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Following the implementation of food safety limits on cadmium (Cd) in cacao products, there has been a growing demand for monitoring Cd in cacao tissues and soils. Traditional methods like acid digestion followed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) are time-consuming and costly. X-ray Fluorescence is an alternative technique that offers advantages in terms of speed, cost, ease of use and less environmental impact. However, to date, relatively high detection limits have impeded its application for food safety limits. This study examines a Monochromatic Energy Dispersive X-ray Fluorescence (MEDXRF) method optimized for Cd analysis as an alternative to ICP-MS. Using a measurement time of 200 s, the average limit of quantification (LOQ) was 0.178 mg Cd kg -1 for biological samples and 0.205 mg Cd kg -1 for soil samples. A strong correlation (y = 1.013 x + 0.003, R 2  = 0.984) with ICP-MS results was found for 95 bean, 16 cacao liquor, 75 leaf, and 91 soil samples. The coefficient of variation (CV) among three replicates was below the threshold value of 15 % for most samples with Cd concentrations above the reported LOQ values. Additionally, a significant difference in CV was obtained between soils sieved over 500 μm (median 8.2 %) or 2 mm (median 9.8 %). However, no significant difference in CV was observed between 500 μm unpeeled beans and cocoa liquor with particle size of 20 μm. Based on our data, the proposed procedure is to analyze three replicates for 200 s with a sample size of 500 μm. The optimized MEDXRF technique offers important advantages in terms of cost-effectiveness and efficiency of routine Cd monitoring in the cacao supply chain, large-scale screening, and scientific research, and could be extended to other crops and heavy metals that are subject to food safety regulation at low concentrations., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Despite the dominance of female labor in agricultural production, female-controlled farm plots have lower efficiency compared to plot managed by male-headed households, which indicates a huge gender disparity in agricultural productivity. Overlooking gender preferences when designing interventions that promote the conservation of soil and water resources might face challenges in adoption and could result in ineffective policies to close the gender gap. This study seeks to analyze gender-specific preferences regarding attributes of soil and water conservation (SWC) in northern Rwanda. A best-worst survey was conducted among 653 respondents, comprising 253 males and 400 females, representing 422 households surveyed between September and December 2019. The analysis of BWS data involved assessing attribute-level relative importance, Pearson correlation, and maximum difference scaling using multinomial logit (MNL). Findings from attribute-level importance analysis revealed significant gender-based disparities in preferences across three important SWC attribute scenarios: the high scenario (between 65 % and 100 %), the moderate scenario (between 50 % and 65 %), and the basic scenario (with <50 % relative importance). The study identified heterogeneity in preferences regarding the relative importance of SWC attribute levels. Pearson correlation analysis revealed substantial synergies among attribute levels linked to land consolidation, improved land tenure, and joint SWC decision-making between genders. Additionally, the study identified trade-offs among multiple levels of SWC attributes, including households' SWC decision-making and physical and structural measures. The results from MNL regression show that both males and females exhibit positive preferences for multiple levels of SWC attributes, but show negative preferences when it comes to household decisions involving multiple SWC strategies. The study highlights the importance of equal opportunities for males and females' participation in agricultural transformation through the adoption of SWC technologies as a fundamental step towards sustainable agricultural intensification. It advocates for gender transformational approaches to incentivize the scaling up of SWC practices and promote packages with lower uptake rates. Additionally, the study suggests enhancing knowledge and extension education in SWC to better understand diverse needs and preferences of female farmers., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Climate change still adversely affects agriculture in the sub-Saharan Africa. There is need to strengthen early action to bolster livelihoods and food security. Most governments use pre- and post-harvest field surveys to capture statistics for National Food Balance Sheets (NFBS) key in food policy and economic planning. These surveys, though accurate, are costly, time consuming, and may not offer rapid yield estimates to support governments, emergency organizations, and related stakeholders to take advanced strategic decisions in the face of climate change. To help governments in Kenya (KEN), Zambia (ZMB), and Malawi (MWI) adopt digitally advanced maize yield forecasts, we developed a hybrid model based on the Regional Hydrologic Extremes Assessment System (RHEAS) and machine learning. The framework is set-up to use weather data (precipitation, temperature, and wind), simulations from RHEAS model (soil total moisture, soil temperature, solar radiation, surface temperature, net transpiration from vegetation, net evapotranspiration, and root zone soil moisture), simulations from DSSAT (leaf area index and water stress), and MODIS vegetation indices. Random Forest (RF) machine learning model emerged as the best hybrid setup for unit maize yield forecasts per administrative boundary scoring the lowest unbiased Root Mean Square Error (RMSE) of 0.16 MT/ha, 0.18 MT/ha, and 0.20 MT/ha in Malawi's Karonga district, Kenya's Homa Bay county, and Zambia's Senanga district respectively. According to relative RMSE, RF outperformed other hybrid models attaining the lowest score in all countries (ZMB: 25.96%, MWI: 28.97%, and KEN: 27.54%) followed by support vector machines (ZMB: 26.92%, MWI: 31.14%, and KEN: 29.50%), and linear regression (ZMB: 29.44%, MWI: 31.76%, and KEN: 47.00%). Lastly, the integration of VI and RHEAS information using hybrid models improved yield prediction. This information is useful for NFBS bulletins forecasts, design and certification of maize insurance contracts, and estimation of loss and damage in the advent of climate justice., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Population growth and climate change challenge our food and farming systems and provide arguments for an increased intensification of agriculture. Organic farming has been seen as a promising option due to its eco-friendly approaches during production. However, weeds are regarded as the major hindrance to effective crop production which varies depending on the type of crop and spacing. Their presence leads to reduced yield, increase in harvest cost and lower the qualities of some produce. Thus, weed management is a key priority for successful crop production. Therefore, we conducted a meta-analysis from published studies to quantify possible differences on weed density, diversity and evenness in organic and conventional farming systems and best intervention for weed management in organic farming system. Data included were obtained from 32 studies where 31 studies with 410 observations were obtained for weed density, 15 studies with 168 observations for diversity, and 5 studies with 104 observations for evenness. Standard deviation of mean was obtained from the studies, log transformed using natural logarithms and the effect size pooled using standardized mean difference (SMD). Publication bias was determined through funnel plot. Results showed that organic farming has significant higher weed density (P < 0.01) , diversity (P = 0.01) , and evenness (P < 0.05) compared to conventional farming. Despite so, diversified crop rotation has been proved to reduce weed density in organic farming by up to 49 % while maize-bean intercropping decrease densities of Amaranthus ssp, Cyperus ssp and C ammelina ssp compared with monocropping. Use of mulch after one hand weeding was found to control up to 98 % of weeds and use of cover crop between 24 % and 85 % depending on the type of the cover crop. The study results show that organic farming encourages high weed density, diversity and evenness but use of the integrated approaches can help to maintain weed density at a manageable level., Competing Interests: Authors have got no competing interest for the manuscript., (© 2024 The Authors. Published by Elsevier Ltd.)

Cassava ( Manihot esculenta Crantz) is a crop of global economic and food safety importance, used for human consumption and in various industrial applications. The genebank of the Genetic Resources Program of the Alliance of Bioversity International and CIAT currently holds the world's largest cassava collection, with 5965 in vitro accessions from 28 countries. Managing this extensive collection involves indexing quarantine pathogens as a phytosanitary certification requirement for safely distributing cassava germplasm. The study therefore aimed to optimize a quantitative diagnostic protocol to detect cassava common mosaic virus (CsCMV) using quantitative PCR (qPCR) as a better alternative to other molecular techniques. This was done through designing primers and a probe in the RdRP region of CsCMV, and optimizing the qPCR conditions of the diagnostic protocol using primer concentration assays, and reaction amplification conditions such as volume and reaction time. We also evaluated the qPCR protocol by comparing the results of 140 cassava accession evaluations using three diagnostic methodologies (DAS-ELISA, end-point PCR, and qPCR) for CsCMV. Our protocol established that qPCR technique analysis is ten-times more sensitive in detecting CsCMV compared to end-point PCR, showing a maximum detection level of 77.97 copies/μL of plasmid, with 76 min of reaction time. The comparison allowed us to verify the level of CsCMV detection through the techniques evaluated, concluding that qPCR was more sensitive and allowed the quantification of viral concentration. The optimized qPCR protocol will be used to accelerate diagnostic screening of cassava germplasm for the presence or absence of CsCMV to ensure safe movement and distribution of disease-free germplasm., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Anthracnose caused by Colletotrichum lindemuthianum is the major common bean