Drivers of maize yield variability at household level in northern Ghana and Malawi

Open Access Journal; Published online: 03 Jul 2023Maize is a staple food, but productivity has stagnated due to limited access to advanced farming methods and knowledge. To promote sustainable agriculture, understanding the factors affecting maize yield at the farm level is crucial. This study used panel data on maize yield and agronomic practices in Northern Ghana and Malawi from 2014 to 2020. Satellite-based environmental variables were extracted at household locations, and Random Forest modeling was used to identify factors influencing maize yield variability. The models performance was sub-par with low R2 values (∼0.1 and ∼0.24 for Northern Ghana and Malawi). Fertilizer and precipitation were the most important factors explaining maize yield variability. Spatial maps showed that Malawi’s maize yield can increase with more fertilizer, but rainfall is essential. In Northern Ghana, relying solely on fertilizer may not be enough to boost maize production

Assessment of land degradation in semiarid Tanzania using multiscale remote sensing datasets to support sustainable development goal 15.3

Open Access Journal; Published online: 30 Apr 2021Monitoring land degradation (LD) to improve the measurement of the sustainable development goal (SDG) 15.3.1 indicator (“proportion of land that is degraded over a total land area”) is key to ensure a more sustainable future. Current frameworks rely on default medium-resolution remote sensing datasets available to assess LD and cannot identify subtle changes at the sub-national scale. This study is the first to adapt local datasets in interplay with high-resolution imagery to monitor the extent of LD in the semiarid Kiteto and Kongwa (KK) districts of Tanzania from 2000–2019. It incorporates freely available datasets such as Landsat time series and customized land cover and uses open-source software and cloud-computing. Further, we compared our results of the LD assessment based on the adopted high-resolution data and methodology (AM) with the default medium-resolution data and methodology (DM) suggested by the United Nations Convention to Combat Desertification. According to AM, 16% of the area in KK districts was degraded during 2000–2015, whereas DM revealed total LD on 70% of the area. Furthermore, based on the AM, overall, 27% of the land was degraded from 2000–2019. To achieve LD neutrality until 2030, spatial planning should focus on hotspot areas and implement sustainable land management practices based on these fine resolution results

Extrapolation suitability index for sustainable vegetable cultivation in Babati district, Tanzania.

Open Access JournalLand suitability assessment matches crop requirements with available resources to promote sustainable production. Scaling out of sustainable agricultural intensification practices to suitable biophysical and socio-economic conditions reduces the risk of failure and increases their adoption rate. This study applies a geospatial framework to identify potentially suitable sites for extrapolating two improved vegetable cultivars grown under integrated management practices (IMP’s) in Babati District of Tanzania. On-farm trial data on the yield and income of two cultivars were used as a reference. Extrapolation was based on the gridded biophysical and socio-economic layers that limit the production of the two improved vegetable cultivars’. The extrapolation suitability index (ESI) showed the areas where cultivation of the two improved vegetable cultivars under IMP’s can be scaled-out with a potentially low risk of failure. We generate maps of the most important limiting factor for each cultivar in every pixel to guide the spatial targeting of appropriate remedial measures. Application of these maps will promote evidence-based scaling out of improved vegetable technologies by the extension and development agencies

Mediation and moderation roles of resilience capacity in the shock–food-security nexus in northern Ghana

Open Access ArticleThis paper examines how resilience capacity mediates or moderates the relationship between weather shocks and household food security based on two waves of farm household survey and satellite-based weather data in northern Ghana and applying econometric models. Results show that resilience capacity moderate or mediates the negative effects of heat stress and drought on food security. However, the mediating role of resilience capacity in the shock-food security nexus is more stable and stronger than its moderating role. A standard deviation (SD) increase in heat stress reduces household food consumption by 0.71 SD, but resilience capacity effectively moderates this effect by approximately 0.61 SD. For drought, household food consumption is reduced by 0.67 SD, but resilience capacity effectively dampens this negative effect by approximately 0.60 SD. The mediation results, on the other hand, indicate that 537% of the total effect of heat stress on household calorie consumption is explained by the indirect effect through resilience capacity. Similarly, resilience capacity mediates about 74% of the total effect of heat stress on household food consumption. These results suggest that strategies that help improve resilience capacity, such as the adoption of sustainable intensification practices, are critical in enhancing food security in northern Ghana

Trends of rainfall onset, cessation, and length of growing season in northern Ghana: comparing the rain gauge, satellite, and farmer's perceptions

Open Access Journal; Published: 13 Dec 2021Rainfall onset and cessation date greatly influence cropping calendar decisions in rain-fed agricultural systems. This paper examined trends of onsets, cessation, and the length of growing season over Northern Ghana using CHIRPS-v2, gauge, and farmers’ perceptions data between 1981 and 2019. Results from CHIRPS-v2 revealed that the three seasonal rainfall indices have substantial latitudinal variability. Significant late and early onsets were observed at the West and East of 1.5◦ W longitude, respectively. Significant late cessations and longer growing periods occurred across Northern Ghana. The ability of farmers’ perceptions and CHIRPS-v2 to capture rainfall onsets are time and location-dependent. A total of 71% of farmers rely on traditional knowledge to forecast rainfall onsets. Adaptation measures applied were not always consistent with the rainfall seasonality. More investment in modern climate information services is required to complement the existing local knowledge of forecasting rainfall seasonalit

