Faculty of Agriculture and Environmental Studies

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A Backward Regressed Capsule Neural Network for Plant Leaf Disease Classification
(Heliyon, 2021) Mugo, D. M.; Kenduiywo, B. K.; Too, E. C.
This study investigated the introduction of backward regression coupled with DenseNet features into a Capsule Neural Network (CapsNet) for plant leaf disease classification. Plant diseases are considered one of the main factors influencing food production, and therefore fast crop diseases detection and recognition is important in enhancing interventions. In the recent past, CapsNets have been used for plant leaf disease classification with some success. However, back propagation of signals to earlier layers is still a challenge due to low gradient flow, parameter and computational complexities exist due to lack of feature diversification which leads to poor patterns, and uses only higher level features while all features are necessary for classification. This work therefore adopted DenseNet intuition where a loop connectivity pattern was done in the convolution layer, a technique that made it easier for signals to be back propagated and create a strong gradient flow. The resultant model was able to attain computational and parameter efficiency because feature diversification led to richer patterns hence higher accuracy. The resultant model maintained low complexity as it used both complex and simple features. After feature collected in the convolution layer, backward regression was introduced to select only the features that had significant information to be used by the model, a technique that reduced computation time and reduced characters in the model without the loss of data. This work used the standard PlantVillage (PV) dataset comprising of ten tomato classes with a total of 9080 images and observed 99% accuracy on testing with backward regression and 87% on testing without backward regression.
A Comparative Study of Caffeine Levels in Coffee and Cocoa in Kenyan Supermarkets and Shops
(Pan-African Journal of Health and Environmental Science, 2024-05-20) Alex Muthengi1*, Silas Njiru1 and Juster Mungiria; ; ;
Background: Caffeine is an alkaloid belonging to the methylxanthine family. An overdose of caffeine causes the following side effects: restlessness, nervousness, excitement, insomnia, flushed face, diuresis, gastrointestinal disturbances, muscle twitching, rambling flow of thought and speech, and tachycardia or cardiac arrhythmia. This study aimed to determine the caffeine levels of various brands of coffee and cocoa and enlighten people on the safe and healthy consumption of the two products. Methods: Different brands of coffee and cocoa products were randomly sampled and purchased from supermarkets and shops in Nairobi, Kenya. Five samples of coffee and four brands of cocoa were purchased from a supermarket and taken to the laboratory for analysis. Caffeine was extracted, and quantitative analysis was done using High Performance Liquid Chromatography (HPLC). Results: The study found that coffee has a higher concentration of caffeine than cocoa. Coffee Brand A recorded the lowest level of caffeine with 30.9845 µ g/g, while Coffee Brand C recorded the highest level of caffeine with 426.9639 µ g/g. Among the Cocoa brands, Cocoa Brand B recorded the lowest level of caffeine (2.6367 µg/g), while Cocoa Brand C recorded the highest level of caffeine at 19.03 µ g/g. Conclusion: Therefore, there is a need to reduce coffee consumption per day because caffeine overdose can cause high blood pressure and other illnesses. Cocoa is recommended for consumption since it contains less caffeine per servin
A Survey on Knowledge, Attitude, and Practice about Antibiotic Prescribing and Resistance among Medical Practitioners in Kenya [Version 1; Peer Review: Awaiting Peer Review].
(AAS Open Research, 2022) Kamita, M.; Gitaka, J.; Kimani, R.; Kijogi, C.; Mureithi, D.; Mungai, S.; Mutungi, J. K.
Background Antibiotic resistance is a growing global health threat worldwide and especially in developing countries. Irrational antibiotic prescription as well as lack of the requisite knowledge and awareness of proper antibiotic use are major drivers of antibiotic resistance. In Kenya, although the Ministry of Health has developed antibiotic use guidelines, these guidelines are not widely followed. Antibiotic prescription is, therefore, hugely at the discretion of the clinician. It is thus necessary to understand the knowledge, attitude, and practices (KAP) of antibiotic prescription among medical practitioners in the country. This study aimed to evaluate the knowledge, attitude, and practices (KAP) among antibiotic prescribers in three counties (Kiambu, Nakuru, and Bungoma) in Kenya. Methods This was a cross-sectional study using a self-administered questionnaire. Simple descriptive statistics were used to generate frequencies, percentages, and proportions. Where necessary, univariate analyses such as Pearson’s chi-square were performed to compare proportions for statistical significance. Results From the three counties, 240 respondents recorded their responses: 30% from Kiambu, 34.6% from Nakuru, and 35.4% from Bungoma. The respondents included 19 (7.9%) consultants, 66 (27.4%) medical officers, 135 (56.3%) clinical officers and 20 (8.3%) pharmacists. Of all respondents, more than 90% agreed or strongly agreed that antibiotic resistance (ABR) is a catastrophe worldwide and in Kenya. However, the proportion of the respondents who either agreed or strongly agreed (71.6%) that antibiotic resistance is a problem in their respective health facilities was significantly lower (ρ=0.013). Conclusion This study revealed that most medical practitioners were aware and knowledgeable about antibiotic resistance. However, there was a disconnect with mitigation measures such as active antibiotic stewardship and laboratory analyses to support judicious prescription. There is, therefore, a need for continuous education and stewardship interventions.