disease worldwide causing complete yield loss under favourable disease conditions. This study aimed to determine phenotypic traits associated with anthracnose resistance for future use in breeding programmes. Twenty-two common bean varieties (CBVs) were selected basing on susceptibility to anthracnose, advanced breeding lines, improved variety resembling advanced breeding lines and the farmer variety widely grown in Tanzania. Selected varieties were planted in anthracnose hotspot fields and the same CBVs were planted in a screen house to validate resistance to anthracnose. Anthracnose infection score, leaf length, leaf width, length of fifth internode, length of petiole, plant vigour, canopy height and canopy width were recorded. Data on number of plants emerging; days to flowering; days to maturity; plant stands at harvest; and grain yield were also collected and analysed using R software. Phenotypic traits evaluated differed significantly among genotypes, environment and genotype by environment interaction. Seventy-five percent of phenotypic traits evaluated were positively correlated to anthracnose resistance. Highly-strong correlations to anthracnose were observed on number of days to maturity, plant stands at harvest, plant vigour and grain yield. Leaf length, leaf width, length of fifth internode, length of petiole and number of stands emerging were strongly correlated to anthracnose resistance. Additive main effects and multiplicative interaction analysis (AMMI) revealed highest contribution of environment on anthracnose infection-58.9% and grain yield -84.9% compared to genotype effects on anthracnose infection -32.7% and grain yield-15.7%. Based on these results, four traits - plant vigour, number of days to maturity, number of plant stands at harvest and grain yield - are recommended for selecting anthracnose-resistant varieties. NUA 48, NUA 64 and RWR 2154 were superior varieties, resistant to anthracnose and high yielding, while Sweet Violet and VTT 923-23-10 were most stable varieties across environments. Further on-farm research is suggested to assess their performance and identify traits preferred by farmers., Competing Interests: Edith Laurence Kadege reports financial support was provided by Alliance of Bioversity International and the 10.13039/501100005346International Center for Tropical Agriculture Arusha, Tanzania. The authors declare no conflict of interest or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

The cattle sector plays a pivotal role in the economies of numerous Latin American and Caribbean countries. However, it also exerts a significant impact on environmental degradation, including substantial contributions to greenhouse gas emissions (accounting for 23.5 % of global livestock emissions) and deforestation (70 % attributed to livestock in South America). This article aims to investigate the complex, long-term, and short-term relationships between population growth, pastureland expansion, deforestation, and the cattle sector in 15 countries across the region, focusing on their effects on greenhouse gas emissions as well as beef and dairy production. Utilizing data from FAOSTAT spanning the period from 1990 to 2019, a cointegrated panel model was developed using the Pooled Mean Group technique, resulting in the estimation of six models. The aggregate-level results for the region reveal the presence of relatively stable long-term relationships. This implies that over time, the influence of population growth, pastureland expansion, and deforestation on greenhouse gas emissions from cattle production tends to diminish in significance. This long-term behavior may be particularly pronounced in countries with more developed cattle sectors, where efforts to mitigate the environmental impacts of cattle production, such as promoting improved forage technologies, silvo-pastoral systems, grazing management practices, and the implementation of policies, regulatory frameworks, and incentives, have gained traction. These progressive countries can serve as regional benchmarks, and the lessons they have learned hold valuable insights for the sustainable intensification of cattle production in countries with less-developed cattle sectors., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Stefan Burkart reports financial support was provided by 10.13039/501100015815CGIAR Consortium. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

With climate change, population growth, and land degradation exerting mounting pressures on agricultural systems in developing countries, climate-smart agriculture (CSA) strategies have been prioritized as a means to strengthen smallholder farmers' resilience. However, precise targeting methodologies remain a challenge. This study employs a comprehensive approach, integrating Socio-economic, and Biophysical (SEBP), and the Five Capitals Model analyses encompassing human, social, physical, natural, and financial capital. The study employs factor analysis for mixed data (FAMD), cluster analysis using partitioning around the medoids (PAM) and univariate and bivariate techniques to identify and classify distinct typologies of smallholder farming systems in Senegal's Tambacounda and Sedhiou regions in 2020. A probit regression model gauges CSA adoption probability, to better focus