Faculty of Science, Engineering and Technology (FSET)

Permanent URI for this communityhttps://repository.chuka.ac.ke/handle/123456789/156

Browse

Now showing 1 - 20 of 32

A hybrid deep learning model for intrusion detection in cloud-based implantable medical devices
(Chuka University, 2015) Kirimi James
The rapidly evolving technologies in the healthcare sector, such as implantable medical devices (IMDs), require advanced security solutions that leverage the intelligence capabilities of these technologies while ensuring optimal safety and reliability. The IMD technology redefines healthcare service delivery by offering timely interventions, minimally invasive treatment options, and continuous patient condition monitoring to improve quality of life. Despite these achievements, IMDs face unauthorised access, data manipulation, and denial-of-service attacks, which conventional security solutions are limited in handling due to resource constraints within IMD ecosystems. As a result, different machine learning and deep learning frameworks have been proposed for real‐time threat detection. However, they still suffer from overfitting, slow inference, and excessive resource demands, hindering their effective integration into the IMD ecosystem. The study's primary goal was to design and develop a hybrid of deep autoencoders, convolutional neural networks, and long short-term memory (LSTM) strategies to provide a comprehensive detection model that reduces inference time for deployed models while enhancing performance. Autoencoders provide the fundamental architecture of the detection model, while convolutional neural networks are used in the encoder and decoder for simplicity and to capture nonlinear data effectively. The Long Short-Term Memory captures temporal dependencies in the model, enhancing overall detection capabilities. The study adopted an experimental approach, developing a hybrid deep autoencoder model to test its performance against convolutional neural networks, long short-term memory, and other conventional machine learning techniques. The results demonstrate that the hybrid model outperformed standalone models, achieving high accuracy scores across the datasets. The best model in the ICU dataset achieved 100% accuracy, precision, recall, and F1 score, and a false positive rate of 0.00%. The WUSTL had an accuracy of 79.32%, a recall of 79.92%, a precision of 79.41%, a specificity of 79.24%, and a false positive rate of 20.59%. The Edge IIoT dataset had a recall, F1, and accuracy of 96.87%, a precision of 96.94%, a specificity of 96.88%, and a false-positive rate of 3.12%. The model’s inference time was substantially reduced compared to the standard deep autoencoder model across the datasets, providing a lightweight detection environment for the intrusion detection system.
AB INITIO STUDY OF STRUCTURAL AND PIEZOELECTRIC PROPERTIES OF HAFNIUM DOPED BISMUTH SODIUM POTASSIUM TITANATE
(Chuka University, 2023-10) MWANZIA BONFACE MUTUKU
Piezoelectric materials have gained increased attention in the recent times due to their significant technological applications. These materials are widely used to make ultrasound transducers, sensors, actuators and others are used for energy harvesting. Due to its brilliant piezoelectric properties, Lead Zirconate Titanate (PZT) is mostly used with a piezoelectric constant of 𝑑33 = 374 𝑝𝐶/𝑁 from experimental reports and 306 − 314 𝑝𝐶/𝑁 from theoretical studies. However, due to the toxic nature of lead oxide which is formed when PZT is being manufactured, there is increased effort in development of lead-free materials. Several classes of materials have recently been studied and are now being considered as potential alternatives to PZT. Lead free perovskite systems such as Bismuth Sodium Potassium Titanate (BNKT) have been developed, with a piezoelectric constant 𝑑33 = 157 𝑝𝐶/𝑁 . However, the main drawback of this system is that it is highly corrosive and has a low piezoelectric constant compared to PZT. In the quest to provide suitable alternatives, dopants such as zirconium have been used, which improved the piezoelectric constant of BNKT up to203 𝑝𝐶/𝑁. Hf which possesses similar physico-chemical properties as zirconium has led to an improvement in the piezo electric constant of other piezoelectric systems such as in hafnium doped Barium Titanate (BT). It has an added advantage of being extremely resistant to corrosion, which is expected to mitigate the corrosive nature of BNKT. In this study, hafnium has been incorporated in BNKT so as to engineer an alternative material suitable for piezoelectric applications. Density Functional Theory (DFT) method was used to predict the structural and piezoelectric properties of hafnium doped BNKT, starting with those of Bismuth Sodium Titanate (BNT) and BNKT. The exchange and correlation was taken as the Generalized Gradient Approximation (GGA). The optimal lattice parameters for BNT were found to be 𝑎 = 5.57 Å and 𝑐/𝑎 ratio of 2.50 for the conventional cell, having space group R3c space group number 161. Piezoelectric constant for this system was found to be 97.67 pC/N. This structure was adopted for doping and further calculations. Potassium doped bismuth sodium titanate was modelled using VESTA software and its optimized lattice parameter was found to be 𝑎 = 5.60 Å. Piezoelectric constant for this system was found to be 147.42 pC/N. Hafnium doped BNKT had an improved piezoelectric constant of 205.52 pC/N for 3% hafnium doping, which decreased to 163.22 pC/N at the level of 6% doping. The results shows that small amounts of hafnium improved the piezoelectric constant of BNKT from 147.42 pC/N to 205.52 pC/N. Elastic and elastic compliance full tensors for these systems was also generated with elastic constants of C33 = 286.48 Gpa, 282.13 Gpa, 257.193 Gpa and 276.43 Gpa for BNT, BNKT, 3% Hf doped BNKT and 6% Hf doped BNKT respectively. This study concludes that doping BNKT with hafnium indeed improves the piezoelectric properties of BNKT. This makes this material more useful in energy generation since high piezoelectric constant leads to efficient mechanical – electrical energy conversion in the piezoelectric materials.
An enhanced convolutional neural network model for translating Kenyan sign language into text in english
(Chuka University, 2024) Muthui Nancy Njoki
Most people communicate effectively and socialize through verbal means, such as talking. However, mute and deaf people cannot interact with society through speech. So, they use the non-verbal modes of communication. Non-verbal communication is a sort of usual body movements, hand gestures, and facial expressions like sign language, and this needs translation according to the specific patterns that the gestures and facial expressions or positioning of the hands, fingers, and arms carry with them during sign language. While it bridges a gap between those who can hear and those who cannot, it is by no means universally comprehended, thus standing as a barrier that leads to frustration and social exclusion of deaf people. As such, a translation tool may help convert sign language into easily understandable written language that will facilitate smooth communication between hearing and hard-of-hearing persons. While lots of research is going on in the area, little attention has been given to translating Kenyan Sign Language into some of the commonly spoken languages in Kenya. Besides, most translation tools face several challenges due to changing environmental conditions and the movement of a person while performing sign language, leading to changes in background lighting. This work translates KSL into English text through the experimental approach using a deep learning CNN model, DenseNet121, preprocessed by Contrast-Limited Adaptive Histogram Equalization. This architecture has been developed, trained, and tested on the dataset provided by the Kenyan Sign Language Classification Hackathon with an accuracy of 91.5%. The proposed model will bridge communication gaps and help include people who are hard of hearing in educational, health, and employment opportunities.
