FACULTY OF AGRICULTURE http://ir.library.ui.edu.ng/handle/123456789/261 2026-04-07T03:03:41Z 2026-04-07T03:03:41Z Olaniyi, J. O. Olusoga, S. Babatola, L. A. Atanda, T. T. http://ir.library.ui.edu.ng/handle/123456789/9495 2024-08-30T09:45:01Z 2016-01-01T00:00:00Z

Title: Effects of pre-storage treatments on sprouting and nutritional quality of ginger (zingiberofficinalerosc) rhizomes in different storage periods Authors: Olaniyi, J. O.; Olusoga, S.; Babatola, L. A.; Atanda, T. T. Abstract: Purpose: Ginger rhizomes are highly susceptible to damage during postharvest storage due to soil borne pathogenic disorder. Experiments were conducted to evaluate the effects of prestorage treatments required for sprouting and maintaining the quality of ginger plant in different storage periods at the Teaching and Research Farm, Ladoke Akintola University of Technology, Ogbomoso. Method: The rhizomes were treated with four different pre-storage treatments viz.,control, hydrated lime, - Mancozeb, and 100ml of Trichodermaharzianum solution at different storage periods of one, two and three months. The experiment was arranged in a complete randomized designand laid out in a randomized complete block design with three replicates. Data were collected on percentage sprouting, plant height, number of leaves, leaf area and nutritional quality of ginger rhizomes. Data were subjected to analysis of variance using Statistical Analysis System Software (SAS, 2005). Differences among treatment means were compared using Least Significance Difference (LSD) at 5% probability level. Results: The storage periods significantly (P≤0.05) influenced the percentage sprouting andgrowth parametersof ginger at various sampling period. Highest growth of 9.05cm was recorded from ginger plant stored for three months while the least value of 6.94cm was obtained from rhizomes stored for one month. The pre-storage treatments significantly (P≤0.05) influenced the percentage sprouting, weight loss and growth parameters of ginger at various sampling period. Highest percentage sprouting (94.3%) was recorded from rhizomes treated with 100 ml Trichodermaharzianim solution followed by rhizomes treated with hydrated lime (88.3 %) while lowest percentage sprouting (61.5 %) were recorded from control. Highest percentage weight loss of 46.3% was recorded from control followed by hydrated lime (35.58 %) while the lowest percentage weight loss of 33.93 % was recorded from 100 ml Trichodermaharzianim solution. Conclusions: In conclusion, rhizomes treated with Trichodermaharzianim solution for a period of three months before planting produced better sprouting and enhanced the growth quality of ginger on the field

2016-01-01T00:00:00Z OLAJIDE, F.O http://ir.library.ui.edu.ng/handle/123456789/9458 2024-08-09T09:10:50Z 2014-12-01T00:00:00Z

Title: DETERMINANTS OF AGRICULTURAL RISK MANAGEMENT BEHAVIOUR OF CROP FARMERS IN NIGERIA Authors: OLAJIDE, F.O Abstract: Agricultural risks constitute a fundamental challenge in Nigeria, leading to low productivity among farmers. Farmers risk management behaviour determines the extent to which they overcome risk types. Information on crop farmers’ risk management behaviour in Nigeria is however scanty. Therefore determinants of agricultural risk management behaviour of crop farmers in Nigeria were investigated. Multistage sampling technique was used. Of the agro-ecological zones, Coastal, Rainforest and Guinea savannah were randomly selected. Thereafter, 10% of the states in the zones (Lagos, Osun and Niger) and 10% of the Local Governments Areas (LGAs) in the states were selected. Two communities were selected from each of the LGAs and 15% of crop farmers were chosen in the selected communities to give 323 crop farmers. Interview schedule was used to collect data on respondents’ risks types, risk exposure levels and risk management strategies. Indices were used to categorise farmers on their risk types (production, marketing, financial and social) and risk behaviour (superior, active, di-function, mono-function and part-time risk managers). Data were analysed using descriptive statistics, chi-square, Pearson Product Moment Correlation, ANOVA and multinomial logistic regression at p= 0.05. Most (90.0%) respondents were males, married (89.7%), and had at least primary school education (62.3%) with farm sizes of less than 5 hectares (72.3%). Age and years of farming experience were 53.2±10.5 and 28.3±12.1 years respectively. Majority (94.2%) identified inadequate cash-flow, pests and diseases (91.3%), ill-health of farmer/farm employee (89.0%) and volatility in output price (85.5%) as types of agricultural risks. Respondents were more vulnerable to production (9.85) and financial (9.84) risks. Majority (81.3%) were moderately or highly exposed to agricultural risks. Risk management strategies highly utilised were reducing leverage (2.94), maintaining good relations with contracting partners (2.73), use of fertilizers (2.65) and use of improved seedlings (2.57), while 73.9% of the farmers that had crop insurance coverage affirmed that it was effective in managing risks. Use of risk management strategies was low for 47.1%, with marketing strategies being the least (1.17) utilised. Superior agricultural risk managers accounted for 14.2%; active (26.8%); di-function (33.2%); mono-function (21.9%) and part-timers (3.9%), with the coastal zone having the highest percentage of superior (19.0%) and active (43.1%) risk managers. There were significant relationships between level of risk management and each of sex, marital status, educational level and farm size. While the Guinea savannah zone had the highest level (259.58) of agricultural risk exposure, the coastal zone had the highest level (75.89) of agricultural risk management. Significant predictors of agricultural risk management behaviour were farm size, organization membership and risk exposure level for mono-function and active managers. Di-function and superior managers were significantly predicted by farm size and risk exposure level respectively. Crop farmers in the zones encountered more of production and financial risks and lacked adequate risk management strategies. Their low level of insurance coverage indicated that factors other than awareness determined participation in insurance. Crop farmers should utilise more risk management strategies in order to reduce their risk exposure levels. Description: A Thesis in The Department Of Agricultural Extension And Rural Development submitted To The Faculty Of Agriculture And Forestry In Partial Fulfilment Of The Requirements For The Award Of The Degree Of Doctor Of Philosophy Of the University Of Ibadan, Ibadan