CSA efforts. Results underscore the pivotal role of SEBP factors in shaping distinct farmer typologies, enabling precise CSA targeting. Geographical distribution patterns of these typologies reveal non-random clustering, particularly in specific regions. Four farmer typologies emerge: Cluster 1 (Sedhiou, low-income, high climate challenges), Cluster 2 (Sedhiou and Tambacounda, low-to middle-income, moderate climatic challenges), Cluster 3 (Tambacounda, high income, favorable climate), and Cluster 4 (Tambacounda, low income, severe climate challenges). Technology mismatches emerge between farmers' SEBP profiles and capital assets, prompting the identification of relevant technologies for soil fertility restoration and increased output. These findings highlight the importance of implementing CSAs in accordance with specific requirements, such as enhancing soil fertility, yield, and nutritional quality. A contextual understanding of local agricultural dynamics is likewise necessary for optimizing intervention strategies, according to the study., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 Published by Elsevier Ltd.)

Cattle production in Colombia has an important social and economic role but causes considerable environmental impacts, such as deforestation and greenhouse gas emissions by ruminants, particularly methane. Thus, technological innovations aimed at reducing these impacts must focus on both economic and environmental sustainability. Silvo-pastoral systems (SPS) offer productivity increases while generating environmental benefits and ecosystem services and are therefore at the center of debate around sustainable production alternatives. The objective of this article is to evaluate the economic-environmental performance of two proposed SPS for a cattle fattening system for the Colombian context: (i) Urochloa brizantha cv. Toledo and (ii) Urochloa hybrid cv. Cayman, both in association with Leucaena leucocephala trees for browsing and shade provision. They are compared with the respective base scenarios of only using the grasses in monocultures. The study consists of a financial analysis, which estimates potential profitability increases in beef production in the SPS, and an environmental evaluation, which estimates the monetary values of microclimatic regulation and reduction of methane emissions. The value of methane emission reductions is then integrated into a combined economic-environmental evaluation. Results show that both SPS improve the profitability indicators of the production system and reduce the probability of economic loss. Likewise, the reduction of methane emissions in the SPS is estimated at US$6.12 per cattle, and the economic value of microclimatic regulation at US$2,026 per hectare., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Iron and zinc deficiencies cause high health risk to young children and expectant mothers in sub Saharan Africa. The development of biofortified common bean ( Phaseolus vulgaris L.) varieties could address the acute micronutrient deficiencies with associated improvement in the nutrition and health of women, children and adults. The objective of this study was to determine the mode of gene action and genetic advance in iron and zinc levels in common bean. Field experiment was carried out using six generations of two populations made of crosses between pairs of low iron, low zinc and high iron, moderate zinc genotypes (Cal 96 ˣ RWR 2154; MCR-ISD-672 ˣ RWR 2154). Each generation (P 1 , P 2 , F 1 , F 2 , BC 1 P 1 and BC 1 P 2 ) was evaluated on the field in a randomized complete block design with three replications. Generation mean analysis were performed for each trait measured in each of the crosses while iron and zinc levels were quantified by x-ray fluorescence. The study showed that both additive and non-additive gene effects were important in determining the expression of high iron and zinc levels. Iron concentration in the common bean seeds ranged from 60.68 to 101.66 ppm while zinc levels ranged from 25.87 to 34.04 ppm. Broad sense heritability estimates of iron and zinc were high in the two crosses (62-82% for Fe and 60-74% for Zn) while narrow sense heritability ranged from low to high (53-75% for Fe and 21-46% for Zn). Heritability and genetic gain were used as selection criteria for iron and zinc, and it was concluded that doing so would be beneficial for future improvement., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)

Zinc deficiency in agricultural soils is a current global agroecosystems challenge. Maize exhibits elevated susceptibility to Zn deficiency and low response to zinc fertilization. As a result, there are contradicting literature reports on the crop response to zinc fertilization. This meta-analysis synthesized the current evidence on maize response to zinc fertilization from different studies and highlighted the potential innovations to improve the crop response to zinc application. Systematic literature searches were conducted on the Web of Science and Google Scholar for peer-reviewed publications. From the selected publications, data extracted were maize grain yield and maize grain zinc concentration. The meta-analysis was conducted in R statistical environment using the metafor package. The ratio of means was the chosen effect size