Potential impact of groundnut production technology on welfare of smallholder farmers in Ghana

Open Access Journal; Published online: 14 Jan 2022This study was conducted to assess the potential impact of applying a new groundnut planting density on welfare of smallholder farmers in northern Ghana. We used data from on-farm experiments, focus group discussions, and a household survey. We followed three steps in our analysis. First, we conducted cost-benefit analysis in which we showed the economic advantage of the new technology over the farmers’ practice. Second, we predicted adoption rates along timeline using the Adoption and Diffusion Outcome Prediction Tool (ADOPT). Third, using the results of the first and the second steps, we estimated the potential impact of the technology on poverty at household level using a combination of methods such as economic surplus model and econometric model. The cost-benefit analysis shows that increasing plant density increases farmers’ financial returns i.e., the benefit-cost-ratio increases from 1.05 under farmers’ practice to 1.87 under the best plant density option, which is 22 plants/sqm. The adoption prediction analysis shows that the maximum adoption rate for the best practice will be 62% which will take about nine years to reach. At the maximum adoption rate the incidence of extreme poverty will be reduced by about 3.6% if farmers have access to the international groundnut market and by about 2% if they do not have. The intervention will also reduce poverty gap and poverty severity. The results suggest that policy actions which can improve farmers’ access to the international market will enhance farmers’ welfare more than the situation in which farmers have access to domestic markets only. Furthermore, promoting a more integrated groundnut value-chain can broaden the demand base of the produce resulting in higher and sustainable impact of the technology on the welfare of groundnut producers and beyond

Taking technologies to a greater scale

Open Access ChapterThis chapter presents a definition of 'scaling' and outlines the key elements for success based on the experiences gained from Africa RISING research and dissemination in East and Southern Africa (ESA). Three examples are presented: (a) research and development partnerships; (b) community based scaling through seed systems; and (c) outdoor advertising for orange-fleshed sweet potato. It presents experiences and lessons learned from using these approaches to transfer and scale the technologies

Distribution of Pseudocercospora species causing Sigatoka leaf diseases of banana in Uganda and Tanzania

Open Access Article; Published online: 11 Oct 2019Sigatoka leaf diseases are a major constraint to banana production. A survey was conducted in Tanzania and Uganda to assess the distribution of Pseudocercospora species and severity of Sigatoka leaf diseases. Pseudocercospora species were identified using species‐specific primers. Sigatoka‐like leaf diseases were observed in all farms and on all cultivars, but disease severity varied significantly (P < 0.001) between countries, districts/regions within countries, altitudinal ranges and banana cultivars. In all regions except Kilimanjaro, P. fijiensis, the causal agent of black Sigatoka, was the only pathogen associated with Sigatoka disease. Mycosphaerella musae was associated with Sigatoka‐like symptoms in Kilimanjaro region. Black Sigatoka disease was more severe in Uganda, with a mean disease severity index (DSI) of 37.5%, than in Tanzania (DSI = 19.9%). In Uganda, black Sigatoka disease was equally severe in Luwero district (mean DSI = 40.4%) and Mbarara district (mean DSI = 37.9%). In Tanzania, black Sigatoka was most severe in Kagera region (mean DSI = 29.2%) and least in Mbeya region (mean DSI = 11.5%). Pseudocercospora fijiensis, the most devastating sigatoka pathogen, was detected at altitudes of up to 1877 m a.s.l. This range expansion of P. fijiensis, previously confined to altitudes lower than 1350 m a.s.l. in East Africa, is of concern, especially for smallholder banana farmers growing the susceptible East African Highland bananas (EAHB). Among the banana varieties sampled, the EAHB, FHIA hybrids and Mchare were the most susceptible. Here, the loss of resistance in Yangambi KM5, a banana variety previously resistant to P. fijiensis, is reported for the first time

Tracking the magnitude of climate change and variability with remote sensing data to improve targeting of climate smart agricultural technologies

Quantifying the magnitude and significance of climate change variables over space and time in Africa is challenging due to sparse distribution of weather stations and poor quality of existing data. Time series climate data generated from remote sensing platforms could provide plausible alternative for measuring the trends of climate change in data limiting context. This study utilise time series remote sensing data for rainfall, maximum temperature and minimum temperature to investigate the magnitude and significance of spatial-temporal trends over six countries in West Africa. A modified Mann-Kendall test and Theil-Sen's slope are utilised to test the significance and the magnitude of trends respectively for period between 1981 and 2017. June to September rainfall along the Sahel, Sudan and northern Guinea savanna agro-ecological zones revealed a significant increase (0.1 - 3 mm yr -1 ) that peaked in August. Extreme temperatures for period between August and October remained stable while significant positive trend (0.005 - 0.07°C yr -1 ) was observed in rest of months. Areas experiencing significant drying and warming trends are earmarked as priority for targeting appropriate climate smart agricultural technologies. The widespread significant increase of extreme temperatures justifies increased investments in measures to cope with heat stress