The continuous mining of soil nutrients with inadequate replenishment and improper soil management has resulted in poor fertility levels leading to poor harvests. Even so, researchers have come up with information and new technologies that can reverse the status of poor soils but the concern is that information on the uptake and use of these technologies is inadequate in Embu County. The objectives of this study were therefore to: (i) determine how household demographic and socioeconomic factors influence use of integrated soil fertility management strategies for maize production (ii) assess smallholder farmers’ knowledge levels on the use of ISFM strategies for maize production, (iii) determine factors affecting knowledge levels of ISFM strategies for maize production and (iv) determine the influence of farmer management practices on the level of phosphorus in their farms in Embu County. A pilot study was conducted to ensure the appropriateness of the data collection tools. During the actual survey, 100 farm households were randomly selected and included in the study. A detailed questionnaire with both closed and open-ended questions was used to collect data on the levels of farmer knowledge on ISFM strategies, household demographic and socio-economic factors affecting farmers’ use of ISFM strategies. Soil samples were also collected from fields of each farmer interviewed thus a total of 100 soil samples for analysis of phosphorus levels. Three soil cores were collected according to variability and farm size then composited to produce one sample for analysis. Soil was analysed for available P using Bray’s method. The study considered five ISFM strategies; use of inorganic fertilizer, use of organic fertilizer, combined use of inorganic and organic fertilizer, use of improved seeds and combined use of inorganic and organic fertilizer with improved seeds. Data was analysed using descriptive statistic, ordinary least squares regression, binary logistic regression, multinomial logistic regression using SPSS version 20 software. Comparisons and associations were done using t-test and Chi-square. Ordinary least square regression showed that household size, off-farm income, size of land under maize, maize yield, occupation of household head and training were the socio-demographic factors significant in predicting phosphorus fertilizer use and animal manure use at p
ACHIENG, A (2021). Determinants Of Adoption Of Integrated Soil Fertility Management Strategies For Maize Production Intensification In Embu County, Kenya. Afribary. Retrieved from https://afribary.com/works/determinants-of-adoption-of-integrated-soil-fertility-management-strategies-for-maize-production-intensification-in-embu-county-kenya
ACHIENG, ADA "Determinants Of Adoption Of Integrated Soil Fertility Management Strategies For Maize Production Intensification In Embu County, Kenya" Afribary. Afribary, 01 Jun. 2021, https://afribary.com/works/determinants-of-adoption-of-integrated-soil-fertility-management-strategies-for-maize-production-intensification-in-embu-county-kenya. Accessed 31 Mar. 2023.
ACHIENG, ADA . "Determinants Of Adoption Of Integrated Soil Fertility Management Strategies For Maize Production Intensification In Embu County, Kenya". Afribary, Afribary, 01 Jun. 2021. Web. 31 Mar. 2023. < https://afribary.com/works/determinants-of-adoption-of-integrated-soil-fertility-management-strategies-for-maize-production-intensification-in-embu-county-kenya >.
ACHIENG, ADA . "Determinants Of Adoption Of Integrated Soil Fertility Management Strategies For Maize Production Intensification In Embu County, Kenya" Afribary (2021). Accessed March 31, 2023. https://afribary.com/works/determinants-of-adoption-of-integrated-soil-fertility-management-strategies-for-maize-production-intensification-in-embu-county-kenya