ANALYSIS OF PRODUCTION, SOCIO-ECONOMIC AND INSTITUTIONAL FACTORS AFFECTING TECHNICAL EFFICIENCY OF SMALLHOLDER BANANA PRODUCERS IN KIRINYAGA CENTRAL SUB-COUNTY, KENYA
(Chuka University, 2023-10) MATIVA JACKSON MKENYE
Banana provides food, nutrition security and income for most households and is fourth most popular food crop in the world after wheat, maize and rice. Despite its significance, full potential of banana production in Kenya remains unexploited by smallholder producers. This is as a result of low technical efficiency especially in utilization of farming inputs and producer specific factors like production, socio-economic and institutional factors among others. In Kirinyaga County, the actual banana production is at 4-18 tonnes per acre against the potential of 30-40 tonnes. Due to the limited supply of resources for production, attainment of highest possible levels of technical efficiency is key to achieving sufficiency in banana farming. This study aimed at analyzing the effects of production, socio-economic and institutional factors on technical efficiency of smallholder banana producers in Kirinyaga Central Sub-County, Kenya. The study used a cross-sectional research design and targeted a population of 24,440 smallholder banana producers. Multistage sampling technique was employed where purposive sampling and simple random sampling methods were used in some stages to sample respondents in the study area. A sample of 402 smallholder banana producers were selected. Using a questionnaire, primary data on production, socio-economic and institutional factors affecting technical efficiency of banana production was collected. The data was then analyzed using Stata version 17 and SPSS version 25. Descriptive statistics were used to describe the production, socio-economic and institutional factors of the smallholder banana producers. A stochastic frontier analysis approach was used to model the technical efficiency level using the Cobb-Douglas function. The stochastic production function of the Cobb Douglas function was estimated using the maximum likelihood estimation technique. The study showed that the level of banana production technical efficiency among the smallholder producers varied between 0.9% to 95.5% and average technical efficiency of 83.1%. According to the model parameters calculated, land set aside for production of banana, banana suckers and agrochemicals were significant production factors in banana cultivation at 5% significance level. The study found that agrochemicals and planting materials had positive effects on technical efficiency whereas land size had a negative impact on technical efficiency. This implied that increasing the amount of land set aside for banana production by an acre reduces the amount of banana harvested by 0.438 kgs while increasing the amount of planting materials and agrochemicals used by one unit increases banana production by 1.315 and 0.155 kgs, respectively. The study found that decision makers’ age and size of the household had negative effects on banana production technical efficiency whereas education, experience, producer group membership and market access had positive effects. The study recommends people with high levels of education to venture into banana production. In addition, producer group formation and membership be encouraged for the benefit of increasing technical efficiencies. The inefficient producers are advised to increase their present output by enhancing technical efficiency as a result of the inefficient utilization of their resources throughout production.
APPLICATION OF QUEUING THEORY FOR OPTIMAL CUSTOMER CENTRICITY TO THE BANKING SECTOR IN KENYA
(Chuka University, 2023-10) JUMA SAMWEL KISIANG’ANI
Long queues and waiting times are common in banks, resulting in customer dissatisfaction and low customer retention. The study applied a descriptive research design to investigate queuing dynamics in a banking hall at a commercial bank in Kenya. A single server system (M/M/1) queuing model was used to estimate the average waiting time, system intensity, service time, and optimal number of staff during peak and off-peak periods (July). The study used secondary data on daily waiting times, service times, the number of customers, and servers for May and July 2019, 2020, and 2021 during working hours between 8.30 a.m. and 4 p.m. on Monday to Friday and 8:30 a.m. and 12 p.m. on Saturdays. Data analysis was done using R and Excel. The research findings indicated that the peak periods (May) recorded an average waiting time (AWT) of 13 minutes, 35 seconds in 2019, 10 minutes, 14 seconds in 2020, and 8 minutes, 36 seconds in May 2021. In the off-peak periods (July), an AWT of 3 minutes, 46 seconds, was registered in 2019, 5 minutes, 12 seconds in 2020, and 7 minutes, 42 seconds in 2021. An average service time (AST) of 1 minute 52 seconds in May 2019, 2 minutes 34 seconds in May 2020, and 2 minutes 27 seconds in May 2021. In the off-peak periods (July), an AST of 3 11 seconds was registered in 2019, 3 4 seconds in July 2020, and 2 43 seconds in July 2021. Overall, the system intensities are low to moderate, with the COVID-19 pandemic severely impacting the peak period more than the off-peak. In the peak periods, the service rates averaged 33, 24, and 25 persons per hour in May 2019, May 2020, and May 2021. The respective system intensities were 0.534, 0.360, and 0.492. In the off-peak periods, the average service rates were 19, 20, and 23 persons per hour in July 2029, July 2020, and July 2021. The respective associated system intensities of 0.535, 0.461, and 0.487. From the pooled data for 2019 and 2021, the study recommends that banks operate with an AWT of 6 minutes, 24 seconds, and an AST of 3 minutes. Further, the study established that a bank could work with an optimal four servers with an AST of 2 minutes, 35 seconds (a service rate of 20 people per hour), and achieve a moderate average service intensity of 0.552.
ASSESSMENT OF QUALITY OF SHALLOW WELLS WATER IN CHUKA SUB-COUNTY, KENYA
(Chuka University, 2020-12) Rugendo, Edith Mwende
Groundwater from shallow wells is an important source of water for domestic and agricultural uses in Chuka Sub-County. However, most shallow wells in Chuka Sub-County are undocumented because approval is not required to sink a shallow well. Groundwater from these shallow wells is therefore susceptible to contamination by both geogenic and anthropogenic sources. This study was conducted to determine the quality of shallow wells water in Chuka Sub-County. Samples were collected from twenty shallow wells in Chuka Sub-County during the dry and wet seasons. The temperature, pH and conductivity were determined in situ using a conductivity meter. The concentration of cations in the water samples was determined using an Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) system. The concentration of chloride and nitrate ions in the water samples were determined using the argentometric and the spectrophotometric method, respectively. The concentration of sulphate ions was determined using a turbidimetric method while the concentration of phosphate ions was determined using a colorimetric method. The data obtained were subjected to ANOVA to test the significance differences using R-3.5.2. Mean comparison was achieved through LSD. The temperatures of the waters were significantly higher during the dry season. The pH of water in most shallow wells during the wet season was within the limits set by KEBS and WHO. However, shallow well water at Karandini (T15) was highly acidic (pH of 3.95) during the wet season. During the dry season, the shallow well waters were slightly acidic (4.42 - 6.44) except for the shallow wells at Ndagani market (T11), whose water was alkaline (pH = 8.75). The shallow wells water at site T11 had remarkably higher conductivities than the other shallow wells in the study area during both the wet (1150 μs/cm) and the dry (1208 μs/cm) seasons. The concentrations of macro-cations (Ca2+ and Mg2+) were higher during the dry season. The concentrations of the trace and toxic cations differed significantly across sites and seasons but were within the limits set by KEBS and WHO. The concentrations of anions (NO3-, SO42-, Cl- and PO43-) were within the limits set by KEBS and WHO for portable water. Groundwater from most shallow wells in Chuka Sub-County is generally safe for domestic uses but regular monitoring for quality is recommended because, the concentration of nitrate in several wells during the dry season was within the range that causes chronic health effects including colorectal, ovarian, thyroid, kidney and bladder cancers.
