Sustainable development of crop-livestock farms in Africa

Crop-livestock farms across Africa are highly variable due to in agroecological and socioeconomic factors, the latter shaping the demand and supply of livestock products. Crop-livestock farms in Africa in the 20-first century are very different from most mixed farms elsewhere in the world. African crop-livestock farms are smaller in size, have fewer livestock, lower productivity and less dependency on imported feed than farms in most countries of Europe, the Americas and the intensive agricultural systems of Asia. This paper discusses the role African crop-livestock farms have in the broader socio-agricultural economy, and how these are likely to change adapting to pressures brought on by the intensification of food systems. This intensification implies increasing land productivity (more food per hectare), often leading to more livestock heads per farm, producing fertilized feeds in croplands and importing feed supplements from the market. This discussion includes (1) the links between crop yields, soil fertility and crop-livestock integration, (2) the increasing demand for livestock products and the land resources required to meet to this demand, and (3) the opportunities to integrate broader societal goals into the development of crop-livestock farms. There is ample room for development of crop-livestock farms in Africa, and keeping integration as part of the development will help prevent many of the mistakes and environmental problems related to the intensification of livestock production observed elsewhere in the world. This development can integrate biodiversity, climate change adaptation and mitigation to the current goals of increasing productivity and food security. The inclusion of broader goals could help farmers access the level of finance required to implement changes

The content of African diets is adequate to achieve optimal efficacy with fixed-dose artemether-lumefantrine: a review of the evidence

A fixed-dose combination of artemether-lumefantrine (AL, Coartem®) has shown high efficacy, good tolerability and cost-effectiveness in adults and children with uncomplicated malaria caused by Plasmodium falciparum. Lumefantrine bioavailability is enhanced by food, particularly fat

Adverse maternal, fetal, and newborn outcomes among pregnant women with SARS-CoV-2 infection: an individual participant data meta-analysis.

INTRODUCTION Despite a growing body of research on the risks of SARS-CoV-2 infection during pregnancy, there is continued controversy given heterogeneity in the quality and design of published studies. METHODS We screened ongoing studies in our sequential, prospective meta-analysis. We pooled individual participant data to estimate the absolute and relative risk (RR) of adverse outcomes among pregnant women with SARS-CoV-2 infection, compared with confirmed negative pregnancies. We evaluated the risk of bias using a modified Newcastle-Ottawa Scale. RESULTS We screened 137 studies and included 12 studies in 12 countries involving 13 136 pregnant women.Pregnant women with SARS-CoV-2 infection-as compared with uninfected pregnant women-were at significantly increased risk of maternal mortality (10 studies; n=1490; RR 7.68, 95% CI 1.70 to 34.61); admission to intensive care unit (8 studies; n=6660; RR 3.81, 95% CI 2.03 to 7.17); receiving mechanical ventilation (7 studies; n=4887; RR 15.23, 95% CI 4.32 to 53.71); receiving any critical care (7 studies; n=4735; RR 5.48, 95% CI 2.57 to 11.72); and being diagnosed with pneumonia (6 studies; n=4573; RR 23.46, 95% CI 3.03 to 181.39) and thromboembolic disease (8 studies; n=5146; RR 5.50, 95% CI 1.12 to 27.12).Neonates born to women with SARS-CoV-2 infection were more likely to be admitted to a neonatal care unit after birth (7 studies; n=7637; RR 1.86, 95% CI 1.12 to 3.08); be born preterm (7 studies; n=6233; RR 1.71, 95% CI 1.28 to 2.29) or moderately preterm (7 studies; n=6071; RR 2.92, 95% CI 1.88 to 4.54); and to be born low birth weight (12 studies; n=11 930; RR 1.19, 95% CI 1.02 to 1.40). Infection was not linked to stillbirth. Studies were generally at low or moderate risk of bias. CONCLUSIONS This analysis indicates that SARS-CoV-2 infection at any time during pregnancy increases the risk of maternal death, severe maternal morbidities and neonatal morbidity, but not stillbirth or intrauterine growth restriction. As more data become available, we will update these findings per the published protocol