Agronomic characterization of soybean and bambara groundnut genotypes grown on different soils of Lake Victoria Basin
(Fundamental and Applied Agriculture, 2020-04-29) Benson O Onyango; Fredrick Otieno Ogolla; ; ;
Neglect and under-utilization of legumes such as soybeans and bambara groundnuts are the reason for increased food insufficiency in the Lake Victoria basin. Diversification of legumes into the cropping systems of Lake Victoria basin ensures protein rich diets and improved soil fertility. This study was carried out to evaluate agronomic characters of two soybean varieties and two bambara groundnut landraces cultivated on different soils of Lake Victoria basin. Seeds of two bambara groundnut landraces; Kakamega Cream (KAKC) and Busia Brown (BUSB) were collected from farmers in Kakamega and Busia counties, respectively in Kenya. Soil sampling was done at selected farmers’ fields with no history of inoculation in Kisumu, Port Victoria, Kendu bay and Karungu within Lake Victoria basin. Screen house experiment was performed in plastic pots with two plants of each cultivar. Randomized Complete Block Design was used. Agronomic characters of BUSB and KAKC landraces differed significant (p<0.05). Bambara groundnuts performed better in Port Victoria and Kendu bay soils than Kisumu and Karungu. Agronomic performance of two soybean varieties SB19 and ‘Safari’ on soils from four sites in Lake Victoria basin was significant (p<0.05). Soybeans yield in Port Victoria and Kendu bay soils was better compared to Kisumu and Karungu soils. Agronomic performance of bambara groundnuts and soybeans were influenced by soil type. Port Victoria and Kendu bay soils resulted in better growth compared to Kisumu and Karungu soils. Landrace KAKC and SB19 had better agronomic performers and are recommended to farmers and seed companies for certified seed production.
The analogy of simple and inter simple sequence repeat markers in the assessment of genetic diversity of pumpkin accessions in Kenya
(Innspub, 2020-09) Kiramana, James; Isutsa, Dorcas Khasungu; Nyende, Aggrey Bernard; ; ;
Pumpkin is found growing in many parts of Kenya although its genetic variation has not been determined using available molecular markers. This study compared SSR and ISSR efficacy in assessing diversity of 139 pumpkin accessions using the multiplex ratio (MR), polymorphic information content (PIC), effective multiplex ratio (EMR), marker index (MI), different (Na) and effective (Ne) alleles, Shannon index (I), expected (He) and unbiased expected heterozygosity (UHe), analysis of molecular variance (AMOVA), clusters and mantel correspondence. DNA ranged from 27-2992ng/µl and 0.45-2.1 of 260/280nm. SSR detected 23 total alleles and 4.6 average alleles of 100-700bp. ISSR detected 152 total alleles and 21.7 average alleles of 200-2000bp. Amplified and polymorphic DNA bands were 437 and 117 for SSR, 512 and 391 for ISSR, respectively. Total and polymorphic bands MR was 87.4 and 29.4 for SSR, 73.1 and 55.9 for ISSR, respectively. PIC, EMR and MI for ISSR were higher than for SSR. Markers with high polymorphism portrayed high EMR and MI. SSR PKCT-122 and ISSR 17899A had the highest polymorphism, PIC, EMR and MI. Ne, I, He and UHe was high for SSR, while Na was high for ISSR. AMOVA revealed significant (P=0.01; P=0.02) differentiation. Genetic diversity was 14% and 7% among, 86% and 93% within accessions for SSR and ISSR, respectively. Three clusters independent of geographic origin were revealed. SSR and ISSR Euclidean matrices showed positive significant (r=0.272, P=0.0001) correlation, which implied they reflected the same genetic diversity. Hence, the genetic diversity of pumpkins can be assessed effectively using either SSR or ISSR markers.