CHARACTERIZATION AND SCREENING OF ANTIBACTERIAL PROPERTIES OF Actinomycetes FROM RIVER TANA AND LAKE ELEMENTAITA, KENYA
(Chuka University, 2023-04) SHIKUKU BONFACE OLOO
The increased prevalence of bacterial infections has been a major challenge to human with devastating high mortality and morbidity rates. This situation has been worsened by increasing antibiotic resistant strains of pathogenic bacteria, reduced effectiveness of antibiotics in the market, and the emergence of new bacterial infections. This study aimed at identification of antibacterial Actinomycetes species using biochemical and molecular methods, screening for their antibacterial secondary metabolite and determination of effect of pH, fructose, sucrose, urea and sodium nitrate on their antibacterial activities. The experiments for this study was laid out in Complete Randomized Design and replicated thrice to determine the difference between the inhibition zones (mm) of isolates against the tests organisms and effects of different levels of pH, sucrose and fructose on antbacterial properties of isolates. The resultant data ( zones of inhibition in millmetres) was analysed using One Way Analysis of Variance and Kruskal Wallis test in SAS version 9.4. A total of six antibiotic producing Actinomycetes species were isolated from river Tana and lake Elementaita and identified through morphological, biochemical and molecular methods.There was a significant (p<0.05) different antibacterial activity of Actinomycetes isolates against Staphylococcus aureus, Salmonella typhi and Escherichia coli. The thin layer chromatography profiling for secondary metabolites in extracts revealed a total of 13 different spots with each having a unique retardation factor. The GC-MS analysis of the extracts revealed 140 different metabolites which have been documented to have antibacterial properties from the six Actinomycetes isolates. There was a significant (p<0.05) effects of different levels of pH and concentration of fructose, urea and sodium nitrate on the antibacterial activity of Actinomycetes isolates against Escherichia coli. The study has revealed different secondary metabolites in unique combinations across the six Actinomycetes isolates with antibacterial activities against Staphylococcus aureus, Salmonella typhi and Escherichia coli. The findings of this study can help in developing new or alternative antibiotics that can be used for treatment of pathogenic and resistant bacteria.
Characterization of clay samples from Murang’a, Nyeri, Embu and Tharaka Nithi Counties for adsorption of cadmium for water purification
(Chuka University, 2025) Thuo Maryrose Wandia
Heavy metal pollution, particularly cadmium (Cd² ), remains a critical environmental challenge threatening water quality, aquatic ecosystems, and human health. Cadmium is widely introduced into aquatic systems through industrial effluents, agricultural runoff, and urban discharges. This study investigated the adsorption potential of locally available clay minerals as cost-effective and sustainable remediation materials. Clay samples were collected from Gakoigo (S), Mukurwe-ini (2A) Gakindu K1, Karurina (K2) and Mbogoni (M). The clay samples were characterized using Atomic Absorption Spectroscopy (AAS), X-ray Diffraction (XRD), and Fourier Transform Infrared Spectroscopy (FTIR). The results from elemental analysis and ANOVA revealed difference in concentrations of iron, magnesium, sodium, and aluminum across the counties, explaining the calculated F-statistics 2.83 (p = 0.048), 3.01 (p = 0.035), 4.51 (p = 0.020), and 5.22 (p = 0.011), respectively. These constituents are vital as they assist, particularly, the samples from Mbogoni (M) and Gakoigo (S), in boosting cadmium (Cd²) adsorption. On the contrary, calcium and potassium were seen to have less influence, evidenced by their F-statistics of 2.45 (p = 0.068) and 2.13 (p = 0.080), respectively. Physicochemical water quality analysis was done from 12 rivers sites within Nairobi County, Kenya. Turbidity ranged between 2.75–95.67 NTU, exceeding WHO’s 5 NTU guideline in urban rivers due to runoff and effluent discharges. Electrical conductivity (556–1123 µS/cm) surpassed WHO limits across all sites, confirming high ionic loading, while dissolved oxygen (0.51–3.06 mg/L) was critically low, pointing to severe organic pollution. Total suspended solids (12–247 mg/L) and TDS (362–736 mg/L) were elevated in urbanized sites, further degrading aquatic health. Cadmium concentrations (0.0105–0.0498 mg/L) consistently exceeded WHO (0.003 mg/L) and KEBS (0.01 mg/L) standards, with highest levels in industrially impacted rivers, highlighting risks of bioaccumulation and human exposure. Batch adsorption studies demonstrated that pH was a key determinant, with maximum efficiency at neutrality (pH 7, 99.81% removal by K1), while acidic conditions reduced removal due to proton competition. Contact time experiments showed rapid uptake within 20 minutes, with equilibrium achieved at 40 minutes (69.16% removal by K1). Adsorbent dosage showed optimum performance at 0.1 g (99.72% removal at 8 ppm), though higher dosages reduced efficiency due to particle aggregation. Desorption confirmed strong Cd binding, indicating chemisorption via ion exchange and surface complexation. Agitation improved uptake by minimizing mass transfer resistance, with peak efficiency (92.29% by K1) at 400 rpm. Temperature exerted a negative effect, with maximum adsorption at 25 °C (97.52% by K1), confirming exothermic behavior. Isotherm modeling revealed Langmuir’s model (Qmax = 2.06 mg/g, KL = 5.44 L/mg, R² = 0.77) better fit the data compared to Freundlich (R² = 0.67), suggesting monolayer adsorption on homogeneous sites. Kinetic modeling indicated pseudo-second order (R² = 0.8496) best described the process, implying chemisorption. Thermodynamic evaluation showed that cadmium adsorption on the clay adsorbent was endothermic, with a positive enthalpy change (ΔH = 17,936.42 J/mol) and a positive entropy change (ΔS = 64.18 J/mol·K). Gibbs free energy (ΔG) remained negative across all temperatures (ΔG = 1.21 to -1.27 kJ/mol), confirming spontaneous adsorption at higher temperatures.