measure used. The assessment of effect size heterogeneity showed that the study effect sizes were significantly heterogeneous and also publication bias was evident. The analysis showed 17% and 25% maize grain yield and grain zinc concentration response to zinc fertilization. As a result, zinc fertilization was associated with yield increments of up to 1 t ha -1 and 7.19 mg kg -1 grain zinc concentration over the control (no zinc application). Despite the observed maize grain response to zinc application, the median concentration of grain Zn was below the 38 mg kg -1 recommended maize grain zinc concentration to combat human zinc deficiency ( hidden hunger ). As a result, potential innovations likely to achieve sufficient maize grain zinc content were highlighted including the use of nano-particulate zinc oxide, foliar zinc application, timing of zinc application, precision fertilization and zinc micro-dosing. Due to scanty literature on the progress of these innovations in maize, follow-up studies are recommended to evaluate their potential success in the agronomic bio-fortification of maize with zinc., Competing Interests: The authors have no conflict of interest to declare., (© 2023 The Authors.)

Persistent food insecurity in the global south has triggered calls for sustainable development worldwide. Moreover, more than a quarter of the world's population suffers from micronutrient deficiencies or hidden hunger. The population bulge, declining soil fertility and inadequate/inappropriate use of farm inputs in Sub-Saharan Africa place it in a precarious position. Multi-nutrient fertilizer blends have been mooted as a key innovation in closing yield gaps and boosting food and nutrition security. This study assessed the extent of multi-nutrient fertilizer blends utilization and yield response across agroecological zones and their on-farm profitability under Kenyan smallholder farmer conditions. We collected data through a detailed household survey conducted in eight counties in Kenya representative of high, medium, and low productivity zones using a sample of 1094 smallholder farmers. Multi-nutrient fertilizers increased maize yields significantly ( P < 0.05 ), eliciting a 400% yield increase compared to the control and 108% greater maize yield than conventional fertilizers in the high potential zone. Conversely, at 3.7 t/ha conventional fertilizers elicited a significant ( P < 0.05 ) yield response in Irish potatoes in the high potential areas. Multi-nutrient fertilizers increased on-farm profitability of crops, specifically for potato production systems where a benefit: cost ratio (BCR) of more than 2 was observed. Farmers may break even when they use multi-nutrient fertilizers on maize particularly in the low potential areas. Therefore, there is considerable potential for multi-nutrient fertilizers to increase crop productivity while being economically viable across agroecological zones and cropping systems. However, the uptake of multi-nutrient fertilizers among farmers is quite low across the country, except for small pockets where limited interventions have been carried out. This calls for sustained efforts to scale multi-nutrient fertilizers with a focus on clear messaging that stresses the need to apply appropriate rates of various nutrients including the secondary nutrients and micro-nutrients., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Beans are one of the most important cheap source of protein in developing countries. However, their utilisation in the diets of many people remains limited due to long cooking time, among others. Therefore, it is imperative to identify ways to enhance utilisation of beans. The aim of the current study was to assess the effects of soaking and cooking in different types of water (tap, borehole, acidulated- 1.0 percent citric acid and soda- 0.2 percent sodium bicarbonate) on cooking time (CT), split percentage (SP) and total soluble solids (TSS) in broth of different varieties of beans. Results show that soaking significantly reduced CT across eight varieties from an average CT of 109.5-84.6 min in tap water, 109.5-85.2 min in borehole water, 115.9-92.7 min in acidulated water and 82.0-51.2 min in soda water representing 22.7%, 22.1%, 20.0% and 37.6% reduction in CT, respectively. Soaking generally decreased SP and varietal differences were observed suggesting beans are less likely to break when soaking precede cooking. Although cooking in soda water significantly reduced CT, unfortunately, it increased SP. Acidulated water extended CT but reduced SP in almost all varieties. Soaking generally decreased TSS in broth from 7.0 to 6.7% in tap water, 6.1-5.8% in borehole water and 11.3-7.7% in soda water while it increased TSS in acidulated water from 18.2 to 20.6% across all the eight varieties which suggest reduction in leaching out of bean solids into cooking water which is consistent with reduced SP of soaked beans. While use of soda water reduced cooking time and therefore saved time and energy, its effect of increasing split percent may not be appealing to some consumers. This study has demonstrated that bean soaking significantly reduced cooking time and split percent and these can also be affected by type of cooking water., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors.)