Analysis of Institutional Factors Affecting Optimization of Coffee Yields in Chuka Sub-County, Tharaka-Nithi County, Kenya
(Research gate, 2020) Kihoro, David M.; Gathungu, Geofrey K.; ; ;
The importance of coffee production in the world economy cannot be ruled out due to its contribution in the developing countries in areas such as creation of employment and rise in foreign exchange. Most of the coffee producing countries in the world have come up with strategies to increase their quantity and improve the quality of their produce. In Kenya, the government have also come with numerous policies to support coffee production at the farm level but production of coffee in Kenya has since 1989 crop year been declining. There has been emergence of other enterprises that are profitable than coffee production such as real estate and dairy sector in most of the coffee-growing zones, but there are many farmers who have been determined to maintain coffee production. Despite the efforts made by the government to maximise coffee production in terms of quality and quantity, production has shown a downward trend, with some farmers completely doing away with production This study was aimed at assessing the factors that affect optimization of coffee production in Chuka sub-County, Tharaka-Nithi County. Proportional stratified random sampling was used to select a sample of 153 respondents from a population of 7,428 small-scale coffee farmersfrom ten cooperatives in the sub-County. The findings of the study indicated that access to extension, access to research and management of coffee cooperative were essential in coffee production with a mean agreement of 58.33%. The research established that access to extension (5%) and management of cooperatives (5%) were statistically significant while access to research at (5%) was statistically insignificant. Similarly, access to extension services increased optimization by 91%, poor management of coffee cooperatives reduced production by 45.1%, while access to research increased coffee production by 51%. Therefore, it is important to ensure farmers access extension services, research and there is improved management of coffee cooperatives.
Analysis of socioeconomic characteristics on coffee yield gap among smallholder farmers in Nyeri Central sub-county, Kenya
(world journal of advanced research and review, 2024-09-05) Florence Wairimu Ndungu 1, * , Martin Kagiki Njogu 2 and Geoffrey Kingori Gathungu
Kenya’s coffee production has been declining over the years leading to decreased yields and making it hard for farmers to benefit from the sector. This has resulted in a considerable yield difference, with actual farmer yields far below the potential yields of station trials. This large yield gap reveals an enormous potential for yield improvement in coffee production. However, the large yield gap may be attributed to several factors, yet there is limited quantitative information on site-specific factors and the yield gap attributed to the factors. This study informs the knowledge gap by analysing the effect of socioeconomic characteristics on the coffee yield gap of smallholder farmers in Nyeri Central sub county, Nyeri County. A cross-sectional research design was used, and a sample of 175 smallholder coffee farmers was drawn using the systematic random sampling technique. Data on socioeconomic characteristics was analysed using SPSS version 29, and their effect on the coffee yield gap was determined using a fractional logit regression model in STATA version 17. The findings noted that the yield gap index per variety was 88.54% for Ruiru 11, 93.78% for Batian, and 95.68% for SL 28. The model parameters indicated that the gender of the household head, schooling years, household size, and labour were negative but significant at p<0.05. This study concluded that smallholder coffee farmers were producing below their potential, as depicted by the large yield gap estimate. Therefore, feasible actions are required to close the existing yield gap, increase coffee yields, and enhance household food security
Analysis of Technical Efficiency on Orange Fleshed Sweet Potatoes Production Among the Smallholder Farmers in Migori County Kenya
(Scvience of PG, 2024-10-18) Lawrence Otieno Jabuya1, * , Shelmith Wanja Munyiri2 , Martin Kagiki Njogu2; ; ;
Sweet potatoes (Ipomea batatas L.), particularly the orange fleshed variety, have become increasingly popular due to their ability to thrive in various environmental conditions with minimal inputs. Orange fleshed sweet potatoes (OFSPs) show potential for productivity, yet smallholder farmers in Kenya still struggle to maximize their yields. The factors influencing OFSP production efficiency among these farmers in Western Kenya have not been thoroughly examined. This study evaluated the technical efficiency of OFSP production among smallholder farmers in Migori County. Using a descriptive research design, a sample of 225 OFSP farmers was randomly selected by a cluster sampling technique. Data was collected through a structured questionnaire on inputs and selected socio-economic factors. The data was analyzed using the frontier stochastic model in STATA. Smallholder farmers estimated mean technical efficiency was 77.82% significant variables were; size of the land, availability of planting vines, access to hired labour, gender of the household decision maker, farming experience, household size, land ownership status, participation in training programs and extension services, and proximity to markets, indicating a need to improve OFSP production by 22.18%. These findings suggest that to reduce inefficiencies among smallholder OFSP farmers, targeted training programs are needed to enhance farmers' agronomic knowledge specific to OFSP production. Further, policy interventions should prioritize the provision of extension services to support and improve the performance of OFSP smallholder farmers.
