Elemental analysis of rice husk using X-ray fluorescence techniques – a case study of Jigawa State, Nigeria

The rice husk or hard protective shell are woody, siliceous, and not edible part of the rice plant. Here in, the elemental composition of rice husk was determined using the energy dispersive X-ray Fluorescence Technique. The rice husks were obtained from four different Local Governments namely, Hadejia, Dutse, Auyo and Ringim of Jigawa State, Nigeria. The samples were collected during dry season and ground into a fine powder using mortar and pestle The results of the analyses revealed the presence of eleven elements which are; Silicon (Si), Rubidium (Rb), Potassium (K), Calcium (Ca), Manganese (Mn), Iron (Fe), Nickel (Ni), Copper (Cu), Zinc (Zn), Bromine (Br) and Strontium (Sr) for Hadejia and Ringim while Dutse and Auyo are having ten with the absence of Br. The elements detected and their concentration (in %) for Hadejia, Dutse, Auyo and Ringim respectively are as follows Si (69.05, 70.52, 73.18, 69.33), Rb (0.321, 0.153, 0.164, 0.219), K (16.52, 16.03, 14.29, 16.66), Ca (8.45, 8.064, 8.101, 8.85), Mn (1.104, 1.026, 0.99, 1.077), Fe (3.739, 3.564, 2.719, 3.162), Ni (0.27, 0.291, 0.291, 0.249, 0.26), Cu (0.021, 0.018, 0.017, 0.015), Zn (0.36, 0.266, 0.226, 0.307), Br (0.065, 0.00, 0.00, 0.046) and Sr (0.087, 0.056, 0.05, 0.063). The results of the analysis in % shows Si with high percentage concentration followed by K and the rest are in the following ascending order Ca > Fe > Zn > Rb > Sr > Br > Ni > Cu. Four new elements were discovered namely; Rb, Cu, Sr and Br in rice husk which were not common in other existing studies. The composition can also be affected by factors such as soil chemistry, climatic conditions, and the type of fertilizer used

Assessment of biogas production from mixtures of poultry waste and cow dung

The increase price of cooking gas and high rate of deforestation (firewood) has led to search for an alternative source for cooking. This study was carried out to produce biogas from cow dung and poultry waste as well as the respective co-digestion of cow dung and poultry dung as alternative fuel for cooking. Four-liters digester and gas collection system were designed and fabricated using locally available materials. The digesters were used to digest cow dung and poultry dung respectively as a single substrate as well as to digest cow dung and poultry dung respectively. The respective materials were collected locally. They were fermented, digested and analyzed in accordance with standard methods for the single substrate. The total volume of gas produced was recorded for different mixtures of cow and poultry waste. The total volume of gas produced ranged from 222 cm3 (20g cow dung plus 60g poultry waste) to 258cm3 (80g cow dung plus 0g poultry). The result shows that cow dung produces more gas than the poultry waste. Therefore, it is recommended that biogas factories or industries should be established that make use of the abundant animal waste. This will reduce the over-dependence on other forms of energy

Assessing the influence of weather parameters on rainfall to forecast river discharge based on short-term

Rain serves as one of the key components in water cycle and it comes in the form of water droplets that are condensed from atmosphere and then fall on earth surface as rainfall. It has much importance. However, excessive rainfall can cause environmental hazards. This work developed an adaptive neuro – fuzzy inference system (ANFIS) to relate certain weather parameters (temperature and relative humidity) with rainfall in order to forecast the amount of rainfall capable of causing River Yazaram in Mubi town to discharge. It is predicted that, Mubi will experience high rainfall on 7th, 27th and 30th August 2016 as 56 mm, 28.8 mm and 28.8 mm respectively. Furthermore, on 7th August 2016 River Yazaram is likely to discharge. The model developed is validated with mean square percentage error (MAPE) of 4.64% and correlation coefficient of 0.1277 and 0.075 of rainfall with temperature and relative humidity respectively. Keywords: Model, Weather parameters, Forecasting and rainfal