yield is logY = 0.0715-0.0817 logX2, implying that if the occurrence of total dry spells during the growing season is unity, the yield of millet would be reduced by about 0.0817 T/ha in the study area. That for sorghum is logY = 0.170 + 0.0629 logx1 - 0.141 logx2, meaning that the occurrence of a single 5-day dry spell in May would increase sorghum yield by about 0.0629 T/ha but that of total dry spells would reduce it by 0.141 T/ha. About 54.5% variation in millet yield is accounted for by occurrences of total dry spells during the growing season while 63.2% of the variation in sorghum yield is due jointly to the occurrence of 5-day dry spells in May and total dry spells in the growing season. Both the forecast error and the linear graph of observed and predicted yields suggest that the models are good enough for the forecast of millet and sorghum yield in the area.
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