Rice aggregation centers are tasked with checkmating substandard agricultural produce that are often encountered by the integrated millers during the course of buying from farm to farm to ensure already made market for their produce. Thus, it must be well placed to occupy strategic positions such that all different rice cultivating zones of the state get access to the facility. Given that these facilities will provide salient services, sets of demand points tasked with the provision storage, processing capability and a constant market for various rice farmers within the state. It is pertinent that these facilities are located properly considering all unique factors on ground. This study therefore aimed at a GIS-based multi criteria model for location of rice aggregation centers in Anambra State. The study was carried out using Geographical Information System (GIS) technology. Several GIS thematic layers were obtained and considered important factors in citing rice aggregation centers such as road network, Land Use and Land Cover (LULC), slope, river, cost distance, electricity network, floodplains, erosion plains and proximity to rice farms. It revealed optimal locations for siting a modular aggregation rice center at Nzam, Onoia, Aguleri, Nando, Akenu, Achalla, Ezira, Ndiokpalaeze, Ogbakuma and Uli. The goal throughout this study was to provide a reliable and complete analysis of siting modular rice aggregation centers in the agricultural zones in Anambra State. The approach and results obtained in this study are recommended as a spatial decision tool for site selection of modular rice aggregation centers in developing countries.
Investigation of microwave drying of sweet potato slices was conducted at microwave oven power settings of 90, 100, 120 Watts and slice thicknesses of 3mm, 4mm and 6mm using Fourier models and response surface methods. The slice samples dried from initial moisture content of 70.71ππππππ/ππ ππ ππππππ to 12.7ππππππ/ππ ππ ππππππ final (equilibrium) moisture content in the microwave oven. Fourier models adequately fitted the drying data with the following values of the fit parameters: MBE= 0.00002943 to 0.000645, RΒ² = 0.9987 to 1, RMSE = 0.00384 to 0.01692. Effective moisture diffusion coefficient (π«π) of the samples ranged from π.ππππ Γ ππβπm2/s to π.ππππ Γ ππβπ m2/s. Analysis of Variance (ANOVA) was used to analyze the effect of drying conditions on the samples parameters at 95% ( p<0.05). The results showed that slice thickness and microwave power have significant effects on the ash and fiber contents of the dried potato samples. At the microwave power of 90 W and slice thickness of 4 mm the values of Fiber and Ash retained in the dried sweet potato samples were optimal at 4.30% and 2.50% respectively, after drying for 390 minutes to an average moisture content of 14.2 gH2O/gdm. Optimized equations for predicting the percent ash and fiber contents at combined factors of microwave power and slice thickness were developed using Response Surface Methodology (RSM) at 95% confidence bound. The coefficients of determination (R2) for the models are 0.7333 and 0.9655 for fiber and ash respectively. These are indications that the models can be used to predict the two food components of microwave dried potato slices.
Keywords: RSM, Fourier Model, Microwave, Sweet Potato, Ash, Fiber
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