Conifers: Species Diversity and Improvement Status in Kenya

A wide range of exotic conifer species have been successfully introduced in Kenya since 1910 for the purpose of supplying wood, mainly for timber, pulp, and plywood industries. Among the conifers introduced, Cupressus lusitanica and Pinus patula have adapted well to local growing conditions and are now the key species widely planted in commercial plantations. The other conifer species are planted at secondary level or as ornamentals. In order to increase productivity, the key conifer species have been subjected to genetic improvement through selection, breeding, and hybridization. Results of tree improvement work on C. lusitanica and P. patula showed growth and productivity increase from 20 to 25 m3/ha/yr. for C. lusitanica and from 25 to 30 m3/ha/yr. for P. patula. Scaling up conifer plantations using the tree improvement technologies drawn for the two species is one of the strategies for closing the annual wood supply–demand deficit which is currently estimated at 10.3 million m3. It is also one of the strategies for achieving 10% tree cover which is currently at 7.2%. The strategy encompasses the application of principles of tree breeding, improved germplasm, silviculture, pests and disease control. This presentation is a review of the status of conifer species since their introduction in Kenya

Calculation of new enteric methane emission factors for small ruminants in western Kenya highlights the heterogeneity of smallholder production systems

Context: African livestock play a critical role in food security and the wider economy, while accounting for >70% of African agricultural greenhouse gas emissions. Accurate estimates of greenhouse gas emissions from livestock are required for inventory purposes and to assess the efficacy of mitigation measures. While there is an increasing number of studies assessing methane (CH$_{4}$) emissions of cattle, little attention has been paid to small ruminants (SR). Aims: Enteric CH$_{4}$ emissions were assessed from 1345 SR in three counties of western Kenya to develop more accurate emission factors (EF) for enteric CH$_{4}$ from sheep and goats. Methods: Using on-farm animal activity data, feed samples were also analysed to produce estimates of feed digestibility by season and region. The combined data were also used to estimate daily CH$_{4}$ production by season, location and class of animal to produce new EF for annual enteric CH$_{4}$ production of SR. Key results: Mean dry-matter digestibility of the feed basket was in the range of 58–64%, depending on region and season (~10% greater than Tier I estimates). EF were similar for sheep (4.4 vs 5 kg CH$_{4}$/year), but lower for goats (3.7 vs 5 kg CH$_{4}$/year) than those given for SR in developing countries in Intergovernmental Panel on Climate Change (Tier I) estimates. Conclusions: Published estimates of EF for SR range widely across Africa. In smallholder systems in western Kenya, SR appear to be managed differently from cattle, and EF appear to be driven by different management considerations. Implications: The findings highlighted the heterogenous nature of SR enteric emissions in East Africa, but also suggested that emissions from SR are quantitatively less important than other estimates suggest compared with cattle

Quantification of methane emitted by ruminants: A review of methods

The contribution of greenhouse gas (GHG) emissions from ruminant production systems varies between countries and between regions within individual countries. The appropriate quantifcation of GHG emissions, specifcally methane (CH4), has raised questions about the correct reporting of GHG inventories and, perhaps more importantly, how best to mitigate CH4 emissions. This review documents existing methods and methodologies to measure and estimate CH4 emissions from ruminant animals and the manure produced therein over various scales and conditions. Measurements of CH4 have frequently been conducted in research settings using classical methodologies developed for bioenergetic purposes, such as gas exchange techniques (respiration chambers, headboxes). While very precise, these techniques are limited to research settings as they are expensive, labor-intensive, and applicable only to a few animals. Head-stalls, such as the GreenFeed system, have been used to measure expired CH4 for individual animals housed alone or in groups in confnement or grazing. This technique requires frequent animal visitation over the diurnal measurement period and an adequate number of collection days. The tracer gas technique can be used to measure CH4 from individual animals housed outdoors, as there is a need to ensure low background concentrations. Micrometeorological techniques (e.g., openpath lasers) can measure CH4 emissions over larger areas and many animals, but limitations exist, including the need to measure over more extended periods. Measurement of CH4 emissions from manure depends on the type of storage, animal housing, CH4 concentration inside and outside the boundaries of the area of interest, and ventilation rate, which is likely the variable that contributes the greatest to measurement uncertainty. For large-scale areas, aircraft, drones, and satellites have been used in association with the tracer fux method, inverse modeling, imagery, and LiDAR (Light Detection and Ranging), but research is lagging in validating these methods. Bottom-up approaches to estimating CH4 emissions rely on empirical or mechanistic modeling to quantify the contribution of individual sources (enteric and manure). In contrast, top-down approaches estimate the amount of CH4 in the atmosphere using spatial and temporal models to account for transportation from an emitter to an observation point. While these two estimation approaches rarely agree, they help identify knowledge gaps and research requirements in practice