Improving agricultural productivity to improve food security and feed the future generation is needed. One of the ways to achieve this is by adopting low-cost solutions such as soil carbon enhancing practices (SCEPs). Given the complexity of adoption decisions, technologies are either adopted as substitutes or complements. A structured survey was utilized to collect data from 334 households in Western Kenya to estimate the impact of adopting SCEPs in combination and identify challenges hindering the adoption of the technologies. Two models, namely a multinomial endogenous treatment effect model and a multi-valued treatment effect model under conditional independence, were utilized to assess the impact of adoption on maize yield. Key variables established to influence adoption were literacy level, tenure security, and market participation. It was further revealed that adopting farmyard manure, intercropping, and a combination of intercropping and farmyard manure had a significant and positive impact on maize yield. This creates a need to promote the adoption of low-cost SCEPs to increase productivity and food security., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors.)

Declining soil fertility is one of the major causes of food insecurity and high levels of poverty, both of which tend to hamper economic development in sub-Saharan Africa (SSA). To improve soil fertility, the implementation of soil organic carbon (SOC) enhancement technologies has become crucial to slowing land degradation, through increasing SOC, which is the basis of soil fertility. Using data from 381 households from Azuga-Suba and Yesir watersheds in Ethiopia, this study explores the extent of the adoption of technologies that enhance SOC. Soil organic carbon enhancing technologies include the use of manure, fertilizer, and crop residue management. The Probit model was used to assess what constrains the adoption of these technologies. The results indicate that fertilizer is the most adopted technology having over 90% adoption in both watersheds. Manure at 28% and 56% adoption while crop residue management at 37% and 26% adoption in Azuga-Suba and Yesir respectively. Technology adoption is highly constrained by lack of education, access to extension services, and access to credit services. Institutions and local farmer groups influence these constraints through training, provision of information, offering incentives, and credit services. Large plots hinder the use of manure and fertilizer due to the bulky nature of manure and the high costs of fertilizers. Insecurity in land tenure limits the adoption of manure and residue management. Perception of soil erosion and soil fertility tends to constrain the adoption of SOC technologies, as farmers are afraid that all improvements through soil amendment will be diminished through soil erosion. At the same time, farmers do not perceive the importance of SOC enhancing technologies in plots that were fertile. These results imply that strengthening institutions that enhance farmers' knowledge and provide credit as well as strengthening social protection schemes and farmer groups is crucial in promoting the adoption of these technologies., Competing Interests: The authors declare no conflict of interest., (© 2021 The Authors.)

