PHD-Department of Agricultural Resources Management (ARM)

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    Use oMinjingu Phosphate Rock with Tithonia Diversifolia in Maize-Bean Intercrop For Improved Maize Yields in Two Soil Types in Kenya
    (Kenyatta University, 2015) Ahmat, Filbert Leone
    Phosphorus deficiency and aluminium phytotoxicity are major factors limiting crop production in acid soils. Use of mineral fertilizers, especially by small scale farmers, to alleviate deficiencies of nutrients, such as P, is mainly hindered by their high costs and frequent unavailability. This has made the low input approach using locally available resources such as Tithonia diversifolia and Minjingu Rock Phosphate (MPR) gain a substantial research attention. However, less is known on the response of maize to integrated application of Tithonia and MPR. Therefore, four experiments were conducted to generate this information. Experiment one aimed to examine the relationship between mineral N and available P of surface soils and Tithonia biomass quality (N and P); whereas experiment two was to determine the effect of Tithonia and MPR on soil nutrients, pH and exchangeable AI. The third and forth experiments investigated the influence of the acid synthesized and secreted into the rhizosphere by beans on MPR solubilization and the agronomic responses of maize to Tithonia and MPR application under maize-bean intercrop. In experiment one soil and leafy samples were collected from five areas and analysed for Nand P. The second experiment was an incubation experiment with five treatments while the third experiment was a greenhouse pot experiment with two factors consisting of sole maize and maize-bean intercrop as main factor treatments; and use of different fertilizing input sources plus one combination as sub factor treatments. The fourth was a field trial conducted for two consecutive planting seasons at Kavutiri in Embu County and Muguga in Kiambu County. The experiment was laid in a split plot organized in a Completely Randomized Block Design with two factors: sole maize and maize bean intercrop as the main factor treatments; and sub factor treatments consisting of: Control; T alone (5t1ha dry weight); MPR alone (60 Kg P/ha); TSP alone (60 Kg P/ha); T (5t/ha) combined with MPR (50 Kg P/ha); and T (5t/ha) combined with TSP (50 Kg P/ha). Analysis of Variance (ANOVA) was done using the General Linear Model (GLM) procedure of the Statistical Analyses Software (SAS), version 9.3. Results showed that the concentration levels of mineral Nand available P of the top soils weakly correlated (- .22 ::;r ::;+ .62) with their respective levels in the biomass while in the biomass, N concentration, however, increased with the rising concentration of P (r = +. 95). Integrated application of Tithonia biomass with MPR not only resulted in significant rise, above the control, of available soil N (30.2%), P (182.3%), K (27.6%) and Ca (70.8%) but also in a significant decrease of the concentration of soluble AI; MPR solubilization was further enhanced by 68.7% for MPR applied alone and 223.6% for MPR combined with the biomass under maize-bean intercrop as compared to sole maize. Effects of the applied Tithonia biomass and MPR on agronomic parameters of maize differed under the two cropping systems. In conclusion, this study reveals that integrated use of the low fertilizing inputs (Tithonia biomass and MPR) under maize-bean intercrop improves maize yield on a P-deficient acid soil that is highly saturated with soluble Al more than mineral P fertilizers. Dissemination to farmers of this newly established low input technology by appropriate institutions, such as the ministry of Agriculture, is highly recommended.
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    Efficiency and competitiveness of chicken production in Machakos, Kiambu and Uasin Gishu Counties, Kenya
    (Kenyatta University, 2023) Wambua, Scolastica Mwikali; Ibrahim Macharia; Gabriel Mwenjeri
    A company's or industry's competitiveness is its capacity to successfully compete in order to achieve sustainable growth and earn at least the opportunity cost of the resources used. The poultry sector is very important to the economy of Kenya and plays a key role in food and income security of majority of the producers who are mostly in rural areas. There has been high imports of poultry products from Uganda and China to the country in the past five years causing an uproar by local producers who complain of cheap products flooding the market and affecting their profits. In 2020, Kenya imported 1,000 MT of eggs with zero exports despite having a surplus in egg production. This study was therefore to assess the competitiveness and efficiency of chicken production in Kenya to determine the level of efficiency and ability to produce quality products at relatively lower costs. The specific objectives were; determine the technical, cost and allocative efficiency levels, assess the factors influencing these levels and investigate the competitiveness of improved indigenous chicken farmers in Kenya. Data were collected from 384 small-scale chicken producers across three counties of Kenya (Uasin Gishu, Machakos and Kiambu). A semi-structured questionnaire which had been uploaded on android phones was used to obtain data .A stochastic frontier analysis was carried out to determine the technical and cost efficiency of improved chicken producers in the three counties and factors influencing the efficiencies and a policy analysis matrix approach (PAM) was used to measure the competitiveness of the producers. Results indicated that majority of the farmers were middle aged women who had formal education. The major constraint of chicken production was cost of feeds which had driven some producers of the chicken enterprise. Results indicated that the producers attained an average technical efficiency of 58%,cost efficiency of 39% and allocative was 67%, which were low compared to efficiency scores recorded elsewhere. Some of the socio and institutional factors affecting the efficiencies included; household size, education level of household head, access to extension services, distance to input and output markets and distance to a tarmacked road. Results from the PAM indicated that they were competitive at social values but uncompetitive at private values. The study recommends that research institutions develop cheaper alternative sources of starch and proteins to cut down cost of feeds. It is also recommended that extension services are enhanced to improve farmers’ knowhow on feed formulation, housing and disease management.
