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The production of soybean is gaining more attention in West Africa. In light of projected changes in climate, there is a need to assess the potential impacts on yield productivity and variability among farmers. An evaluated GROPGRO module of the Decision Support System for Agro-technological Transfer (DSSAT) was used to simulate soybean productivity under both historical (1980–2009) and projected climate scenarios from multiple general circulation models (GCMs) under two representative concentration pathways (RCPs): 4.5 and 8.5. Agronomic data from 90 farms, as well as multiple soil profile data, were also used for the impact assessment. Climate change leads to a reduction (3% to 13.5% across GCMs and RCPs) in the productivity of soybean in Northern Ghana. However, elevated atmospheric carbon dioxide has the potential to offset the negative impact, resulting in increased (14.8% to 31.3% across GCMs and RCPs) productivity. The impact of climate change on yield varied widely amongst farms (with relative standard deviation (RSD) ranging between 17% and 35%) and across years (RSD of between 10% and 15%). Diversity in management practices, as well as differences in soils, explained the heterogeneity in impact among farms. Variability among farms was higher than that among years. The strategic management of cultural practices provides an option to enhance the resilience of soybean productivity among smallholders. [ABSTRACT FROM AUTHOR]

Abstract: The CERES-sorghum module of the Decision Support System for Agro-Technological Transfer (DSSAT) model was calibrated for sorghum (Sorghum bicolor (L.) Moench) using data from sorghum grown with adequate water and nitrogen and evaluated with data from several N rates trials in Navrongo, Ghana with an overall modified internal efficiency of 0.63. The use of mineral N fertilizer was found to be profitable with economically optimal rates of 40 and 80kgNha−1 for more intensively managed homestead fields and less intensively managed bush fields respectively. Agronomic N use efficiency varied from 21 to 37kggrainkg−1 N for the homestead fields and from 15 to 49kggrainkg−1 N in the bush fields. Simulated grain yield for homestead fields at 40kgNha−1 application was equal to yield for bush fields at 80kgNha−1. Water use efficiency generally increased with increased mineral N rate and was greater for the homestead fields compared with the bush fields. Grain yield per unit of cumulative evapo-transpiration (simulated) was consistently higher compared with yield per unit of cumulative precipitation for the season, probably because of runoff and deep percolation. In the simulation experiment, grain yield variability was less with mineral N application and under higher soil fertility (organic matter) condition. Application of mineral N reduced variability in yield from a CV of 37 to 11% in the bush farm and from 17 to 7% in the homestead fields. The use of mineral fertilizer and encouraging practices that retain organic matter to the soil provide a more sustainable system for ensuring crop production and hence food security. [Copyright &y& Elsevier]

Abstract: The cropping systems model APSIM (Agricultural Production Systems sIMulator) was applied to assess the response of sorghum grain yield to inorganic fertilizers applications and residue retention in diverse farmers’ management systems (homestead fields and bush farms). The model was parameterized using data collected from experiments under optimum growth conditions (limited water or nutrient stress). Independent data from field experiments with three levels of P and four levels of N fertilizers conducted at two different locations and soils were used to evaluate the model. Soil water and fertility parameters measured were used for simulations while same starting conditions were assumed for unmeasured parameters for all trials. APSIM predicted the grain yield response of sorghum to both N and P applications with an overall modified internal coefficient of efficiency of 0.64. Following model parameterization, a long-term simulation study was conducted using a stochastic weather data derived from historical weather data to assess the effects of crop residue management on grain production. A gradual decline in sorghum grain yield was simulated over the 30-year simulation period in both the homestead fields and the bush farms, with yields being much lower in the latter under farmers’ management practices. Half the amount of mineral N fertilizer used in the bush farms was needed in the homestead fields to produce the average grain yields produced on the bush farm with full fertilization, if crop residues were returned to the fields in the homestead. Year-to-year variability in grain yield was consistently higher with the removal of crop residues, irrespective of management systems. APSIM was responsive to both organic and inorganic fertilizer applications in the study area and also highlighted the essential role of crop residues and inorganic fertilizer in influencing the temporal sorghum grain production and hence the impact of farmers’ management practices on food security. This was evident in the rapid decline in soil organic carbon (SOC) accompanied by a decline in grain yield over the 30 years of cropping. The use of inorganic fertilizer and retention of crop residues (SOC) are critical for attaining food security in the study area. [Copyright &y& Elsevier]