Conservation agriculture practices involving zero tillage and residue retention are promising nutrient management strategies for soil health restoration. Despite their potential positive impact on soil fertility, improved crop yields and increased revenues for smallholder farmers; their effect on nitrogen inputs and crop growth is not clearly understood. This may limit their potential as a nutrient management strategy that may remedy soil degradation and boost crop yields for farmers. This study investigated how different tillage practices, crop residues and inorganic nitrogen (N) options affect maize production, soil fertility and economics of smallholder farming systems. The study was conducted in a short-term (2 years) on-station trial, under randomized complete block design with three replications in a maize monocrop system. Six treatments, involving three different rates of maize stover residue (0, 3 and 5 t ha -1 ) and inorganic N (0, 3 and 5 t ha -1 ) inputs, respectively, were assessed under conventional and zero tillage systems. Mineral N and organic C were assessed at four depths (0-10 cm, 10-30 cm, 30-60 cm and 60-90 cm) whereas soil aggregate distribution was assessed at 0-5 cm, 5-10 cm, 10-15 cm and 15-20 cm depths. Application of inorganic N as the only input increased ( p ≤ 0.05) grain yield (with the yields doubling in the short rains (SR) of 2015 and increasing by 1.4 times in long rains (LR) of 2016) compared to unfertilized control treatment. Treatment, soil depth and the time of sampling significantly affected soil mineral N concentration ( p ≤ 0.05). Soil organic C reduced significantly ( p ≤ 0.05) with sampling depths, but no differences were observed across treatments. At 0-5 cm depth, the proportion of large macroaggregates in zero tillage increased (48%; p ≤ 0.05) after application of crop residues at 5 t ha -1 relative to 3 t ha -1 . Zero tillage treatment with application of 5 t ha -1 of residue and 80 kg N ha -1 was the most dominant and most profitable compared to the other treatments. This treatment had a benefit cost ratio (BCR) of 2.9 (in the short rains season of 2015) and 3.0 (long rains of 2016 seasons). Its marginal rate of return (MRR) was 368% (in the 2015 short rains season) and 416% (in the 2016 long rains season). This makes it a good nutrient management strategy with potential of optimizing maize yields., Competing Interests: The authors declare no conflict of interest., (© 2021 The Authors.)

A majority of smallholder farmers in sub-Saharan Africa (SSA) countries depend to a large extent on agriculture for food security and income. Efforts aimed at improving farm-related profitability are therefore important to improving livelihoods among smallholder farmers. In Ghana, for example, smallholder farmers that depend on agriculture face serious risks especially those related to climate change and variability and soil degradation. Notwithstanding these dangers, evidence of the published literature on how best to tackle these challenges is limited. Over the recent decades, however, there has been advancement by programs channelling resources into Climate-Smart Agricultural (CSA) practices to improving smallholder livelihoods and food security. The interest in advancing investment in CSA practices is a key pathway that has the potential to significantly reduce the negative effect of climate change and variability risks on smallholder farmers livelihoods. Investing in CSA practices is also a key pathway to improving farm yield per unit area. Consequently, smallholder farmers are adopting and implementing CSA practices. Despite that, a gap still exists on the profitability of undertaking such an investment, as this is key in determining the sustainability of CSA practices. On this basis, the present study undertook a detailed cost-benefit analysis (CBA) of seven CSA practices identified with smallholder farmers in the coastal savannah agro-ecological zone of Ghana. A total of 48 smallholder farmers that had adopted these practices were studied. Three CBA indicators namely the net present value (NPV), internal rate of return (IRR) and payback period (PP) were assessed for each of the seven CSA practices. The results showed that out of the seven CSA practices examined, six of them were profitably suitable for adoption and scaling up from the perspective of smallholder farmers as well as the public perspective. The finding from this study, therefore, fill the current information gap in the literature on the costs and benefits of adopting CSA practices on household livelihoods in Ghana. Such a finding is critical to the promotion and scaling up the adoption of CSA practices by smallholder farmers and serve as a basis of formulating appropriate guidelines and policies for supporting CSA practices., Competing Interests: The authors declare no conflict of interest., (© 2021 The Authors.)

Most smallholder farmers in sub-Saharan Africa (SSA) are adversely affected by low soil fertility, land degradation and climate change-related shocks such as drought. These problems lead to low productivity and low household income. In addition, the adoption of soil carbon enhancing practices remains low in Western Kenya. This study analyses the factors that influence the probability and extent of adoption of soil carbon enhancing practices in Western Kenya utilizing plot-level information, socioeconomic characteristics and external supporting factors. Multivariate probit model and generalized ordered logit were utilized to assess the adoption of multiple soil carbon enhancing practices and the extent of adoption respectively. Results indicate that the adoption of soil carbon enhancing practices is correlated, suggesting interrelation in farmers' adoption decisions. Both the multivariate probit model and generalized ordered probit results indicate that the probability and extent of adoption of soil carbon enhancing practices are influenced by plot-level characteristics, literacy level, access to agricultural credit, agricultural group membership, participation in the market, and gender of the household., (© 2020 Published by Elsevier Ltd.)