Browsing by Author "Fasinmirin, Johnson T."

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    Application of artificial neural network for forecasting standardized precipitation and evapotranspiration index: A case study of Nigeria
    (John Wiley & Sons, Inc., 2020-07) Ogunrinde, Akinwale T.; Oguntunde, Phillip G.; Fasinmirin, Johnson T.; Akinwumiju, Akinola S.
    The necessity to perform an accurate prediction of future characteristics of drought requires a robust and efficient technique that can deduce from historical data the stochastic relationship or dependency between history and future. In this study, the applicability of the artificial neural network (ANN) is used for forecasting the standardized precipitation and evapotranspiration index (SPEI) at 12-month timescale for five candidate stations in Nigeria using predictive variable data from 1985 to 2008 (training) and tested data between 2009 and 2015. The predictive variables are monthly average precipitation, average air temperature, maximum temperature, minimum temperature, mean speed, mean solar radiation, sunshine hours, and two large-scale climate indices (Southern Oscillation Index and North Atlantic Oscillation). From the several combinations of the input variables, training algorithms, hidden, and output transfer functions, a total of eight model runs stood out using a three-layer ANN network. The most efficient ANN model architecture had 9,8,1 as the input, hidden, and output neurons, respectively, trained using the Levenberg-Marquardt training algorithm and tansig as the activation and hidden transfer functions. Assessment on the efficiency of the model based on statistics indicate that the coefficient of determination, root mean square error, Nash-Sutcliffe coefficient of efficiency and the mean absolute error ranges between 0.51 and 0.82; 0.57 and 0.75; 0.28 and 0.79; 0.44 and 0.56, respectively, during the testing period. The output of these findings shows that ANN modeling technique can play a significant role as a data-driven model in forecasting monthly SPEI time series and drought characteristics in the study area, thereby leading to the development of an early warning system for the country
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    Influence of Tree Age and Variety on Allometric Characteristics and Water Use of Mangifera indica L. Growing in Plantation
    (Hindawi Publishing Corporation, 2011-09-22) Oguntunde, Philip G.; Fasinmirin, Johnson T.; Van de Giesen, Nick
    Mango (Mangifera indica L.), a diffuse-porous species and one of the most important tropical tree crops [1], belongs to the family Anacardiaceae [2]. It is believed that mango was brought from Arabia to Africa in the first millennium AD [3]. Ghana received more than a dozen cultivars in the early 1920s and more than a dozen other cultivars were brought in later from Florida and India [2]. However, because of identification problems, an effort was initiated in 1967 to classify the seedlings in the Ejura district, the Ejura Agricultural Station, and the plantation of the Faculty of Agriculture, University of Science and Technology, Kumasi, in order to eliminate confusions and have identifiable cultivars marked for future research. There is great potential for the rapid growth of mango industry in West Africa if the current planting rate and government encouragements are sustained. Although mango is drought tolerant and could be conveniently cropped under rain-fed conditions, supplemental irrigation may be required for optimising growth, fruit set, and yield [4]. Poor and unreliable flowering is one of the factors leading to low productivity [5], but applying irrigation from peak flowering to fruit maturity could induce reliable flowering leading to high yield [6, 7]. Preflowering irrigation was reported to increase the overall photosynthetic activity of the tree at the time of flowering [8]. The necessity to directly and continuously monitor water use for precise irrigation scheduling in mango plantations has been reported [4, 7]. Subsequently, a Granier sap flow measurement method was evaluated and applied successfully to measure sap flow per unit sapwood area in young to mature mango trees. Despite current advances, especially in Australia, there is little or no information regarding water use of mango trees in West Africa. In the study area, the planting practices have resulted in age differences of adjacent plantations coupled with indiscriminate mixtures of varieties or cultivars. These lead to differences in cultivars composition on different stands. Previous studies reported that young/mature trees use more water per unit sapwood area than old trees of the same species in a similar environment due to changes in stem and branch hydraulics with age [9, 10] as well as pressure gradient due to gravity [11]. The objectives of this study were 2 Journal of Botany to examine the degree to which differences in tree age and variety mixture affect water use and allometric characteristics of mango trees under subhumid tropical environment of West Africa. The study was part of the just concluded GLOWA Volta project (http://www.glowa-volta.de/), which lasted between 2000 and 2009. In the context of this project, designed to study “sustainable water use under various land use change and rainfall reliability,” understanding the hydrological process in the basin water balance is very important. Determinations of water use from each component of ecosystem vegetation were required and therefore partly motivated this study