A CONVOLUTIONAL NEURAL NETWORKS AND SUPPORT VECTOR MACHINES HYBRID MODEL FOR NUMBER PLATE RECOGNITION
(Chuka University, 2022-03) Kibaara, Peter
ABSTRACT Automatic Number Plate Recognition (ANPR) systems are applied in many fields such as automatic electronic toll collection, car park management and access control, logistics and vehicle tracking, traffic law enforcement and crime resolution amongst others. Motion blur, plate orientation, lighting changes and image noise severely lower the detection speed and recognition accuracy of these systems. The incorporation of machine learning algorithms in ANPRs has seen Convolutional Neural Network (CNN) being used to develop ANPR models with improved performance in license plate detection. CNNs are best suited for image data where the number of features is large such as license plate detection. This is attributed to their design architecture which enables them to perform feature extraction automatically. However, their speed of execution is slow as the model has to learn a lot of features. Support Vector Machine (SVM) is a supervised machine learning algorithm suitable for classification and regression problems with datasets that have a small number of features. It doesn’t scale up well for large datasets with many features. It has demonstrated high speed and accuracy when used for classification in small datasets such as character recognition. The final stage in ANPR is a character recognition phase and involves few features. These two algorithms have been deployed independently, however the concept of combining the two algorithms for ANPR models remains highly unexplored. The research therefore combines the two models (CNN and SVM) to come up with an efficient hybrid ANPR system with improved number plate recognition accuracy. The two models were developed using a deep cascade framework; a CNN with a SoftMax classifier and a hybrid CNN with a SVM classifier. The Universidade Federal do Paraná (UFPR-ALPR) dataset was used to train validate and test the models. Recognition accuracy, precision, recall and F1 score metrics were used to evaluate the model. The hybrid CNN-SVM model had a recognition accuracy of 91.25% against 89.07 % from the pure CNN model. The weighted average precision, recall, and F1-score of the hybrid CNN-SVM was 92%, 91% and 91% respectively, which was better compared to that of pure CNN. The hybrid model was tested for external validity using the Smart Sense Laboratory (SSIG) dataset. The hybrid CNN-SVM model had a recognition accuracy of 91% against 89 % from the pure CNN model. The weighted average precision, recall, and F1 score of the hybrid CNN-SVM was 91%, 91% and 91% respectively which was better compared to that of pure CNN, which had 90%, 89% and 89% respectively.
Determination of micronutrients, heavy metals and Proximate analysis of selected indigenous vegetables in Kirinyaga East Sub-County, Kirinyaga County
(Chuka University, 2025) Maina Janet Njeri
Socio-economic changes that have taken place in Africa have influenced peoples eating habits in both rural and urban set-ups. Indigenous vegetables are important for food insecurity, malnutrition reduction and therapeutics in sub-Saharan African countries. In Kirinyaga County, indigenous vegetables are underutilized or neglected due to some nutritional content are known and others unknown. Limited data exist on the precise levels of key micronutrients (e.g. iron, zinc, magnesium) in specific indigenous vegetables cultivated in Kirinyaga East Sub-County. Variability in nutrient content due to farming practices, soil types, and climatic conditions in the region has not been comprehensively studied. Leaves are the most preferred parts of indigenous vegetables for consumption. Although they have nutritional benefits, there is a need to determine the safety levels due to toxic metals in vegetables contaminated with pesticides, heavy metals and toxins leading to failure of certain organs of the human body. The study aimed to determine levels of micronutrients (calcium, iron, magnesium and zinc), heavy metals (lead and cadmium) using AAS (atomic absorption spectrometer) using and proximate analysis (ash content, moisture content, crude fat, protein content, carbohydrates and crude fiber) of selected African indigenous vegetables (African nightshade, Spider plant, Vine spinach and Pumpkin leaves) in Kirinyaga east sub county. The results revealed that African indigenous vegetables are rich in essential micronutrients. Pumpkin leaves had the highest calcium levels (14,070.81 mg/kg), spider plant showed the highest iron concentration (233.53 mg/kg), African nightshade recorded the highest zinc content (483.33 mg/kg), while vine spinach was richest in magnesium (570.87 mg/kg). Proximate analysis indicated that spider plant and African nightshade contained higher protein levels (up to 17.9%), while moisture content ranged from 82–91%. Crude fat levels were consistently low, confirming African indigenous vegetables as nutrient-dense but energy-light vegetables Cadmium and lead concentrations varied across species and locations, with African nightshade and vine spinach showing relatively higher levels. However, all values remained within WHO/FAO permissible limits, indicating that the vegetables are safe for human consumption in terms of heavy metal contamination. African indigenous vegetables have high nutritional potential and can be promoted as affordable dietary sources of essential minerals and protein to combat malnutrition.
Determination of water quality of Nguue spring and river Mutonga in Tharaka-Nithi, Kenya and evaluation of corn-cob derived carbon powder in remediation of contaminated water
(Chuka University, 2015) Mwenda Bertha Kinya
Water quality is a pressing global concern, since water pollution negatively impacts water bodies and poses severe threats to both human and aquatic life.The aim of this study was to, determine physico-chemical and bacteriological parameters of Nguue spring and river Mutonga, and compare to the limits set by WHO and KEBS. The performance of low-cost adsorbent in removal of zinc and iron from contaminated water was also evaluated. Sampling was done each at six points along the river and the spring approximately 500 metres apart, in the dry and wet season in the months of September and November 2024. The physical parameters of water such as temperature, pH, DO, TDS and EC were measured using multiparameter. Total hardness was estimated by titrimetry. Anions of NO3 - and PO4 3- were determined by UV spectrophotometric method. The heavy metals of Zn2+ and Fe3+ in water samples were determined by Atomic Absorption Spectrophotometer. In the dry season, River Mutonga recorded a temperature between 25.9-26.6 °C, pH of 7.1-7.4 , electrical conductivity was 172.8-202 µS/cm, total dissolved solids 0.838-0.886 mg/L , dissolved oxygen, 3.19-3.25 mg/l, however, total hardness 0.838-0.886 mg/L, nitrate concentrations 16.57-19.35 mg/L, while phosphate was 1.95-2.12 mg/L. Nguue Spring during the dry season exhibited a temperature of 25.9-26.5 °C, pH was 5.21-6.58 indicating slight acidity, electrical conductivity of 147.6-193.6 µS/cm and total dissolved solids 0.552-1.2 mg/L, total hardness wa 58-160 mg/L, well Similar to Mutonga River, nitrate levels 16.83-19.47 mg/L. In the wet season, River Mutonga recorded a lower temperature of 21 °C compared to the dry.4 and 6.5-8.5 respectively, indicating increased acidity in sampling point M1. Electrical conductivity 57.2-60.4 µS/cm and total dissolved solids 31.3-36.6 mg/L were markedly lower than in the dry season, reflecting dilution effects of rainfall. Dissolved oxygen was 8.72-8.92 mg/L increased substantially and was well above the WHO minimum standard 4.0 mg/l. Total hardness decreased to 87.3-122 mg/L but remained within permissible limits. Nitrate levels dropped to 7.25-12.35 mg/L, now falling within KEBS standards which is 10 mg/l, while phosphates was 2.01-2.29 mg/L remained above WHO limits 0.5 mg/L. Nguue Spring in the wet season showed a temperature of 20.5-21 °C, pH was4.210-5.724 was consistently below both WHO and KEBS ranges, suggesting acidic conditions. Electrical conductivity was 37.8-55.6 µS/cm and total dissolved solids 27.7-59.5 mg/L decreased compared to the dry season, reflecting rainwater dilution. Dissolved oxygen was 8.58-8.86 mg/L was significantly elevated and met WHO standards, total hardness was 22.6-84 mg/L remained within permissible limits. Nitrate concentration was 7.8-14.65 mg/Lwas marginally above the KEBS guideline, while phosphate was 1.95-2.23 mg/L exceeded WHO standards but was acceptable under KEBS. Batch adsorption was carried out by varying the parameters of temperature, pH, intial concentration, contact time and adsorbent dosage. The total coliforms count in Mutonga were 11-460 and 36-1100 MPN per 100 ml in dry and wet season repectively and exceeded KEBS and WHO limits. In Nguue spring the toal coliform counts were 36-1100 and 43-˃1100 MPN per 100 ml in dry and wet season respectively exceeding KEBS and WHO limits. Adsorption of zinc and iron on CCAC and CCC was successfully represented by Freundlich and Lngmuir isotherm models. Adsorption of zinc on CCAC and CCC was best described by Freundlich with KF=2.35 mg/g, n=1.387, R2=0.9359 and KF=116.84mg/g, n=0.1634, R2= 0.9497 respectively indicating a favourable multilayer adsorption on heterogenous surface. Adsorption of iron on CCAC and CCC also Freundlich gave a reasonable fit with KF=1.1498mg/g, n=0.5826, R2=0.90703 and KF=1.8034mg/g, n=0.9063, R2=0.97692 respectively
Determination of water quality status, remediation and synthesis of multiwalled carbon nanotube/hydrochar composite in river Kathita, Meru, Kenya.