• Soil degradation impact on maize yield simulated for data-sparse regions. • Simulated maize yield declined with degradation severity. • Soil erosion could be described by depth loss rather than mass loss. The harsh environmental conditions and poor management of agricultural fields in many parts of the tropics lead to rapid soil degradation and low crop yields, once native lands are converted to agriculture. The assessment and management of degraded fields is constrained by the low resource availability to support field data collection. Crop simulation models offer tools for assessing the degradation problem and support improved management decisions. Though a host of comprehensive crop models have been published, their wide-scale application in the tropics, especially as decision support tools continues to lag, largely due to the types and fine-scale data requirements for model execution, which are often lacking in the tropical regions. In this paper, we present a simple modelling framework that is capable of simulating the impact of soil degradation on maize yields using field-scale agriculture data. The major departure of this new modelling framework is the description of erosion in terms of soil depth loss instead of soil mass loss. The framework, which was developed from an assembly of relevant theory and equations in the published literature is designed to address the data paucity challenges often encountered in many tropical regions. The model was programmed in Excel and tested against published observed maize yields for situations where the maize was grown on simulated eroded soils of varying severity and nitrogen application rates. The model simulated well the decline in maize yields with increased erosion severity and varying nitrogen application rates (R2 = 0.79, nRMSE = 28% and Willmott d -index = 0.95). It is concluded that the model, though simple, provided a framework for assessing maize yield response to varied soil degradation conditions. [ABSTRACT FROM AUTHOR]

The efficiency of mineral fertilizer use in most soils in Sub-saharan Africa is low. Prominent among the reasons for this is low soil carbon stock. In this study, we hypothesized that in the short term, combined use of biochar and inorganic fertilizer in irrigated rice (Oryza sativa var KRC Baika) cropping systems will increase soil organic carbon storage, N recovery and agronomic efficiency of N use (above world average of 55% and 20 kg grain·kg−1·N respectively) and improved economic returns compared to the sole use of inorganic fertilizer. A two-year (4‒cropping cycles) field trial was, thus, conducted on a Vertisol. The experiments were designed as split–plot with two (0 and 10 t·ha−1) biochar and four (0, 45, 90, 120 kg·ha−1·N) nitrogen application rates. Additionally, the effect of biochar on the chemical properties of the soil was investigated using standard protocols. Biochar application improved the soil organic carbon storage in the topsoil. There were significant interactions between the application of biochar and nitrogen fertilizer on yield parameters. Introducing biochar significantly increased root volume and nutrient (N, P and K) uptake, resulting in increased grain and straw yield. Grain yields under biochar amended plots were higher than sole fertilizer amended plots in 14 out of 16 instances (cropping cycles × N rates). The increase in grain yield was between 12 to 29% across N rates. Biochar amendment also enhanced agronomic N use and apparent N recovery efficiencies in 3 out of the 4 cropping cycles. Gross margin indicated that biochar application under irrigated rice cropping systems is economically feasible in all cropping cycles and N rates. However, the value cost ratio of biochar application was higher than for sole inorganic fertilizer in three out of the four cropping cycles (each cropping cycle has three N rates). The soil organic carbon storage of biochar amended soil increased by 17% under unfertilized condition and by 32% under fertilized condition. To enable the promotion and efficient use of the biochar technology in enhancing productivity and profitability in irrigated rice, extension officers and farmers will need to be trained on how to char the rice husk to reduce emissions prior to upscaling the technology to farmers. [ABSTRACT FROM AUTHOR]

Climate change is estimated to exacerbate existing challenges faced by smallholder farmers in Sub-Sahara Africa. However, limited studies quantify the extent of variation in climate change impact under these systems at the local scale. The Decision Support System for Agro-technological Transfer (DSSAT) was used to quantify variation in climate change impacts on maize yield under current agricultural practices in semi-arid regions of Senegal (Nioro du Rip) and Ghana (Navrongo and Tamale). Multi-benchmark climate models (Mid-Century, 2040–2069 for two Representative Concentration Pathways, RCP4.5 and RCP8.5), and multiple soil and management information from agronomic surveys were used as input for DSSAT. The average impact of climate scenarios on grain yield among farms ranged between −9% and −39% across sites. Substantial variation in climate response exists across farms in the same farming zone with relative standard deviations from 8% to 117% at Nioro du Rip, 13% to 64% in Navrongo and 9% to 37% in Tamale across climate models. Variations in fertilizer application, planting dates and soil types explained the variation in the impact among farms. This study provides insight into the complexities of the impact of climate scenarios on maize yield and the need for better representation of heterogeneous farming systems for optimized outcomes in adaptation and resilience planning in smallholder systems. [ABSTRACT FROM AUTHOR]

Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi‐arid Rwanda, hot subhumid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from 2‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (a) benefited less from an increase in atmospheric [CO2]; (b) was less affected by higher temperature or decreasing rainfall; and (c) was more affected by increased rainfall because N leaching was more critical. The model intercomparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low‐input systems. Climate change and N input interactions have strong implications for the design of robust adaptation approaches across SSA, because the impact of climate change in low input systems will be modified if farmers intensify maize production with balanced nutrient management. [ABSTRACT FROM AUTHOR]

The interactive effect of biochar, cattle manure and nitrogen (N) fertilizer on the dynamics of carbon (C) mineralization and stabilization was investigated in a sandy soil amended with three sole biochar (0, 20 or 40 t ha−1) or manure (0, 13 or 26 t ha−1) and four combined biochar-manure levels (20 or 40 t ha−1 biochar plus 13 or 26 t ha−1 manure) with or without N fertilizer (0 or 90 kg ha−1) and CO2-C evolution measured over 54-d incubation period. Biochar application, solely or combined with manure resulted in lower applied C mineralized (ACM), indicating C sequestration in the soils. Negative attributable effect (AE) of co-application of biochar and manure on C mineralization was observed relative to the sole treatments. Both ACM and AE were negatively correlated with C/N ratio and mineral N content of the soil-mixtures (r ≥ – 0.573; p ≤ 0.01), indicating microbial N limitation. The double first-order exponential model described CO2-C efflux very well and indicated that ≥94% of C applied was apportioned to stable C pools with slower mineralization rate constant and longer half-life. Cumulative C mineralized and modeled C pools were positively correlated with each other (r ≥ 0.853; p ≤ 0.001) and with readily oxidizable C of soil-amendment mixtures (r ≥ 0.861; p ≤ 0.001). The results suggested that co-application of biochar and manure can promote initial rapid mineralization to release plant nutrients but sequester larger amounts of applied C in refractive C pool, resulting in larger C sequestration in sandy soils. [ABSTRACT FROM AUTHOR]

Smallholder vegetable farmers involved in agricultural production are confronted with numerous challenges which can adversely affect performance. Farmers would prefer to adopt the most profitable vegetable production systems. A cost-benefit analysis of integrated crop management (ICM) and conventional method (CM) systems for vegetable production was conducted. Primary data were solicited from 120 vegetable farmers using questionnaires. Descriptive statistics were used to describe levels of awareness and extent to which farmers understood use of the ICM system. A cash flow projection was done on a 0.4 ha size of land for 5 years. Net present value (NPV) and cost-benefit ratio (CBR) analyses were performed for farmers operating under the ICM and CM production systems. The NPV analysis indicated production of vegetables under both systems was viable. The incremental NPV for cabbage (Brassica oleracea var. capitata L.) and onion (Allium cepa L.) production, and the whole farm enterprise were all positive, indicating the ICM system was more financially viable than the CM system. The NPV increase was GHS 2563.58 (GHS is Ghanaian currency, 1$US = 3.5 GHS in January 2015 when data were collected) for cabbage and GHS 3949.43 for onion, and of the whole farm enterprise, i.e., combined cabbage and onion production, was GHS 6162.75. The CBR analysis indicated that vegetable production under the two systems was viable, confirming results of the NPV analyses. The CBR for cabbage production was 1.58 for the CM and 2.08 for the ICM systems; the CBR for onion production was 2.69 for the CM and 4.36 for the ICM systems. The CBR for whole farm enterprise was 2.42 for the CM and 3.93 for the ICM systems. Sensitivity analyses, under the assumption of a 5% reduction in yield and a 10% cost over-run, indicated positive NPVs for both production systems for cabbage and onion production, and the whole farm enterprise. The NPVs from use of the ICM system were higher than under the CM system. Overall, vegetable production is profitable under both the ICM and CM systems, and awareness is a factor influencing practice of the ICM system. [ABSTRACT FROM AUTHOR]

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there aremixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate. [ABSTRACT FROM AUTHOR]