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    Phenotypic characterization and evaluating the response of sweetpotato genotypes for drought tolerance as an adaptation to climate change in Ethiopia Selamawit Abebe Gitore
    (Kenyatta University, 2023) Gitore, Selamawit Abebe
    Sweet potato plays a major role as a food security crop in many countries particularly in the sub-Saharan Africa and Asia. Despite its importance, current identification is still limited, which is one of the reasons for low sweet potato productivity at the moment. Drought susceptibility is perceived as one of the major drawbacks of orange fleshed sweet potato genotypes that have been so far released. The objectives of this study are; to characterize sweet potato genotypes present in Ethiopia for selection of those possessing optimal dual-purpose characteristics, to assess the drought stress tolerance of orangefleshed sweet potato genotypes and to identify sweet potato cultivars with good yield and quality, and assess various drought stress tolerance selection indices and choose the appropriate ones for use in identifying drought tolerant sweet potato cultivars in Ethiopia. The experiment was conducted at Boloso sore district, Wolaita region, and southern parts of Ethiopia. 40 selected sweet potato genotypes advanced from crossing experiment and 10 orange fleshed sweet potato genotypes planted on the field using Alpha lattice design for characterization and drought evaluation experiment. Characterization of the genotypes performed using international potato center standardized morphological descriptors. Classification of dual-purpose use varieties was done according to Leon- Velarde approach, based on root to vine ratio. Parameters related with a storage root yield such as vine length, vine Internode length, vine internode diameter, number of branch, vine fresh weight, root yield, Leaf area index were collected for drought evaluation study. The generated data in this study were subjected to analysis of variance using R software, agricolae package. The significantly different means were compared using tukey test at the level of p< 0.05. Principal component analysis and cluster analysis performed to separate and group the genotypes based on their differences and similarities. Phenotypic variability observed among the 40 genotypes for almost all leaf, vine and root parameters except for central leaf lobe, petiole length, and root thickness. The research finding showed that 30 genotypes out of 40 qualified for dual-purpose based on their index value of root to vine ratio. The study revealed that the genotypes MUSG014065-21-13, MUSG014065-21-14 and MUSG014019-7-50 showed the lowest rank sum and standard deviation of rank sum and considered as a drought tolerant genotypes. Stress tolerance index, geometric mean productivity, yield index, stress intensity index and tolerance indices were shown to be the best in identifying drought tolerant genotypes based on their strong correlation with yield under stress conditions. Efforts should be made to promote the adoption of these dualpurpose sweet potato genotypes among farmers to enhance the economic and nutritional benefits of sweet potato cultivation. Further research could also be conducted to identify the molecular markers associated with drought tolerance in sweet potato genotypes to facilitate marker-assisted selection in breeding programs. Moreover, collaboration between researchers, farmers, and policymakers is essential to promote the adoption of drought-tolerant sweet potato varieties and support sustainable agricultural practices.
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    Characterization of Sorghum and Green Gram for Data Estimation Using Earth Observation in Machakos and Tharaka-Nithi Counties, Kenya
    (Kenyatta University, 2024-02) Manzi, Hilda Kalekye
    Data management in agriculture is very vital for the planning of any country, including Kenya. A study was conducted to establish the role that remote sensing data can play in the assessment of spatial variability in crop data and the provision of crop farm information. The main objective of the study was to develop a remote sensing-based crop data information system for estimating green gram and sorghum data, respectively, under farm field conditions. The study was carried out in Ikombe Katanga area of Machakos County for the green gram crop and in Tharaka Nithi area for the sorghum crop. Estimating crop data was based on three approaches: crop area estimation, spectral signature library development for sorghum and green gram, and assessment of microclimates within agroecological zones. The following parameters were estimated and used to calculate the most important crop data for green gram and sorghum for the October, November, and December rains. The parameters selected for the development of this estimation model were vegetation indices, biomass, leaf area index (LAI), enhanced vegetation index (EVI), soil moisture index, soil organic carbon, rainfall, land surface temperature, soil pH, soil nutrients (NPK), and evapotranspiration. The first crop data estimation involved crop area, determined by assessing sorghum and green gram cropping pattern data. The identified cropping pattern for the green gram study area and crop area estimates were mixed crop (maize and green gram), mixed crop (maize and beans), green gram, mixed crop (maize and pigeon pea), mixed crop (maize and cowpea), and maize with 2445.93 ha, 10,034 ha, 5981 ha, 4697.82 ha, 3743.82 ha, and 586.35 ha, respectively. The sorghum crop patterns were mixed crop (sorghum and beans), mixed crop (sorghum and cowpea), and sorghum, with crop area estimates of 1988.46 ha, 961.65 ha, and 469.62 ha, respectively. Furthermore, the development of spectral signature libraries was done, and the spectral reflectance ranges for sorghum and green gram were 0.230064 to 0.321126 and 0.26900 to 0.07466 across all bands, respectively. The results further revealed the existence of microclimates within agroecological zones IV and V and four microclimatic zones within the agroecological zones lower midland IV and V of Tharaka Nithi and Machakos counties. Using data for October, November, and December (OND) rains and cropping season data, it was possible to estimate crop yield. Twelve parameters were analyzed and ran through a random forest machine learning algorithm to generate sorghum yield estimates. The validation of the model was carried out using root mean square error (RMSE) and root mean absolute error (RMAE), with results showing that RMSE was 4.036 with R2 of 0.98 and RMAE was 3.022 for the green gram crop, while for sorghum, RMSE was 6.51 with R2 of 0.99 and RMAE of 5.5. The yield estimates were 4.5 bags/acre for green gram and 9 bags/acre for sorghum, respectively. The data estimation under farm field conditions was sufficiently optimized using the farm crop data estimation (FCropDesti) tool developed from this work using ArcGIS software. The study also confirms that employed methodologies were important in creating a homogenous environment on farms for the identification of cropping patterns, which further determine crop data such as crop area, crop type, and crop yield. Crop data estimation is important for policymakers at the county and country level to implement climate smart agriculture. The research can be replicated in other important crops in the country.