(Chuka University, 2025-10) Gitonga, Glory Gatwiri
Freshwater is required for life as well as several other activities such as human consumption, agricultural processes and industrial processes. Heavy metals are absorbed into water bodies through various pathways have adverse effect on the liver, kidneys, lungs, brain, and bones. This study sought to determine the physiochemical parameters, bacteriological, heavy metals and synthesize and characterize a composite of multi-walled carbon nanotubes (MWCNTs)/hydrochar of tea waste and utilize it for removal of Cu2+ ions from river Kathita. Tea wastes were collected from Meru tea factories and MWCNTs purchased from reputable suppliers. The tea waste samples were washed, dried and the MWCNTs, functionalized with sulfuric-nitric acid. The MWCNTs/hydrochar composite was characterized using FTIR and XRD. The water samples and sediments were collected in two seasons from River Kathita using grab method, transferred to 500 ml plastic bottles and transported to Chuka University Laboratory for analysis in a cooler box at 4oC. Standard methods for determining physicochemical and bacteriological parameters were employed and batch adsorption experiments were conducted to study the effect of pH, temperature, contact time, speed, initial metal concentration and dosage on adsorption of Cu 2+ ions. The remaining copper (II) ions concentration was determined using AAS. The water turbidity, electrical conductivity, dissolved oxygen, nitrogen and phosphorous content, TDS and TSS were found to be high during the wet season compared to dry season. pH registered small changes to more neutral-alkaline during the wet season. The pH, temperature, conductivity, TDS, phosphorus and nitrates were within the guidelines by WHO in both seasons. Turbidity and TDO exceeded the WHO and KEBS guidelines in both seasons which indicated high amounts of organic matter. The total coliform counts and faecal coliforms during wet season were beyond proposed standards of safe recreational or agricultural use. This was due to extensive runoff as well as sewer discharge into the water during the rainy season. (MWCNTs) and hydrochar from tea waste composite had a big removal efficiency of 96.5% under optimum conditions. From the kinetic modeling, the adsorption process obeyed pseudo-second order reaction (R² = 0.96683) trend showing that the process is chemisorption driven. There was greater fit of the adsorption equilibrium data on Langmuir isotherm model (R² = 0.99529) indicating monolayer surface coverage of Cu²⁺ ions by homogenous surface. There was a high regeneration potential of the absorbed Cu²⁺ ions being efficiently desorbed. The MWCNTs/hydrochar composite is highly effective and sustainable since it can be recycled multiple times without the loss of functionality on a significant scale. The addition of Pb²⁺ ions did not drastically influence the removal of Cu²⁺ while addition of Cd²⁺ ions and the binary solution of Pb²⁺ and Cd²⁺ caused a significant decrease in the efficiency of copper adsorption. The MWCNTs/hydrochar composite is generally a sustainable option for enhancing the quality of the polluted rivers' water.
FACTORS AFFECTING ADOPTION OF MANURE ON BANANA YIELDS IN SMALLHOLDER FARMS IN MAARA SUB COUNTY, THARAKA NITHI COUNTY, KENYA
(Chuka University, 2022-09) Kimetto, Jerono
ABSTRACT Banana (Musa ssp) is a widely distributed fruit and which is contributing greatly towards food security in the developing countries. In Kenya, banana is among the major food and cash crop produced by smallholder farmers as a source of income and food security. However, it has been associated with low productivity and income. Currently, banana production in Kenya is 14 t/ha-1yr-1, which is below the global average of 20.5 t/ha-1 yr1. The low production has been attributed to various factors such as poor agronomic practices, low soil fertility, poor markets, lack of farming capital and sociodemographic factors. Despite studies on most of these factors, information on dynamics of socio-economic factors on banana farming by smallholder farmers is ever changing due to change in climate and lifestyles. Therefore, there is need to continuously monitor and study the effect of these factors on productivity and income of banana farming. The study, therefore determined the effect of manure adoption on banana production in smallholder farms in Maara Sub County, Tharaka-Nithi County. Descriptive research design was used in the study. The study targeted 34,779 smallholder banana farmers. A structured questionnaire, open and closed ended, were used to collect the data. Data was collected on demographic socio economic, institutional factors and banana production. Data obtained was analysed using the SPSS version 26. Descriptive statistics were employed in the presentation of the results. The study revealed that majority of the banana farmers are above 53 years and majority (54.8%) of the farmers derived their seedlings from their own suckers. About 83.8% of the farmers have adopted manure while 16.2% of the respondents have not. The common variety planted by the farmers is Kampala represented by 30.73%. About 29.7% banana farmers own land sizes between 0.5-1.0 ha of land. The majority (97.3%) of the farmers privately owned their lands while 2.7 3% of the respondents leased the lands for growing bananas. It was established that majority (88.0%) of the adopters received extension services while adopters who had not received any extension services were being represented by 8.0 %. Majority of the farmers who belonged to a farmer group and were adopters of manure being represented by 82.0% respondents while farmers who and were adopters and did not belong to any farmer group were represented by 14.0%. The study sought to determine the socioeconomic factors that affect adoption of manure in smallholder farms in Maara Sub County. Logistic regression model was used to find out whether gender, age, highest level of education of decision maker, access to extension service, participation in a farmer group, labour and land size were significant in the adoption of manure. Education level of decision maker p = 0.007, Gender p = 0.000, land size p = 0.000 and participation in farmer group p = 0.003 and extension services p = 0. 027 were the factors that were found to significantly affect adoption of manure. Multiple regression model was carried out to determine the impact of adoption of manure on banana yield. The result showed that adoption of manure had an association with banana yield and was statically significant at p = 0.000. Most of the respondents were found to be literate. Therefore, illiterate farmers should be enlightened as education boost a farmer’s ability to decode information. Awareness should be created to encourage any member who has not registered to any group as is through such groups the information is disseminated. Extension services should also be well strengthened. The study recommends farmers to adopt manure as a way of increasing banana yields.