Analysis of the benefits and production challenges of working donkeys in smallholder farming systems in Kenya
(Veterinary World, 2020-11-13) Gichure, Mary; Onono, Joshua; Wahome, Raphael; Gathura, Peter
Aim: The aim of the study was to determine the benefits of keeping donkeys and associated production challenges under a smallholder farming system in Kenya. Materials and Methods: A descriptive study was conducted with smallholder farmers keeping donkeys in 13 administrative locations in Kirinyaga County. Data were collected using a questionnaire guide in 13 focus group discussions (FGDs) using participatory epidemiological methods. The FGDs comprised 8-12 participants who were donkey owners. Data were collected through listing, pair-wise ranking, and probing on the benefits of keeping donkeys, challenges faced by working donkeys and the common diseases that affect donkeys in these farms. Data analysis was performed using Kruskal–Wallis non-parametric method to test whether median ranks were significantly different. Other farm level data were also collected using the structured questionnaire and these were analyzed using descriptive statistical methods. Results: The identified benefits included income obtained from the use of donkeys in transportation (Z=5.80) and manure production (Z=3.47), which enabled the farmers to participate in trade activities and improve crop farming. The identified challenges included theft for slaughter (Z=5.99), disease incidence (Z=3.03), road accidents (Z=2.83), and malicious cutting (Z=2.32). Some of the diseases identified were tetanus (Z=5.35), hoof problems (Z=4.55), helminthiases (Z=3.10), and mange (Z=2.24). Participants ranked diseases based on their effects on work output for the donkeys, reducing productivity and often causing death. Addressing these production challenges would optimize donkey use among smallholder farmers. Conclusion: The results presented can be important for policymakers and extension agents regarding the health and welfare of donkeys kept under similar settings. Keywords: benefits and challenges, income, livelihoods, working donkeys
Antimicrobial Usage, Susceptibility Profiles, and Resistance Genes inCampylobacter Isolated from Cattle, Chicken, andWater Samples in Kajiado County, Kenya
(International Journal of Microbiology, 2023-03-22) Daniel W. Wanja ,Paul G. Mbuthia , Lilly C. Bebora , Gabriel O. Aboge , and Brian Ogoti
Campylobacter organisms are the major cause of bacterial gastroenteritis and diarrhoeal illness in man and livestock. Campylobacter is growingly becoming resistant to critically crucial antibiotics; thereby presenting public health challenge. Tis study aimed at establishing antimicrobial use, susceptibility profles, and resistance genes in Campylobacter isolates recovered from chicken, cattle, and cattle-trough water samples. Te study was conducted between October 2020 and May 2022 and involved the revival of cryopreserved Campylobacter isolates confrmed by PCR from a previous prevalence study in Kajiado County, Kenya. Data on antimicrobial use and animal health-seeking behaviour among livestock owners (from the same farms where sampling was done for the prevalence study) were collected through interview using a pretested semistructured questionnaire. One hundred and three isolates (29 C. coli (16 cattle isolates, 9 chicken isolates, and 4 water isolates) and 74 C. jejuni (38 cattle isolates, 30 chicken isolates, and 6 water isolates)) were assayed for phenotypic antibiotic susceptibility profle using the Kirby–Bauer disk difusion method for ampicillin (AX), tetracycline (TE), gentamicin (GEN), erythromycin (E), ciprofoxacin (CIP), and nalidixic acid (NA). Furthermore, detection of genes conferring resistance to tetracyclines (tet (O), β-lactams (blaOXA-61), aminoglycosides (aph-3-1), (fuoro)quinolones (gyrA), and multidrug efux pump (cmeB) encoding resistance to multiple antibiotics was detected by mPCR and confrmed by DNA sequencing. Te correlation between antibiotic use and resistance phenotypes was determined using the Pearson’s correlation coefcient (r) method. Tetracyclines, aminoglycosides, and β-lactam-based antibiotics were the most commonly used antimicrobials; with most farms generally reported using antimicrobials in chicken production systems than in cattle. Te highest resistance amongst isolates was recorded in ampicillin (100%), followed by tetracycline (97.1%), erythromycin (75.7%), and ciprofoxacin (63.1%). Multidrug resistance (MDR) profle was observed in 99 of 103 (96.1%) isolates; with all the Campylobacter coli isolates displaying MDR. All chicken isolates (39/39, 100%) exhibited multidrug resistance. Te AX-TEE-CIP was the most common MDR pattern at 29.1%. Te antibiotic resistance genes were detected as follows: tet (O), gyrA, cmeB, blaOXA-61, and aph-3-1 genes were detected at 93.2%, 61.2%, 54.4%, 36.9%, and 22.3% of all Campylobacter isolates, respectively. Te highest correlations were found between tet (O) and tetracycline-resistant phenotypes for C. coli (96.4%) and C. jejuni (95.8%). A moderate level of concordance was observed between the Kirby–Bauer disk difusion method (phenotypic assay) and
