A mixed concentrate diet was replaced by graded levels of dried moringa foliage in growing Black Bengal goats and dry matter intake, digestibility and nutrient utilization and the growth performances were determined. Thirty growing male goats were divided into five groups with six animals in each group. The five dietary treatments consisted of varying proportions of moringa foliage (MF) and concentrate (C), namely, T 1 (100MF: 0C), T 2 (75MF:25C), T 3 (50MF:50C), T 4 (25MF: 75C) and T 5 (0MF:100C). The experiment was arranged in completely randomized design. All the five diets contain similar level of crude protein (average CP 18.3±0.09%) and metabolizable energy (average ME 10.96±0.19).The intake of dry matter and CP of goats on diet T 1 (100% moringa) differed significantly (p<0.01) from that of T5 (100% concentrate) diet. ADF intake was increased with the increasing level of moringa foliage, similarly the digestibility of ADF was increased significantly (p<0.01) with increasing level of moringa foliage. The digestibility of other nutrients did not vary significantly (p>0.05) among the diets. Nitrogen retention was significantly higher (P<0.01) in goats fed withT 1 , T 2 orT 3 diet than those fed with T 4 orT 5 diet. Highest average daily live weight gain was found in goats fed with T 2 diet while the lowest (P<0.05) was found in goats fed with T 5 diet. It was concluded that moringa foliage may be a replacer of conventionally mixed concentrate for feeding Bengal male goats.

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The study was carried out to determine the presence and concentration of some heavy metals in the blood of Holstein-Friesian cattle in a private farm in Nasarawa State Nigeria. Blood samples were obtained from 22 Holstein-Friesian cattle consisting of 21 cows and 1 bull, of ages between 3.5 and >3.5 years. The samples were analyzed using Atomic Absorption Spectrophotometer (AAS). The mean lead (Pb), Iron (Fe) and Cadmium (Cd) concentrations were 1.160, 47.681 and 0.051 mg/kg, respectively. There was no significant (P>0.05) effect of age and sex on the concentration of Pb, Fe and Cd. The study found the presence of Pb, Fe and Cd in blood samples collected from Friesian cattle. The FAO/WHO permissible limit of Cd and Pb in blood is 0.5mg/kg. Pb was detected above the maximum limit. The high concentration of these metals recorded could be as a result of prolong use of inorganic agricultural products and likely irrigation water which contaminate the feed. High levels of these metals in Holstein-Friesian can cause decreased milk production, placenta damage, mineral deficiency and respiratory failure among others. Inorganic agriculture should be replaced with organic methods; industrial activities close to pasture yards should be avoided. Sources of irrigation water should be free from heavy metals contamination.

The experiment was conducted at screen house of Centre for Dry land Agriculture, Bayero University Kano, in the year 2016. The objective of the study was to determine the effects of poultry manure and nitrogen rates from battery cage and deep litter systems on dry matter yield, morphological characteristics and forage quality of Columbus grass (Sorghum almum). Sorghum almum seeds were sown in 32 plastic containers (dimensions 26 cm height, 28 cm top width and 20cm base width) perforated at the bottom containing 12 kg mixture of sandy and loamy soil in ratio of 1:3. The treatments consisted of poultry manure from two production systems (Battery cage and Deep litter) and nitrogen rates (50, 60, 70 and 80 kgN/ha) in a 2x4 factorial combined in a completely randomized design. Parameters measured were dry matter yield, number of tillers and stem diameter at the late boot stage of Sorghum almum, in addition, forage quality parameters (CP, ADF NDF, digestible dry matter (DDM) dry matter intake as a percentage of body weight (DMI) and relative feud value (RFV)) were also evaluated. The results revealed no significant (p>0.05) difference between battery cage and deep litter fertilized Sorghum almum but deep litter fertilized Sorghum almum had numerically higher dry matter yield (5062.30 kg/ha) than battery cage (4400.40 kg/ha) Number of tillers and stem diameter were found to be significantly greater (p<0.05) in Deep litter (2.56 and5.70mm respectively) compared to Battery cage (1.13 and 5.08mm respectively. Both dry matter yield and stem diameter of Sorghum almum were significantly (p<0.05) highest at 80 kg N/ha. Crude protein was observed to be significant (P<0.05) in Sorghum almum fertilized with poultry manure from deep liter (11.35%) compared with buttery cage (10.05 %). The CP value was observed to increase with increased nitrogen rate with the highest value recorded at 80 kg N/ha (1.71%). Dry matter intake (us a percentage of body weight) was equally greater (p<0.05) in Sorghum album fertilized with deep litter (2.63%) compared to battery cage (2.49%). The value for NDF was significantly higher in sorghum almum fertilized with battery cage, while that of ADF was greater in deep litter it can be concluded that, Sorghum almum fertilized with manure from deep litter system produced better yield and nutritive value.

<p>Quadcopters are popular UAVs owing to their compact size and maneuverability. Quadcopters are unmanned aircraft guided by remote control, and the demand for them is increasing due to their widespread surveillance, goods delivery, aerial photography, and defense applications. Nonlinear quadcopter operation makes control system implementation very challenging. In this paper, based on artificial intelligence (AI), we train a feedforward neural network (FFNN) controller of a traditional proportional integral derivative (PID). The conventional (PID) is generally tuned to improve the quadcopter control and performance. FFNN can perform offline learning between the inputs and outputs of the controller to learn its behavior. Once the learning is complete, we replace the PID controller with the neural network controller, to get a controller that can maintain system stability,and overcome the limitations of hardware implementation problems caused by the classical PID controller.</p>