Browsing by Author "Muraya, Moses M."

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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.
Influence of Farm’s Characteristics on Adoption of Eco-Friendly Farming Practices in Agroecosystems of Embu County, Kenya
(CRDEEP Journals, 2019-08) Njeru, Moses Kathuri; Muraya, Moses M.; Mutegi, James K.; ; ;
There is a close association between agriculture and the environment. Agriculture is one of the main economic activities that depends on and influences a number of environmental resources including water, land and biodiversity as well as production technologies and management skills. In the pursuit of feeding the rapidly increasing world population, some widespread agricultural practices have contributed to loss of biodiversity, acidification, soil erosion, unsustainable production and salinization. To simultaneously address these environmental challenges and ensure sustainable production, environmentalists have recommended a paradigm shift. This has led to promotion of Eco-Friendly Farming Practices (EFFPs) among farmers. EFFPs are farming activities that ensure optimum farm production and simultaneously maintain the environmental integrity of the agroecosystems within which they occur. However, despite the effort made in promoting EFFPs among farming households in Kenya, the adoption rates have varied greatly. This study was conducted in the agroecosystems of Embu County in Kenya to evaluate the Eco-Friendly Farming Practices (EFFPs). The purpose of the study was to find out the influence of farm’s characteristics on adoption of the EFFPs. Ex post facto research design was used and through a multi-stage random sampling technique, 240 household farms were selected for the study. Soil pH, Farms’ slopes, soil moisture and carbon content were determined and their relationship with EFFPs established. Slope of the farm had a statistically significant relationship with adoption of EFFPs. Levels of soil moisture were positively influencing adoption of EFFPs. Therefore the farms’ biophysical characteristics need to be evaluated as EFFPs and related technologies are introduced on farms.
Mathematical Modeling of Host - Pest Interactions in Stage-Structured Populations: A Case of False Codling Moth [Thaumatotibia leucotreta]
(Scitech Research Organisation (SRO), 2021-09) Ochwach, Jimrise O.; Okongo, Mark O.; Muraya, Moses M.; ; ;
False codling moth (FCM) (Thaumatotibia lucotreta) is a significant pest due to its potential economic impact on many susceptible fruits in most temperate regions of the world. Efforts to control the codling moth in the past mostly relied on the use of broad spectrum insecticide sprays, which has resulted in the development of insecticide resistance, and the disruption of the control of secondary pests. Understanding the dynamic of this pest is of great in importance in order to effectively employ the most effective control strategies. In this study, a mathematical model of host-false codling moth interactions is developed and qualitatively analysed using stability theory of system of differential equations. The basic offspring number with respect to FCM free equilibrium is obtain using next generation matrix. The condition for local and global asymptotic stability of FCM free and coexistence equilibria are established. The model is analysed numerically and graphically represented to justify the analytical results.
Targeted sequencing reveals largscale sequence polymorphism in maize candidate genes for biomass production and composition PLoS ONE 10(7)
(2015-07-07) Muraya, Moses M.; Schmutzer, Thomas; Ulpinnis, Chris; Scholz, Uwe; Altmann, Thomas
Abstract A major goal of maize genomic research is to identify sequence polymorphisms responsible for phenotypic variation in traits of economic importance. Large-scale detection of sequence variation is critical for linking genes, or genomic regions, to phenotypes. However, due to its size and complexity, it remains expensive to generate whole genome sequences of sufficient coverage for divergent maize lines, even with access to next generation sequencing (NGS) technology. Because methods involving reduction of genome complexity, such as genotyping-by-sequencing (GBS), assess only a limited fraction of sequence variation, targeted sequencing of selected genomic loci offers an attractive alternative. We therefore designed a sequence capture assay to target 29 Mb genomic regions and surveyed a total of 4,648 genes possibly affecting biomass production in 21 diverse inbred maize lines (7 flints, 14 dents). Captured and enriched genomic DNA was sequenced using the 454 NGS platform to 19.6-fold average depth coverage, and a broad evaluation of read alignment and variant calling methods was performed to select optimal procedures for variant discovery. Sequence alignment with the B73 reference and de novo assembly identified 383,145 putative single nucleotide polymorphisms (SNPs), of which 42,685 were non-synonymous alterations and 7,139 caused frameshifts. Presence/absence variation (PAV) of genes was also detected. We found that substantial sequence variation exists among genomic regions targeted in this study, which was particularly evident within coding regions. This diversification has the potential to broaden functional diversity and generate phenotypic variation that may lead to new adaptations and the modification of important agronomic traits. Further, annotated SNPs identified here will serve as useful genetic tools and as candidates in searches for phenotype-altering DNA variation. In summary, we demonstrated that sequencing of captured DNA is a powerful approach for variant discovery in maize genes.