• Energy Research

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.

AbstractIn sub‐Saharan Africa (SSA), few studies have quantified greenhouse gas (GHG) emissions following application of soil amendments, for development of accurate national GHG inventories. Therefore, this study quantified soil GHG emissions using static chambers for two maize cropping seasons (one full year) of four different soil amendments in the central highlands of Kenya. The four treatments were (i) animal manure, (ii) inorganic fertilizer, (iii) combined animal manure and inorganic fertilizer, and (iv) a no‐N control (no amendment) laid out in a randomized complete block design. Cumulative annual soil fluxes (February 2017 to February 2018) ranged from −1.03 ± 0.19 kg CH4‐C ha−1 yr−1 from the manure inorganic fertilizer treatment to −0.09 ± 0.03 kg CH4‐C ha−1 yr−1 from the manure treatment, 1,391 ± 74 kg CO2‐C ha−1 yr−1 from the control treatment to 3,574 ± 113 kg CO2‐C ha−1 yr−1 from the manure treatment, and 0.13 ± 0.08 to 1.22 ± 0.12 kg N2O‐N ha−1 yr−1 in the control and manure treatments, respectively. Animal manure amendment produced the highest cumulative CO2 emissions (P < 0.001), N2O emissions (P < 0.001), and maize yields (P = 0.002) but the lowest N2O yield‐scaled emission (YSE) (0.5 g N2O–N kg−1 grain yield). Manure combined with inorganic fertilizer had the highest cumulative CH4 uptake (P < 0.001) and N2O YSE (2.2 g N2O–N kg−1 grain yield). Our results indicate that while the use of animal manure may increase total GHG emissions, the concurrent increase in maize yields results in reduced yield‐scaled GHG emissions.

Most sub-Saharan Africa smallholder farming systems are highly heterogeneous. Direct quantification of greenhouse gas emissions from these farming systems is hampered by diversity at farm-level. Each farm contributes differently to greenhouse gas (GHG) emissions and consequently GHG inventories. Typologies can be used as a mechanism of addressing farming systems’ heterogeneity by grouping them into specific farm types. With the GHG quantification simplification initiatives in mind, we developed smallholder farm typologies based on soil fertility inputs. We assessed nitrogen application rate, soil fertility management technologies and the socio-economic factors diversity among the farm typologies in the central highlands of Kenya. We used data from a cross-sectional household survey with a sample size of 300 smallholder farmers. We characterized the farm types using principal component analysis (PCA). To develop farm typologies, we subjected the PCA-derived typologies related factors to cluster analysis (CA). The results showed six farm types: Type 1, comprising cash crop and hybrid cattle farmers; Type 2, comprising food crop farmers; Type 3, composed of coffee-maize farmers; Type 4, comprising millet-livestock farmers; Type 5, comprising highly diversified farmers, and Type 6, comprising tobacco farmers. Land size owned, total tropical livestock unit, the proportion of land and nitrogen applied to different cropping systems were significant in the construction of farm typologies. Univariate analysis showed the household head's level of education, hired labour, group membership, access to extension services, and proportion of income from cropping activities as critical factors influencing farm typologies in the study area. This study demonstrates the importance of smallholder farm typologies in identifying greenhouse gas emissions hotspots, designing quantification experiment and policy framing. We concluded that policies and intervention measures targeting climate-smart agriculture at smallholder farms should consider not only farm-level soil fertility management technologies but also socio-economic characteristics that influence their adoption.

As influenced by agricultural practices, soil organic matter (SOM) stability is imperative in maintaining soil fertility and crop production. Integrated soil management practices have been recommended for soil fertility improvement by enhancing soil organic matter. We examined the SOM stability under integrated soil management practices for six consecutive cropping seasons in the high agricultural potential area of the Central Highlands of Kenya. The experimental design was a complete randomized block design with fourteen treatments replicated four times. The treatments were minimum (Mt) and conventional tillage (Ct) combined with sole mineral fertilizer (Mf), crop residue combined with mineral fertilizer (RMf), crop residue combined with mineral fertilizer and animal manure (RMfM), crop residue combined with animal manure and Dolichos Lablab L. intercrop (RML), crop residue combined with Tithonia diversifolia and animal manure (RTiM), and crop residue combined with Tithonia diversifolia and phosphate rock (Minjingu) (RTiP), as well as a control (no inputs). SOC was higher in treatments with organic inputs and a combination of organic and inorganic inputs. Treatments with sole mineral fertilizer and no input recorded lower SOC amounts. The C functional groups followed the sequence: alkyl C (53%) > O-alkyl C (17%) > aromatic C (9%) > carboxyl C (8%) > methoxyl C (7%) > phenolic C (6%). The alkyl C proportion was higher in organic inputs treatments, while O-alkyl C was higher in organic and inorganic fertilizer treatment combinations. Methoxyl C, aromatic C, and phenolic C proportion of SOC was greater in crop residue and mineral fertilizer combination, while carboxylic C was lower than the control in most treatments. In addition, the organic inputs treatments had a higher alkyl C/O-alkyl C ratio, increased aliphaticity, and higher hydrophobicity. Applying organic fertilizers individually or in combination with inorganic fertilizers could potentially increase C storage in the soil, thereby enhancing SOC stocks.