FIRST PRINCIPLES STUDY ON EFFECTS OF PRESSURE AND NIOBIUM DOPING ON STRUCTURAL AND ELECTRONIC PROPERTIES OF MOLYBDENUM DISULFIDE MONOLAYER
(Chuka University, 2023-10) MUTAVA GABRIEL MUTINDA
Semiconductor materials are dominant in the fabrication of electronic devices. Unlike metals, the presence of an energy band gap makes them ideal for application in optoelectronics nanostructures. Silicon was the most preferred 2D material to be used, but due to its limitations, for example, quantum tunneling effects, graphene was preferred to silicon. However, graphene has no bandgap, and since the bandgap property is very useful in electronics, research is ongoing to replace silicon and graphene with Transition Metal Dichalcogenides (TMDs). TMDs make nanostructures easily with adjustable energy bandgap, hence applicable in optoelectronics. They exhibit various unique optoelectronic characteristics, attracting interest due to distinct features from bulk predecessors and have bandgap characteristics between 1.80 - 2.30 eV, which can be tuned to fabricate Field Effect Transistors (FET) and other optoelectronic devices. Molybdenum disulfide has sparked attention among TMDs because of the potential of tuning the band gap. Up to date, research on the effects of impurities and pressure on the energy band gap of molybdenum disulfide have been studied, resulting in energy band gaps falling between 1.3 - 1.55 eV. There is need to reduce the value of the energy band gap further so as to make the semiconductor applicable at lower energies. Therefore, this study combined the ionic doping and pressure application on MoS2 in an attempt to narrow the energy band gap to a lower value that could accommodate majority of radiations falling under electromagnetic spectrum. Structural optimization of MoS2 monolayer and niobium doped MoS2 was done using the Density Functional Theory (DFT) method as implemented by the Quantum ESPRESSO simulation package. The study utilized PBE-GGA method of approximation and the number of k-points utilized were 8 x 8 x 1. The structure was optimized to a cell dimension of 3.175 Å for 𝑎 = 𝑏 parameters. A vacuum height of 14.971 Å served to minimize artificial interactions between periodic layers. A 4 x 4 x 1 supercell was modelled and had optimized dimensions of 12.57 Å for 𝑎 = 𝑏 and a vacuum height of 14.971 Å. Its band gap energy was found to be 1.70 eV. Upon 8.33% niobium doping of the 4 x 4 x 1 MoS2 supercell, the energy band gap reduced to 1.375 eV. A pressure in the range of −2.852 GPa to 6.832 GPa was applied, which corresponds to strains ranging from 2. 52 % to -2.50 %. The energy band gap for undoped MoS2 monolayer reduced from 1.70 eV to 1.40 eV at a pressure of -2.852 GPa. The energy band gap for the 8.33% Nb doped MoS2 monolayer narrowed from 1.375 eV to 1.25 eV at a pressure of -5.166 GPa. The combined effect decreased the band gap of MoS2 monolayer from 1.70 eV to 1.25 eV. This study concludes that the combined effect of Nb doping and pressure on the structure of molybdenum disulfide can improve its electronic properties by reducing its energy band gap. This property makes it useful in fabricating optoelectronic devices which can work well at lower energies.
Formulation of Schrödinger Equation Using The Hilbert Space Operators Approach
(Chuka University, 2019-09) Mbatha, Elizabeth
Operators in Hilbert space have properties which are useful in the study of mathematical abstract areas such as approximation theory, Banach Fixed point theory, the spectral theory as well as Quantum Mechanics. Schrödinger equation is a fundamental entity with many applications in Quantum Mechanics. This equation was initially derived by applying the knowledge of electromagnetic wave function and Einstein theory of relativity. Later, it was derived by applying the knowledge of Newtonian mechanics. It was also derived by extending the wave equation for classical fields to photons and simplified using approximations consistent with generalized non-zero rest mass. However, from the existing literature no study has been done on deriving Schrödinger equation using properties of Hilbert space operators. In this study, Hilbert space operators that include unitary operators, self adjoint operators and compact operators, norms of linear operators, Hilbert Schmidt operator, normal operators together with Lebesque Integral, Neumann Integral and spectrum are used in place of the existing concepts of electromagnetic wave function, Einstein theory of relativity and approximation consistent with generalized non zero mass to derive the Schrödinger equation. Furthermore, this study has established the correlation between the electromagnetic wave function and Einstein theory of relativity in relation with Hilbert space operators. Application of Hilbert space operators on Quantum observables such as position, momentum and energy of a particle has been done in these study. The derivation of Schrödinger enhances equation and its application using Hilbert space operators have enhanced a better understanding of the concept of Schrödinger equation. The results of this work will be useful in quantum mechanics as well as in mathematical operator theory.
IMPACTS OF SHORELINE CHANGE ON THE NEARSHORE MARINE ENVIRONMENT AT GAZI BAY, KENYA; BETWEEN 1989 AND 2020
(Chuka University, 2023-10) MWANGI PAULINE NYAMBURA
Coastal zones are dynamic environments influenced by both human and natural processes. In the current study, the objectives were to estimate change in shoreline at Gazi bay between 1989 and 2020, to identify the spatial-temporal changes of the nearshore marine environment; particularly on mangrove forests and to establish hotspot areas of shoreline change. The study applied both longitudinal and ecological research design. Digital Shoreline Analysis System (DSAS 5.0), a software within ArcGIS Platform computed change statistics along the study area over the study period. Kalman filter model was used to project future shoreline positions. Supervised, and unsupervised classification methods were used in detecting vegetational change. The relationship between shoreline change and mangrove cover change was examined using the Pearson Correlation coefficient. The average End Point Rate (EPR) of shoreline change at Gazi bay was estimated at -1.38 m/y, with the northerner sections of the western creek showing an accretion rate of 2.38 m/y. At least 88.62 hectares of the mangroves had been affected by the sedimentation processes, representing 55% of mangroves in the study site. A hotspot area exhibiting a change of -4.99m/y was observed at the opening of the Mkurumudzi River, where sandspits and sandbars had formed. Other hotspots areas were at the site with introduced artificial rocks to serve as gabions, fish landing sites, and at the northern side of western creek that had enhanced sediment accretions killing mangroves. A negative correlation between shoreline change and mangrove cover loss was observed, though not statistically significant (r=-0.536, p=0.273, α=0.05). Assessing the dynamics and vulnerabilities of the coastal zones is very crucial in understanding sustainable coastal development and management. These findings provide valuable insights on shoreline changes that could contribute towards integrated coastal zone management strategies for the area.