APPLICATION OF BOX-BEHNKEN DESIGN AND RESPONSE SURFACE METHODOLOGY FOR OPTIMISATION OF BUTTERNUT (CUCURBITA MOSCHATA) FRUIT YIELD USING FERTILISERS AND PINCHING
(Afr. J. Hort. Sci., 2022) Njiru, Rachael W.; Muraya, Moses M.; Gathungu, Geoffrey K.; ; ;
Butternut (Cucurbita moschata) production is constrained by poor agronomic practices such as suboptimal application of fertilizers and lack of appropriate pinching practices aimed at improving the number of female flowers. Moreover, many farmers mix animal manures and inorganic fertilisers in one hill without any recommended rates. The objective of this study was to apply Box-Behnken Design and Response Surface Methodology to optimize butternut fruit yield using poultry manure, NPK fertiliser and pinching. The experiments were conducted in two trials in 2019 and 2020 at Karingani ward, Chuka. A Factorial experiment laid down in Randomised Complete Block Design was used. The factors included poultry manure at three levels (0, 5 and 10 tons/ha), NPK at three levels (0, 100 and 200 kg/ha of NPK 17:17:17) and pinching at three levels (0, 4th node and 6th node). Butternut variety Atlas F1 was used. Data was collected on the fruit yield. The input variables were modelled and maximised using Box-Behnken design (BBD) and Response Surface Methodology. The optimisation of the input variables revealed that the optimal levels of application of NPK and poultry manure that can lead to maximum yield of butternut fruits were 505 kg/ha of NPK and 8102 kg/ha poultry manure. The model also showed that pinching should be conducted 30 days after planting (equivalent to pinching at 3rd node) for optimal butternut fruit yield. The study demonstrated that BBD can serve as an inexpensive tool in optimization of the butternut fruit production. However, there is need for further field studies to validate the findings of this study in order to accurately advice farmers on optimum combined application of manure, NPK and pinching time.
Application of Box-Behnken Design and Response Surface Methodology for Optimisation of Butternut (Cucurbita Moschata) Fruit Yield using Fertilisers and Pinching
(2022) Njiru, R.; Gathungu, G.; Muraya, M.
Butternut (Cucurbita moschata) production is constrained by poor agronomic practices such as suboptimal application of fertilizers and lack of appropriate pinching practices aimed at improving the number of female flowers. Moreover, many farmers mix animal manures and inorganic fertilisers in one hill without any recommended rates. The objective of this study was to apply Box-Behnken Design and Response Surface Methodology to optimize butternut fruit yield using poultry manure, NPK fertiliser and pinching. The experiments were conducted in two trials in 2019 and 2020 at Karingani ward, Chuka. A Factorial experiment laid down in Randomised Complete Block Design was used. The factors included poultry manure at three levels (0, 5 and 10 tons/ha), NPK at three levels (0, 100 and 200 kg/ha of NPK 17:17:17) and pinching at three levels (0, 4th node and 6th node). Butternut variety Atlas F1 was used. Data was collected on the fruit yield. The input variables were modelled and maximised using Box-Behnken design (BBD) and Response Surface Methodology. The optimisation of the input variables revealed that the optimal levels of application of NPK and poultry manure that can lead to maximum yield of butternut fruits were 505 kg/ha of NPK and 8102 kg/ha poultry manure. The model also showed that pinching should be conducted 30 days after planting (equivalent to pinching at 3rd node) for optimal butternut fruit yield. The study demonstrated that BBD can serve as an inexpensive tool in optimization of the butternut fruit production. However, there is need for further field studies to validate the findings of this study in order to accurately advice farmers on optimum combined application of manure, NPK and pinching time.