Climate variability in recent decades has intensified in the SSA region, which makes it imperative to explore adequate adaptation and mitigation strategies to offset its current and future adverse impacts. Farmers' perception of climate variability can significantly influence their coping, mitigation, and adaptation potential. This study assessed farmers' perceptions of indicators and consequences of climate variability and explored factors influencing their perception of climate variability and adoption of climate coping strategies. A cross-sectional survey design was used to sample 300 farmers in the Central Highlands of Kenya. Binary logistic regression models were used to determine factors that influenced the perception of climate variability, adaptation, and mitigation strategies based on three predictor sets, including socioeconomic, institutional, and environmental dimensions. Three climate adaptation and mitigation strategy groups adopted by farmers, including crop adjustment, nutrient management, and soil and water management practices, were subjected to binary logistic regression models. The core determinants of farmers' perception of climate variability included tropical livestock unit (TLU, p = 0.008), access to agricultural training (p = 0.022), change in agricultural production (p = 0.005), change in forest cover (p = 0.014), soil fertility status (p = 0.039), and perceptions of soil erosion (p = 0.001). Most farmers reported changes in all climatic indicators during the decade preceding the survey, including increasing temperature (80%), reduced precipitation (78%), and declining season lengths (76%). There were significant relationships between climate variability perceptions and coping strategies, with the soil and water management set showing stronger links with climate perceptions compared to crop adjustment and nutrient management strategies. Critical mitigation and adaptation strategies to cope with climate variability implemented by farmers included the use of fertilizer and manure in combination (71%), terracing (66%), and crop rotation (60%). Farmers' perceptions significantly determined the adoption of climate-smart agriculture technologies, and environmental determinants strongly influenced climate variability coping strategies. Therefore, while formulating climate sustainability-related policies, farmers' perceptions should be considered.

Deficits in soil moisture and low soil fertility are the major constraints to smallholder farming systems in the SSA (sub-Saharan Africa) region. This study evaluated the effects of tied ridging and selected soil fertility inputs on; soil water content at different depths, maize yields, and economic returns. The treatments were: Tithonia diversifolia + inorganic fertilizer, manure + inorganic fertilizer, inorganic fertilizer, and control with or without tied ridging as the soil water conservation factor. Data were subjected to analysis of variance, and the means were separated using LSD at p ≤ 0.05. Treatments with Tithonia diversifolia or manure combined with inorganic fertilizer with or without tied ridging consistently affected soil water content positively. The effect of tied ridging on soil water content was greater during the short rain season compared to the long rains. In addition, there was evidence that tied ridging and organic soil inputs resulted in greater soil moisture conservation during the critical silking and tasselling maize phenological stages during the short rain season. Treatments had significant effects on grain and stover yields during the long rain 2016 season (p < 0.0001 and p = 0.0477, respectively) and the short rain 2016 season (p < 0.0001 and p = 0.0035, respectively). The highest (4.87 Mg ha−1) maize grain yield was recorded in Tithonia diversifolia plus inorganic fertilizer under tied ridging in the long rain 2016 season, while manure + inorganic fertilizer without tied ridging gave the highest yields (1.27 Mg ha−1) in the short rain 2016 season. The highest net benefits of US$ 1229.90 ha−1 and US$ 171.57 ha−1 were recorded under Tithonia diversifolia plus inorganic fertilizer with tied ridging during the long and short rain seasons, respectively. Overall, the best-performing treatments in yields and profitability were those that combined organic and inorganic fertilizers, regardless of the presence or absence of tied ridging. Climate-smart agricultural strategies combining tied ridges and organic inputs should be an integral component of farmer management if losses related to soil fertility and water stress are to be minimized under erratic rainfall regimes in the semiarid farming systems of the SSA region.

Climate change and low agricultural productivity are the major hurdles facing sorghum farming in the Lake Zone Region of Tanzania. However, there is limited information on the contribution of sustainable projects in greening the sorghum value chain in Tanzania. This study aims to analyze how to develop a resilient and sustainable sorghum value chain using a project approach. Primary and secondary data were collected and used. Primary data were collected using key informant interviews (KII) administered to the value chain actors using audio recordings and notes. Secondary data were obtained from project-related project documents, reports, publications, and conference proceedings. The audio recordings were transcribed into lengthy notes summarized for ease of interview theme identification. To enhance access to improved seeds and fertilizers and advisory services, a linkage between the agro-dealers (input suppliers), farmers, and extension personnel was established to improve farmers’ yield potential. Good agricultural practices, e.g., planting methods and pest management and improved seed varieties that were drought tolerant, early maturing, and high yielding, such as Macia and Tegemeo, were readily available in shops and promoted through the establishment of demo plots. Local aggregation of sorghum grain helped to ease transport-to-market logistics for farmers and contributed to lower transport costs. Mechanized threshing was promoted to ensure the high-quality crop is sold to the off-taker for premium prices and meets the export market requirements. We highlight the Lake Zone project experiences and lessons learned to demonstrate the potential for building resilience and sustainability of the sorghum value chain.