2014-12-01T00:00:00Z Fashae, O. A. Tijani, M. N. Adekoya, A. E. Tijani, S.A. Adagbasa, E. G. Aladejana, J. A. http://ir.library.ui.edu.ng/handle/123456789/9299 2024-05-30T14:51:27Z 2022-01-01T00:00:00Z

Title: Comparative assessment of the changing pattern of land cover along the Southwestern coast of Nigeria using GIS and remote sensing techniques Authors: Fashae, O. A.; Tijani, M. N.; Adekoya, A. E.; Tijani, S.A.; Adagbasa, E. G.; Aladejana, J. A. Abstract: The changing pattern of land cover is increasingly becoming of global concern in the sustainable management of environmental resources. Different facets of the natural ecosystem continue witnessing devastation orchestrated by rapid population growth and urban expansion in the face of climate change. This study examined the contribution of human’s to the global environmental change by assessing the dynamics of land cover between 1984 and 2017 while predicting the future extent of land cover pattern for 2047 at the Epe and Igbokoda areas on the coast of southwestern Nigeria. Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM + ), and Operational Land Imager (OLI) imageries of 1984, 2002, and 2017 respectively were acquired from the USGS to analyse the land cover changes. Supervised classification was done using the maximum likelihood classifier of Terrset version 18.31. The Change Demand Modelling of Land Change Modeller (LCM) in Terrset integrates the Markov chain for future predictions for 2047. The Epe area which typifies a rapidly urbanizing coastal environment recorded an 84.6% increase in built-up area extent between 1984 and 2017, while the built-up area of the Igbokoda area increased by 103.8% for the same period. This increment corresponds to a decrease in the spatial extent of the forested wetlands with an increase in water bodies. Expansion of water body extents indicates the interaction between the elements of climate change such as incessant flooding and anthropogenic activities like deforestation, urban expansion through sand mining and dredging. Future prediction into 2047 connotes further worsening of the situation. Therefore, solution-based sustainable coastal management practices are recommended to salvage the impoverishing coastal ecosystems from further impairment.

2022-01-01T00:00:00Z Okanlawon, O. M. Tijani, S. A. Oguntade, M. I. http://ir.library.ui.edu.ng/handle/123456789/9298 2024-05-30T14:39:38Z 2021-01-01T00:00:00Z

Title: Determinants of utilisation of university of Ibadan agricultural research outputs among farmers in Oyo and Osun states, Nigeria Authors: Okanlawon, O. M.; Tijani, S. A.; Oguntade, M. I. Abstract: The study assessed determinants of farmers’ utilisation of University of Ibadan (UI) Agricultural Research Outputs (AROs) in Oyo and Osun States, Nigeria. A multi-stage sampling procedure was used to select 176 beneficiaries of AROs in the study area. Focus Group Discussion and interview schedule were used for data collection on respondents’ socio-economic characteristics, knowledge, utilisation level and determinants of utilisation of UI AROs. Data was analysed using descriptive and inferential statistics like Chi square, PPMC, and multiple regression. AROs considered for the study were use of neem (Azadirachta indica) extract for pest management, rice-fish-poultry integrated farming system, processing of moringa oleifera powder and ruminant feed block meal pattern. Results reveal that respondents’ mean age household size were 40.05±35.48 years of 4.04±1.25 persons respectively. Respondents had mean farming experience of 7.92±5.26 years. The most utilised source of labour was family (63.0%) with mean farm size of 1.56±0.93 acres. Respondents’ knowledge (67.0%), and utilisation (55.7%) of UI AROs were high for innovations disseminated. Respondents’ marital status (χ2=5.99), sex (χ2=3.92), level of education (χ2=30.69); age (r=0.23) and income (r=0.79) were significantly related to UI AROs utilisation. Respondents’ knowledge (r=0.32) and benefits derived (r=0.80) were significantly related to utilisation of UI AROs. The determinants of utilisation of the AROs included educational qualification (β = 0.462), years of farming or processing experience (β=0.27), scale of production (β=0.33) and knowledge on utilisation (β=0.45). The study recommends that farmers be encouraged to improve on their level of education for better utilisation of disseminated agricultural research outputs.

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