Institute of Women Gender and Development Studies

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    Effectiveness of deficit irrigation scheduling on crop water use efficiency- a case of french beans in Njoro Nakuru County Kenya
    (Egerton University, 2018-10) Sabri, Joshua Lado Silla
    Producing enough food in Kenya to better feed people and generate adequate income for the farmers is a great challenge. This challenge is likely to intensity, with a population that is projected to increase to 66.3 million in 2030. Scarce water resources and growing competition for water will be reduce its availability for irrigation, which necessitating major changes in irrigation management and scheduling in order to increase the efficiency of use of water that is allocated to agriculture, one of the options that can be used to reduce the demand of irrigation water is deficit irrigation. Agriculture needs to increase its production with a small amount of available fresh water. Deficit irrigation is now widely been investigated as one of solution for this problem. Relatively few farmers are equipped to deal with it effectively In this study deficit irrigation was investigated to determine its effectiveness in meeting crop water requirement and saving water with minimum effect on yield. And relationship between crop yield and water supply was investigated. This research was conducted from June 2016 to March 2017 at the Agricultural Engineering department demonstration farm Egerton University, Nakuru, Kenya. The objective of the study was to investigate the effectiveness of deficit irrigation scheduling and water use efficiency of French bean (Phaseolus Valgaris L). The modified FAO Penman Montieth Method was used to calculate evaporation ETo using ETo calculator. Crop coefficients were used to calculate reference evapotranspiration (ETc), the water application levels were 100% of evapotranspiration (ETc), 80% of ETc, 60% of ETc, and 40% of ETc. Based on these irrigation levels, the experiment was laid out using complete randomize block design(CRBD) with six treatments and three replications. Three plants from the inner rows of each experimental unit were randomly selected and tagged for measurement of plant growth variables, which included; plant height, number of branches, leaf area, canopy cover, yield and above ground biomass. Data from the experiment was subjected to analysis of variance (ANOVA) using the GLM procedure of SAS. Data obtained from field experiment was used to calibrate and validate Aqua Crop model to simulate the crop growth. The deficit irrigation levels which were applied throughout the growing season of French beans had significantly (P < 0.001) affected plant height, number of branch , leaf area index and yield. From the results the highest yield was found in treatment 100 of % ETc (8680 kg/ha) while the lowest yield was found in treatment 40%ETc (3158 kg/ha). The highest and lowest crop water use efficiency (3.05 kg/m3) and (2.44kg/m3) respectively were found in 80% of ETc and 40%of ETc. Therefore in water scars areas irrigation levels for French beans can be reduced by 20% water requirement without much effecting on yield. The performance of Aqua crop model was good in simulation of final biomass, pod yield and canopy cover for non-stress treatments but it performed less in simulation biomass and pod yield of the treatments less than 60% of ETc ( under the severe water stress throughout the season). The findings verify use of deficit irrigation at 80% in water scare areas with French beans such crop to adopting conditions.
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    Performance and emission characteristics of spark ignition engines based on engine operating parameters
    (Egerton University, 2010-11) Langat, Langat Kipkirui
    Poor vehicle maintenance culture and high proportions of old vehicles are major contributing factors to high vehicle emission levels. The purpose of this study was to determine performance and emission characteristics of vehicles that were taken for inspection at the Vehicle Inspection Centre in Nairobi City based on engine operating parameters and to develop performance and emission prediction models. The specific objectives were; to determine vehicle exhaust emission levels, engine’s performance and emission characteristics and to develop performance and emission models. The sample size comprised 384 petrol vehicles randomly selected. The key observations included vehicle usage, compression pressure, ignition angle, engine speed, spark plug gap, and vehicle category. The key variables examined were emission of CO, HC and CO2, excess air factor (_) and factors that influence emissions. Logistic regression model was fitted to determine the probability of tested vehicles failing emission tests based on the test variables. Field data were simulated using engine test bed and the effects of engine input variables on engine performance and emission were determined. Sub-model equations were generated from engine performance and emission curves and superimposed to develop engine performance and emission models. Validation, optimization and sensitivity analysis of the models were done. The mean vehicle usage ranged between 14328 km/yr and 19640 km/yr and the lowest compression pressure of 6.8 bar was recorded in the non-catalytic vehicles manufactured before 1986. Both categories of non-catalytic vehicles operated at a rich mixture. There was significant difference between the measured and standard values of exhaust emission gases. The models developed predicted well for engine performance and emission as expressed by low percentage error in most of the points. Optimization of Specific Fuel Consumption (SFC) model gave input variables of 2839 rpm, 16o BTDC, 1.05 _ and spark plug gap of 0.8 mm. Excess air factor was found to be the most sensitive variable when adjusted by ±10%, it mostly affected engine performance and emissions. In conclusion, exhaust emission levels from vehicles measured in Nairobi City were 6.8% vol., 4.41% vol., 1.16% vol. and 0.46% vol. CO for non-catalytic vehicles manufactured before 1986, non-catalytic vehicles manufactured between 1986 and 2002, catalytic vehicles manufactured between 1986 and 2002, and catalytic vehicles manufactured after 2002 respectively. The mean values for HC were 1814 ppm, 1884 ppm, 333 ppm, and 253.4 ppm for non-catalytic vehicles manufactured before 1986, non-catalytic vehicles manufactured between 1986 and 2002, catalytic vehicles manufactured between 1986 and 2002, and catalytic vehicles manufactured after 2002 respectively. These values were significantly different from the limits given in KS 1515-2000. Excess air factor for noncatalytic vehicles manufactured before 1986 and those manufactured between 1986 and 2002 oper were 1.14 and 1.08 respectively, while for catalytic vehicles manufactured between 1986 and 2002, and catalytic vehicles manufactured after 2002 were within the required limit of 1±0.03. There were significant changes in engine performance and emissions when the input variables were changed from optimal values. The models developed predicted well engine performance and emission characteristics. It is recommended that emissions control mechanisms be put in place to reduce emission levels. There is also need to include more test parameters in the models so as to improve on the prediction levels.