Application of Box-Behnken Design and Response Surface Methodology for Optimisation of Butternut (Cucurbita Moschata) Fruit Yield Using Fertilisers and Pinching
(2022) Njiru, R.; Gathungu, G.; Muraya, M.
Butternut (Cucurbita moschata) production is constrained by poor agronomic practices such as suboptimal application of fertilizers and lack of appropriate pinching practices aimed at improving the number of female flowers. Moreover, many farmers mix animal manures and inorganic fertilisers in one hill without any recommended rates. The objective of this study was to apply Box-Behnken Design and Response Surface Methodology to optimize butternut fruit yield using poultry manure, NPK fertiliser and pinching. The experiments were conducted in two trials in 2019 and 2020 at Karingani ward, Chuka. A Factorial experiment laid down in Randomised Complete Block Design was used. The factors included poultry manure at three levels (0, 5 and 10 tons/ha), NPK at three levels (0, 100 and 200 kg/ha of NPK 17:17:17) and pinching at three levels (0, 4th node and 6th node). Butternut variety Atlas F1 was used. Data was collected on the fruit yield. The input variables were modelled and maximised using Box-Behnken design (BBD) and Response Surface Methodology. The optimisation of the input variables revealed that the optimal levels of application of NPK and poultry manure that can lead to maximum yield of butternut fruits were 505 kg/ha of NPK and 8102 kg/ha poultry manure. The model also showed that pinching should be conducted 30 days after planting (equivalent to pinching at 3rd node) for optimal butternut fruit yield. The study demonstrated that BBD can serve as an inexpensive tool in optimization of the butternut fruit production. However, there is need for further field studies to validate the findings of this study in order to accurately advice farmers on optimum combined application of manure, NPK and pinching time.
Application of Central Composite Design Based Response Surface Methodology in Parameter Optimization of Watermelon Fruit Weight Using Organic Manure
(American Journal of Theoretical and Applied Statistics, 2017-03-18) Muriithi, Dennis K.; Koskei, J. K. Arap; Gathungu,Geofrey; ; ;
Response Surface Methodology (RSM) is a critical technology in developing new processes, optimizing their performance and improving the design. In Kenya, watermelon cultivation is gradually gaining ground. It is a crop with huge economic importance to man as well as highly nutritious, sweet and thirst- quenching. In order to increase crop production, there is need to increase soil nutrient content with organic manure such as poultry, cow or other animal wastes. At present, there are no recommended standards with respect to rate of poultry manure, cow manure and goat manure for enhancement of yield of watermelon in Kenya. The main objective of the study was to develop an approach for better understanding of the relationship between variables and response for optimum operating settings for maximum yield of watermelon crop using Central Composite Design and Response Surface Methodology. Response Surface Model evolved for response shown the effect of each input parameter and its interaction with other parameters, depicting the trend of response. Verification of the Fitness of the model using ANOVA technique shows that the model can be used with confidence level of 0.95, for watermelon production. Further validation of the model done with the additional experimental data collected demonstrates that the model have high reliability for adoption within the chosen range of parameters. The optimal value for each factor was found as 17.13tons/Ha of poultry manure, 13.3tons/Ha of cow manure and 18.1tons/Ha of goat manure. At optimal conditions, the actual value of the fruit weight of watermelon was 93.148tons/Ha. This translates to 37.3tons per acre piece of land of watermelon fruit weight for a period of 75-85 days after sowing. In addition, a peasant farmer can generate about 745,184 Kenya shillings within a period of 75 day in one acre piece of land at a low price of Kshs 20 per kilogram of watermelon fruit. RSM has resulted in saving of considerable amount of time and money hence recommended in similar study.