INCIDENCE AND PREVALENCE OF FUSARIUM WILT AND PHYTOCHEMICAL ANALYSIS OF CRUDE EXTRACTS OF Tithonia diversifolia (Hemsl.) A.Gray AND Kigelia africana (Lam.) Benth AND THEIR ANTIMICROBIAL ACTIVITIES AGAINST Fusarium oxysporum IN TOMATOES
(Chuka University, 2020-12) Awere, Collince Omondi
Kenya is one of the leading countries in Africa in tomato production. Production of tomato is 14% of the total vegetable and 6.72% of the horticultural crops produced in the country. It is a source of food, foreign exchange earnings and source of employment and income. The major factor that reduces the growth and yield of tomato production in Kenya are pathogenic microorganisms. For instance, Fusarium oxysporum is among the fungal pathogens that destroy the xylem of the plant hence causing Fusarium wilt due to poor transportation of water to various parts of the plant. Besides, it persists in the soil environment for a long period thus continuously infecting healthy plants grown in the site. The management practices that are mostly used to control the pathogen are ineffective and environmentally unfriendly. Therefore, plant products with antimicrobial properties present an affordable alternative solution to control such persistent pathogens. The objective of this study was to determine the incidence and prevalence of Fusarium wilt and the phytochemical composition of Tithonia diversifolia and Kigelia africana and their antimicrobial activity against fungal pathogen F. oxysporum in tomatoes. Tithonia diversifolia and Kigelia africana plants were selected because of their wide medicinal use, distribution and availability. A preliminary survey was carried out in Mwea, Kirinyaga County which is among the most common areas where tomatoes are grown. Questionnaires were used to evaluate the farmers` knowledge, perception and management practices of Fusarium wilt disease. A total of 80 respondents were interviewed. K. africana and T. diversifolia plant samples were collected for phytochemical analysis. The samples were ground into a fine powder and extracted using water. Phytochemical screening of the crude extract was done. Soil was used for F. oxysporum pathogen isolation. Antimicrobial test disc soaked with plant extract was placed on to the media cultured with F. oxysporum and incubated at 28 oC for a week to allow growth. Analysis of the collected data was done using SAS version 9.4 for analysis of variance and further subjected to a post adhoc test with 𝛼 = 0.05 being considered significant. The results showed that the Rio Grande was the tomato variety widely grown; the preference for this variety was attributed due to its high marketability, high production, high quality, and early maturity. From the response, 92.5 % of the farmers had seen the symptoms of the pathogen while the rest had not seen the symptoms of the pathogen in tomatoes. The application of chemicals was widely used to control the pathogen, which contributes to environmental pollution. Screening of the plant extract revealed the presence of tannins, alkaloids, flavonoids, saponins, terpenoids, and glycosides. Each of the plant extract used had antimicrobial activity against F. oxysporum; this was due to the presence of phytochemicals that had an effect on the growth of the pathogen. K. africana exhibited the highest zone of inhibition while T. diversifolia had the lowest zones of inhibition. When each crude extract was used singly and in combination against the F. oxysporum, the zone of inhibition was found to be statistically significant at P< 0.05. The combined crude extract showed an increased antimicrobial activity against F. oxysporum. The results provide a potential application of the crude extract as an antifungal agent against F. oxysporum. It also provides scientific evidence that K. africana and T. diversifolia extract possess antifungal activity that can be used as a broad-spectrum in managing microbial diseases.
INDUCTION OF SYSTEMIC ACQUIRED RESISTANCE AGAINST Ralstonia solanacearum IN IRISH POTATO
(Chuka University, 2023-10) ATIENO MARGARET FAITH
Irish potato (Solanum tubesorum) is an economically important crop throughout the world with large-scale production and consumption. Irish potato is rich in carbohydrates, vitamins and minerals, especially iron, magnesium and potassium. Irish potato production has been plagued by constraints such as lack of certified seeds, pests and diseases. Bacterial wilt caused by Ralstonia solanacearum is the major bacterial disease of potato resulting to 50 - 100% crop losses. Management of R. solanacearum is difficult since it has a wide host range and the fact that it is a soil borne pathogen. Several methods including biocontrol, chemical control, cultural practices, host resistance and phytosanitation have been used to manage R. solanacearum. However, there is no method that has been found to effectively control the disease but a combination of different methods have been reported to reduce the impact of the disease. Inducing systemic acquired resistance is another alternative to control bacterial wilt. Systemic acquired resistance is the response of a plant to a pathogen attack and confers long-lasting protection against a broad spectrum of microorganisms. Thus, this study determined the induction of systemic acquired resistance against bacterial wilt in Irish potato through injection of attenuated pathogen and non-pathogens. The ability of Escherichia coli, Saccharomyces cerevisiae and attenuated R. solanacearum to induce systemic acquired resistance against bacterial wilt of Irish potato was tested in the greenhouse. Attenuation assay was conducted using four levels of formaldehyde concentrations and incubation duration for attenuation of R.solanacearum using randomized complete block design. Randomised complete block design was also used to evaluate in-vivo effect of different treatments and varieties on R. solanacearum in the greenhouse. Bacterial wilt symptoms were observed and a rating scale of 0 - 6 was used to score for disease severity. Leaves of the treated plants were collected for salicylic acid quantification in the laboratory. Disease severity, colony count, amount of salicylic acid and tuber yield data were analysed using statistical analysis software version 9.4 to determine induction of systemic acquired resistance. Significant means were separated using Least Significant Difference test at 5% probability level. Result from this study showed that there was statistically significant effect (p < 0.05) of formaldehyde concentrations and incubation duration for attenuation of R. solanacearum. The results from attenuation of R. solanacearum showed that colony count ranged from 0.67 colony forming units (in 0.6% formaldehyde concentration and incubation duration of attenuation of two hours) to 233 colony forming units (in 0% formaldehyde concentration and incubation duration of attenuation of two hours). There was significant (p < 0.05) treatment effect on disease severity, salicylic acid levels and tuber yield of Irish potato. Higher disease severity was recorded in S. cerevisiae treatments (80%) followed by E. coli treatments (40%) while least disease severity was recorded in attenuated R. solanacearum treatments. Attenuated R. solanacearum induced the highest level of salicylic acid (3409.64 mg/kg of Irish potato leaves) while R. solanacearum induced the lowest (1222.74 mg/kg of Irish potato leaves). Irish potato plants with attenuated R. solanacearum treatment had the highest yield of tubers (0.5772 kg/plant) while those treated with S. cerevisiae treatments had the lowest (0.4840 kg/plant). This study concluded that attenuated R. solanacearum and E. coli triggered systemic acquired resistance in Irish potato plants thereby increasing the levels of salicylic acid, which reduced the negative impact of the disease in the plants. Induction of systemic acquired resistance is a viable method for induction of resistance against bacterial wilt in Irish potato. The study recommends the identification of the specific molecules involved in induction of resistance from attenuated R. solanacearum and E. coli and their utilization in the control of bacterial wilt in order to mitigate the huge loses that are caused by this disease.
