The proximate analysis comprising the carbohydrate, crude protein, crude fibre, ash and moisture contents, and the minerals analysis of two major edible varieties of Dioscorea dumentorum (Esuru), commonly consumed in Ekiti State, Nigeria were estimated after a period of storage using standard chemical methods. The crude protein percentage for stored yellow and white varieties are 3.13 and 2.50 respectively. This is contrary to that of fresh varieties whose crude protein percentages for the yellow and white varieties are 8.24 and 5.44 respectively. The results reveal a significant decrease in protein content in stored Discorea dumentorum varieties compared with previous work on fresh varieties. The crude fat content for the stored yellow and white varieties are 6.07 and 6.88% respectively, while the ash content and the crude fibre contents for the stored yellow and white varieties are 2.80, 2.53 and 1.73 and 1.79% respectively. The carbohydrate contents of the two varieties are 26.97 and 21.33% in the same order. The presence of important minerals like iron, magnesium, phosphorus, calcium, and zinc at a very high level showed that bitter yam would find some useful application in the food and pharmaceutical industries.

The effects of 3 processing techniques: cooking, roasting and autoclaving on the proximate chemical composition, the mineral content and some inherent toxic factors of soya and lima beans were investigated. The processing techniques generally reduced the crude fibre levels and enhanced the extractable fat in the soya and lima beans. The coefficients of variability for crude fibre and ether extract due to the processing techniques of soya and lima beans were 20.9%, 16.0% and 22.3%, 38.1%, respectively. In parallel with decreased ash content in the cooked bean samples, there was a decrease in the K, Mg, Na and P levels relative to the raw bean and also relative to the other processing techniques. Mineral contents of the autoclaved bean samples were generally similar to those of the raw (unprocessed) samples. Under the processing conditions, roasting caused the highest reduction in thioglucoside content (59%) in soya bean while cooking caused the highest reduction in lima bean (78%). Trypsin inhibitor activity (TIA) ranged between 0.59 mg/g sample in the cooked soya bean and 11.6 mg/g sample in the raw bean while the corresponding values for lima bean ranged between 0.59 and 6.3 mg/g sample. Cooking and roasting caused over 90% reduction of TIA, while autoclaving caused 64-69% reduction in both bean samples. Under the assay conditions, haemagglutinating activity was not detected in the cooked and autoclaved soya and lima beans. The need to prevent both functional and nutritional damage to food proteins and other nutrients, resulting from excessive heating, was discussed.

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In this paper, surface data meteorological were used as input variables to create, train and validate the network in which global solar radiation serves as a target. These surface data were obtained from the archives of the European centre for Medium-Range weather forecast for a span of 36 years (1980-2015) over Nigeria. The research aims to evaluate the predictive ability of the nonlinear autoregressive neural network with exogenous input (NARX) model compared with the multivariate linear regression (MLR) model using the statistical metrics. Model selection analysis using the index of agreement (dr) metric showed that the MLR and NARX models have values of 0.710 and 0.853 in the Sahel, 0.748 and 0.849 in the Guinea Savannah, 0.664 and 0.791 in the Derived Savannah, 0.634 and 0.824 in the Coastal regions, and 0.771 and 0.806 in entire Nigeria respectively. Meanwhile, error analyses of the models using root mean square errors (RMSE) showed the values of 1.720 W/m2 and 1.417 in the Sahel region, 2.329 W/m2 and 1.985 W/m2 in the Guinea Savannah region, 2.459 W/m2 and 2.272 W/m2 in the Derived Savannah region, 2.397 W/m2 and 2.261 W/m2 in the Coastal region and 1.691 W/m2 and 1.600 W/m2 in entire Nigeria for MLR and NARX models respectively. These showed that the NARX model has higher dr values and lower RMSE values over all the climatic regions and entire Nigeria than the MLR model. Finally, it can be inferred from these metrics that the NARX model gives a better prediction of global solar radiation than the traditional common MLR models in all the zones in Nigeria.

The study is to analyze the effectiveness of physical biometrics (thumbprint) in order to determine age and gender in humans. An application system was designed to capture the finger prints of sampled population through a fingerprint scanner device interfaced to the computer system via Universal Serial Bus (USB), and stored in Microsoft SQL Server database, while backpropagation neural network will be used to train the stored fingerprint. The specific Objectives of this research are to: Use fingerprint sensor to collect different individual fingerprint, alongside their age and gender, Formulate a model and develop a fingerprint based identification system to determine age and gender of individuals and evaluate the developed system.