Application of Seasonal Autoregressive Moving Average Models to Analysis and Forecasting of Time Series Monthly Rainfall Patterns in Embu County, Kenya
(Asian Journal of Probability and Statistics, 2019-08-19) Filder, Tartisio Njoki; Muraya, Moses Mahugu; Mutwiri, Robert Mathenge
Rainfall is of critical importance for many people, particularly those whose livelihoods depend on rainfed agriculture. Predicting the trend of rainfall is a difficult task, and statistical approaches such as time series analysis provide a means for predicting the patterns of rainfall. The models also offer the potential to improve areas such as increased food production, profitability, and improved food security policing. However, these forecasts and information systems may, in some instances, not be suitable for direct use by stakeholders in their decision-making. The objective of this study was to investigate rainfall variability and develop a Seasonal Auto-Regressive Integrated Moving Average (SARIMA) model for fitting the monthly rainfall using time series data. Secondary monthly data from 1998 to 2017 for Embu County was collected from the Kenya Meteorological Department, Embu and recorded into an excel sheet. R-software was utilized to analyse data for descriptive statistics, rainfall variability, and model fitting. The coefficient of variation for annual and seasonal rainfall was calculated. The Box Jenkin's ARIMA modelling procedure (model identification, model estimation, model validation) was used to determine the best models for the data. The main study findings indicated the existence of annual variability of 34%, March-April-May rainfall variability of 44%, and October-November-December variability of 44%. A first-order differenced SARIMA (1, 1, 1) (0, 1, 2)12 model with an AIC score of 9.99356 was found suitable for predicting rainfall pattern in Embu, County. The study outcome revealed that Embu County experiences high seasonal and rainfall variation of rainfall, thus requires a reliable model for better prediction.
Application of Seasonal Autoregressive Moving Average Models to Analysis and Forecasting of Time Series Monthly Rainfall Patterns in Embu County, Kenya
(Asian Journal of Probability and Statistics, 2019-08-19) Filder, Tartisio Njoki; Muraya, Moses Mahugu; Mutwiri, Robert Mathenge
Rainfall is of critical importance for many people, particularly those whose livelihoods depend on rainfed agriculture. Predicting the trend of rainfall is a difficult task, and statistical approaches such as time series analysis provide a means for predicting the patterns of rainfall. The models also offer the potential to improve areas such as increased food production, profitability, and improved food security policing. However, these forecasts and information systems may, in some instances, not be suitable for direct use by stakeholders in their decision-making. The objective of this study was to investigate rainfall variability and develop a Seasonal Auto-Regressive Integrated Moving Average (SARIMA) model for fitting the monthly rainfall using time series data. Secondary monthly data from 1998 to 2017 for Embu County was collected from the Kenya Meteorological Department, Embu and recorded into an excel sheet. R-software was utilized to analyse data for descriptive statistics, rainfall variability, and model fitting. The coefficient of variation for annual and seasonal rainfall was calculated. The Box Jenkin's ARIMA modelling procedure (model identification, model estimation, model validation) was used to determine the best models for the data. The main study findings indicated the existence of annual variability of 34%, March-April-May rainfall variability of 44%, and October-November-December variability of 44%. A first-order differenced SARIMA (1, 1, 1) (0, 1, 2)12 model with an AIC score of 9.99356 was found suitable for predicting rainfall pattern in Embu, County. The study outcome revealed that Embu County experiences high seasonal and rainfall variation of rainfall, thus requires a reliable model for better prediction.
Are the AgriTech Technologies Available, Adaptable and Practical to Young Farmers? Lessons from Tomato farmers in Kirinyaga County, Kenya
(Journal of Agricultural Science and Food Research, 2020) Kamau, Joram Ngugi; Kiprop, Ibrahim Nyariki; Kipruto, Geoffrey Kosgei; ; ;
Information and communication technologies (ICTs) in particular mobile phone applications and internet are transforming how agribusiness is carried out in some parts of developing countries including Kenya. The spread of information and communication technologies (ICTs), especially mobile phones, in developing countries has been both extensive and rapid creating a need to assess its efficiency and the rate of adoption. This study aimed at examining how farmers in the county integrate technological innovations in the production and marketing stage of tomato in the sampled area. The objective of the study was to examine how small scale farmers are integrating social media marketing platforms, digital credit, agricultural value addition and artificial intelligence in their production and marketing stages in the agricultural value chain. The results indicate statistically significant positive effects of AgriTech Technologies on farm income (t-prob 0.000<0.05). The results notably indicate that using social media marketing platforms has the highest positive contribution to a unit change in farm income (β= 3.84).Smallholder farmer’s ability to access knowledge, networks, and institutions essential for improving productivity, food security, and employment opportunities is a big challenge especially in rural areas where internet connectivity and poverty levels are alarming.
