Browsing by Author "Mulianga, B."
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Item Does the Adoption of Minimum Tillage Improve Sorghum Yield Among Smallholders in Kenya? A Counterfactual Analysis(Elsevier B.V., 2022) Musafiri, C.M.; Kiboi, M.; Macharia, J.; Ng'etich, O.K.; Okoti, M.; Mulianga, B.; Kosgei, D.K.; Ngetich, F.K.; University of Embu ; Cortile Scientific Limited ; KCA University ; Kenyatta University ; Kenya Agricultural and Livestock Research Organization (KALRO) ; , Moi University ; Jaramogi Oginga Odinga University of Science and TechnologyClimate change is a major drawback to food security in most developing countries. Promoting minimum tillage and climate-smart crops is essential in mitigating and adapting to climate shocks. However, information on the impacts of minimum tillage on crop productivity under farmers' conditions is limited in Western Kenya. We assessed the effects of minimum tillage adoption on sorghum productivity among smallholder sorghum farmers in Western Kenya. We used household survey data collected from 300 smallholder farmers and performed an endogenous switching regression model to analyze the effects of minimum tillage adoption on sorghum yields. The results revealed that the adoption of minimum tillage increased sorghum yields by 11%, from 1163 to 1146 kg ha−1. The occupation of the household head, acreage, soil fertility perception, and farm credit significantly and positively determined minimum tillage adoption. The remittance, agricultural associations, weather information, and site negatively and significantly determined minimum tillage adoption. Our findings suggest that minimum tillage adoption under drought-tolerant crops such as sorghum could improve community wellbeing through increased crop productivity, notwithstanding the changing climate and associated weather shocks.Item Smallholders’ Adaptation to Climate Change in Western Kenya: Considering Socioeconomic, Institutional, and Biophysical Determinants(Elsevier B.V., 2022) Musafiri, C.M.; Kiboi, M.; Macharia, J.; Ng’etich, O.K.; Kosgei, D.K.; Mulianga, B.; Okoti, M.; Ngetich, F.K.; University of Embu ; Cortile Scientific Company Ltd ; Kenyatta University ; Moi University ; Kenya Agricultural and Livestock Research Organization (KALRO) ;Jaramogi Oginga Odinga University of Science and Technology (JOOUST); University of Embu; Cortile Scientific Company Ltd; Kenyatta University; Moi University; Kenya Agricultural and Livestock Research Organization (KALRO); Jaramogi Oginga Odinga University of Science and Technology (JOOUST)Climate change has stimulated detrimental threats to the global agricultural ecosystems. The study investigated i) the climate change perceptions, drivers, effects, and barriers, and ii) determinants of climate change adaptation among smallholder farmers in Western Kenya. The study interviewed 300 households using a semi-structured face-to-face interview schedule. The study employed two indices, i.e., weighted average and problem confrontation, and two regression models, i.e., Binary logistic and Poisson regression. The findings indicated that smallholder farmers were aware of climate change, its drivers, and its effects. The main barriers to climate change adaptation were unpredictable weather patterns, financial constraints, and limited agricultural training. Group membership and site negatively influenced climate change adaptation. Household head's education, experience, remittance receipt, access to credit on inputs, climate change perception, access to weather information, and cultivated farm size positively influenced climate change adaptation. The findings underscore the importance of tailoring smallholder farmers' dynamics in climate change policies to enhance adaptation. The negative prediction of group membership needs to be emphasized to prevent demotivating farmers from joining community associations. The study highlights the need to incorporate farmers' perceptions of climate change, climate awareness creation, and monetary assistance to enhance climate change resilience among smallholder farmers.Item Soil Greenhouse Gas Emissions from Different Land Utilization Types in Western Kenya(Frontiers, 2022-11-30) Kibet, E.; Musafiri, C.M.; Kiboi, M.; Macharia, J.; Ng’etich, O.K.; Kosgei, D.K.; Mulianga, B.; Okoti, M.; Zeila, A.; Ngetich, F.K.; University