LEVELS OF SELECTED PHTHALATES FROM WASTEWATER TREATMENT PLANTS IN LAKE VICTORIA CATCHMENT AREA AND THEIR ADSORPTION ONTO WATER HYACINTH BIOCHAR
(Chuka University, 2020-12) OGORA, ELKANAH NYAKWAMA
Endocrine disrupting chemicals (EDCs) disturb the endocrine system’s functionality causing negative effects on health in an organism and its progeny. They can interfere with natural hormone cycles in humans or animals, potentially affecting metabolism, development, reproduction and growth. Phthalates are among the many examples of EDCs, which have been used as plasticizers for longtime around the world. Due to their extensive usage, they are found in many surface waters, sludge and waste waters. The occurrence of phthalates in water, and their exposure to non-target organisms cause adverse effects such as congenital anomalies, endocrine disruption and chronic toxicity. This study determined residual levels of three phthalates namely; dimethyl phthalate (DMP), benzyl butyl phthalate, (BBP) and bis(2-ethylhexyl) phthalate (BEHP) in wastewater sampled from wastewater treatment plants (WWTPs) of Nyalenda, Homabay and Kisii during wet and dry seasons. The wastewater samples were extracted and cleaned by solid phase extraction cartridges (SPE) ready for high performance liquid chromatography (HPLC) for quantitative analysis. Most of the sites sampled had detectable levels of DMP, BBP and BEHP in wastewater. High concentrations were detected during wet season compared to dry season in all sampled sites. Nyalenda WWTP recorded the highest concentrations of phthalates than Homabay and Kisii WWTPs. The concentrations of all selected phthalates were recorded highest at the inlet sampling points from all WWTPs, in both seasons sampled. Almost all the selected phthalates were below the limit of quantification (LOQ) at the outlet sampling points of Homabay and Kisii WWTPs in both seasons. The residue levels obtained showed significant differences at 5% confidence limits with zcal for all phthalates in all WWTPs less than the critical value (Zcritical = 1.96). Therefore, the null hypothesis was rejected. Consequently, a cost-effective technique of removing DMP, BBP and BEHP from their solutions using water hyacinth biochar (WHB) as an adsorbent was investigated. A mass of 0.1 g of WHB both before and after adsorption was used for characterization process. Elemental analysis of WHB was determined using XRF (EDXRF), the XRD patterns were obtained using bruker operating with Cu Kά(λ = 1.541nm) and samples scanned in coupled TwoTheta/Theta. The FTIR spectra were obtained between 4000cm-1 and 400cm-1 using Shimadzu type. The adsorption process was done using an orbital shaker agitated at 125 rpm and residual levels determined using the HPLC. The optimum conditions obtained from the adsorption of DMP, BBP and BEHP onto WHB were as follows; equilibrium time was 25 minutes, maximum adsorbate concentration adsorbed at 0.1 g of WHB was 4 mg/L, temperature of 298 K was appropriate and 0.8 g of WHB was effective for the adsorption of above 67% of 10 mg/L of each selected phthalate. The kinetic data fitted the pseudo second order model with regression values for DMP, BBP and BEHP found to be 0.9987, 0.9984 and 0.9986, respectively. The Freundlich model demonstrated to be a good model for fitting the adsorption data, which was attributed to heterogenous distribution of charged functional groups at adsorption sites of WHB’s surface. The calculated thermodynamic parameters, namely; change in Gibb’s free energy (ΔG), change in enthalpy (ΔH) and change in entropy (ΔS) showed that the adsorption process was favorable, exothermic, spontaneous and of a physical type. This was due to the fact that all of them were negative values. Dimethyl phthalate was the most effectively removed by WHB as adsorbent. The removal efficiency decreased with increasing molecular weight of the phthalates. The findings demonstrated that WHB is a good low cost and environmentally adsorbent for removal of phthalates from water.
Modelling and Application of Response Surface Methodology for Optimization of Weight Gain of Eight Weeks Old Kenbro Served With Pumpkin (Cucurbita Pepo L) Seeds Extract
(Chuka University, 2019-09) Kinyua, Charles Mugendi
Extensive use of synthetic growth promoting antibiotics have become a threat to public health. Therefore, there is a need to search for bioactive phytochemicals that have positive effects on immune, growth and appetite status of the chicken. Such bioactive compounds can be obtained from plants. Pumpkin seeds have been found to be a valuable source of protein and bioactive compounds. Mathematical models have been used to study the effect of pumpkin extracts on the weight gain of chicken. However, most of these studies have focused on the levels of the application of pumpkin extract, rather than on optimising the levels of application on the weight gain of the chicken. Optimization is important since it provides information on the amount of pumpkin seed extracts that should be fed to the chicken without wastage. This study was conducted to evaluate the weight gained by the Kenbro chicken served with pumpkin (Cucurbita pepo L) seeds extract and examined the possible combination of the number of weeks and quantity of pumpkin seed extract that can result in maximum weight gain of the Kenbro chicken. The experiment was conducted using Random Complete Block Design at the poultry demonstration unit of Chuka University. Sixty- day old Kenbro chicks were randomly distributed to five treatments which contained 0, 50, 100, 150 and 200 ml of pumpkin seed extracts per litre of water. Each treatment was replicated three times with four chicken per replicate. The birds were fed with the same diets of finisher and starter feeds. The chickens were provided with enough feeds and water ad libitum in the morning at 8 am. The birds were weighed at the beginning of the experiment and thereafter at an interval of three days for eight weeks. Data was analysed using R statistical software. A Response surface model was fitted to the data and subjected to contour plots to characterize the nature of its turning point and to capture the combination of the number of weeks and quantity of pumpkin seed extract that brings maximum weight gain of the Kenbro chicken. The results showed that the average body weight gained was significant (p < 0.05). The birds served with 200 ml pumpkin seed extract for 4 weeks had the highest weight gain. The fitted Response Surface Model indicated that the number of weeks and quantity of pumpkin seed extract together with their interaction significantly (p < 0.05) determined the weight gain of Kenbro chickens. The study found that the quadratic model fitted using the data had an adjusted R-Squared value of 0.78. The optimal weight gain of 0.23 kg was achieved when the number of weeks was 3.18 with 192.40 ml of pumpkin seed extract. The number of weeks, pumpkin seed extract and their interaction play a key role in obtaining maximum weight gain of the Kenbro chicken. These factors should be put into consideration when developing a feeding system for Kenbro chickens. The study also guides the farmers on the optimization of Kenbro chicken production without incurring an extra cost in the input.

Browse

Browsing Faculty of Science, Engineering and Technology (FSET) by Title