Assessing the influence of knowledge of type and numbers of livestock exchange in stock friends’ concept as a strategy in poverty alleviation; case of Ngomeni Community of Mwingi District in Kenya
(2015) M’mboroki, Kiambi G. 1; Aboud, Abdillahi A. 2; Rithaa, Jafford N. 3
One of the challenge-facing Kenya is high levels of poverty. Different ways of poverty alleviation are applied among them is stock friends strategy. The strategy is ineffective among the Ngomeni community of Mwingi District. It is postulated that there is poor understanding of the right types and numbers of livestock for the exchange; and the rate of adoption of the strategy. A socio-ecological survey of 233 households sampled and complemented by Key Informant interviews was conducted. Descriptive and regression analyses using SPSS were used to determine the associations and influences of the factors (independent variable) on poverty levels of the community (dependent variable). The degree of community knowledge of type and numbers of stock used in the stock exchange (β value of -0.449 that explained 25.5% variation) and adoption of the stock exchange strategy were found to be key and could be addressed using stock friend’s concept.
Assessment of benthic macroinvertebrates as bio indicators of water quality in river Naka, Chuka, Tharaka-Nithi, Kenya
(Journal of Environmental Sustainability Advancement Research, 2022) Chamia, L. K.; Kutuny, G. K.
Freshwater ecosystems worldwide have been progressively deteriorating leading to a decrease in aquatic biodiversity. Conventionally, evaluation of water quality uses single physical-chemical parameters which may be insufficient to fully assess the quality of freshwaters. This study used bio-indicators to assess water quality of River Naka in Tharaka-Nithi County, Kenya. Fluvial ecosystems support rich and diverse assemblages, making them vulnerable to possible alterations in the habitat. The study assessed the diversity and abundance of benthic macroinvertebrate communities and their use as bioindicators of water quality. Grab sampling was used to collect water samples, a kick sampler and D-frame aquatic net was used to collect 121 benthic macroinvertebrates from three selected sites and determined using EPT Index (Ephemeroptera, Plecoptera and Trichoptera group). The data obtained was used to determine the index of the sampling sites. Physico-chemical factors were analyzed in-situ (temperature, turbidity and pH) and in the laboratory(nitrates and phosphates). The highest EPT index values (28) at the upstream corresponded to good water quality, while the slightly low values (21) at the midstream indicated moderate water quality and the lowest values (15) recorded at the downstream showed fair water quality. The downstream water quality parameters exceeded World Health Organization limits, posing a health risk to water consumers. Continuous bio-assessment of rivers based on EPT biotic indicators should be conducted on a regular basis to establish a long-term profile of water quality state and ecological integrity of rivers.
Assessment of Benthic Macroinvertebrates as Bioindicators of Water Quality in River Naka, Chuka, Tharaka-Nithi, Kenya
(Chuka University, 2022) Chamia, L.K.; Kutuny, G.K.
Freshwater ecosystems worldwide have been progressively deteriorating leading to a decrease in aquatic biodiversity. Conventionally, evaluation of water quality uses single physical-chemical parameters which may be insufficient to fully assess the quality of freshwaters. This study used bio-indicators to assess water quality of River Naka in Tharaka-Nithi County, Kenya. Fluvial ecosystems support rich and diverse assemblages, making them vulnerable to possible alterations in the habitat. The study assessed the diversity and abundance of benthic macroinvertebrate communities and their use as bioindicators of water quality. Grab sampling was used to collect water samples, a kick sampler and D-frame aquatic net was used to collect 121 benthic macroinvertebrates from three selected sites and determined using EPT Index (Ephemeroptera, Plecoptera and Trichoptera group). The data obtained was used to determine the index of the sampling sites. Physico-chemical factors were analyzed in-situ (temperature, turbidity and pH) and in the laboratory(nitrates and phosphates). The highest EPT index values (28) at the upstream corresponded to good water quality, while the slightly low values (21) at the midstream indicated moderate water quality and the lowest values (15) recorded at the downstream showed fair water quality. The downstream water quality parameters exceeded World Health Organization limits, posing a health risk to water consumers. Continuous bio-assessment of rivers based on EPT biotic indicators should be conducted on a regular basis to establish a long-term profile of water quality state and ecological integrity of rivers.

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