of Embu ; Cortile Scientific Limited ; Kenyatta University ; Moi University ; Kenya Agricultural and Livestock Research Organization ; The World Bank ; Jaramogi Oginga Odinga University of Science and TechnologyIntroduction. There is a vast data gap for the national and regional greenhouse gas (GHG) budget from different smallholder land utilization types in Kenya and sub-Saharan Africa (SSA) at large. Quantifying soil GHG, i.e., methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) emissions from smallholder land utilization types, is essential in filling the data gap. Methods. We quantified soil GHG emissions from different land utilization types in Western Kenya. We conducted a 26-soil GHG sampling campaign from the different land utilization types. The five land utilization types include 1) agroforestry M (agroforestry Markhamia lutea and sorghum), 2) sole sorghum (sorghum monocrop), 3) agroforestry L (Sorghum and Leucaena leucocephala), 4) sole maize (maize monocrop), and 5) grazing land. Results and discussion. The soil GHG fluxes varied across the land utilization types for all three GHGs (p ≤ 0.0001). We observed the lowest CH4 uptake under grazing land (−0.35 kg CH4–C ha−1) and the highest under sole maize (−1.05 kg CH4–C ha−1). We recorded the lowest soil CO2 emissions under sole maize at 6,509.86 kg CO2–Cha−1 and the highest under grazing land at 14,400.75 kg CO2–Cha−1. The results showed the lowest soil N2O fluxes under grazing land at 0.69 kg N2O–N ha−1 and the highest under agroforestry L at 2.48 kg N2O–N ha−1. The main drivers of soil GHG fluxes were soil bulk density, soil organic carbon, soil moisture, clay content, and root production. The yield-scale N2O fluxes ranged from 0.35 g N2O–N kg−1 under sole maize to 4.90 g N2O–N kg−1 grain yields under agroforestry L. Nevertheless, our findings on the influence of land utilization types on soil GHG fluxes and yield-scaled N2O emissions are within previous studies in SSA, including Kenya, thus fundamental in filling the national and regional data of emissions budget. The findings are pivotal to policymakers in developing low-carbon development across land utilization types for smallholders farming systems.Item Soil Organic Carbon Stocks under Different Land Utilization Types in Western Kenya(MDPI, 2022-07-06) Kibet, E.; Musafiri, C.M.; Kiboi, M.N.; Macharia, J.; Ng’etich, O.K.; Kosgei, D.K.; Mulianga, B.; Okoti, M.; Zeila, A.; Ngetich, F.K.; University of Embu ; Cortile Scientific ; KCA University ; Kenyatta University ; Moi University ; Kenya Agricultural and Livestock Research Organization (KALRO) ; The World Bank ; Jaramogi Oginga Odinga University of Science and Technology (JOOUST)The up-surging population in sub-Saharan Africa (SSA) has led to the conversion of more land for agricultural purposes. Resilient land utilization types that input carbon to the soil are key in enhancing climate change mitigation. However, there are limited data on different land utilization types’ contribution to climate mitigation through carbon input to soils. The study aims to quantify carbon stock across different land utilization types (LUT) practiced in Western Kenya. The following land utilization types were studied: agroforestry M (agroforestry with Markhamia lutea), sole sorghum, agroforestry L (agroforestry with Leucaena leucocephalaI), sole maize, and grazing land replicated thrice. To determine soil bulk density, SOC concentration, and soil carbon stock, soil samples were collected at depths of 0–5, 5–10, 10–20, and 20–30 cm from different LUTs. A PROC ANOVA was used to determine the difference in soil bulk density, SOC, and SOC stock between different LUTs and depths. The four variables differed across the LUTs and depths. A high soil bulk density was observed at 0–5 cm under grazing land (1.6 g cm−3) and the lowest under agroforestry M (1.30 g cm−3). Conversely, the soil bulk density was low at 20–30 cm under grazing land. The 0–5 cm depth accounted for a high share of SOC and SOC stock under Agroforestry M, while the 10–20 and 20–30 cm depth accounted for the high share of SOC stock under agroforestry L. The study showed differences in SOC across the different depths and LUTs. The findings highlight that agroforestry L and agroforestry M are promising interventions toward climate mitigation through carbon induction to soils.
