Net benefits of smallholder dairy cattle farms in Senegal can be significantly increased through the use of better dairy cattle breeds and improved management practices

Senegal, located in West Africa, is an example of a low-to middle-income country where the govern-ment has prioritized improving livestock production self-sufficiency, with a strong focus on dairy. Among other initiatives, the use of exotic dairy cattle has been promoted, despite no evidence for the potential liveli-hood benefits (or otherwise) to smallholder farmers on adopting the new genetics. The current work fills this evidence gap by performing a farm-level economic study comparing the keeping of different breed and cross-breed types of dairy cattle under different management levels. Data for the study were obtained by monitoring 220 smallholder dairy cattle farms, with a combined cattle population of about 3,000 animals, over an almost 2-yr period. Findings of the study suggest that the most net-beneficial and cost-beneficial dairy cattle enterprise that could be used by the smallholder farmers was to keep crossbred indigenous zebu by exotic Bos taurus animals under management standards that are consid-ered good compared with local standards. This dairy enterprise type was 7.4-fold more net beneficial and had a 1.4-fold more favorable cost-benefit ratio than the traditional system of keeping indigenous zebu animals under poor (low-input) management. Interestingly, the keeping of (near) pure B. taurus dairy cattle resulted in the highest milk yields and thus benefit from milk, but was not the most net beneficial due to the high costs of keeping these animals, particularly in terms of feed. We also found that increasing the managementlevel of any of the breed or cross-breed types under consideration, including the indigenous zebu animals, resulted in an increased net benefit of 2.2-to 2.9-fold. Results of this economic analysis are discussed as part of a broader trade-off analysis, resulting in recommendations to strengthen the Senegal dairy sector. The combined intervention of improved dairy cattle genetics and management is considered a promising intervention to improve livelihoods of the rural poor as well as livestock production self-sufficiency for Senegal; some other system constraints are addressed.Peer reviewe

Coupling early warning services, crowdsourcing, and modelling for improved decision support and wildfire emergency management

The threat of a forest fire disaster increases around the globe as the human footprint continues to encroach on natural areas and climate change effects increase the potential of extreme weather. It is essential that the tools to educate, prepare, monitor, react, and fight natural fire disasters are available to emergency managers and responders and reduce the overall disaster effects. In the context of the I-REACT project, such a big crisis data system is being developed and is based on the integration of information from different sources, automated data processing chains and decision support systems. This paper presents the wildfire monitoring for emergency management system for those involved and affected by wildfire disasters developed for European forest fire disasters

Developing a genetic evaluation system for milk traits in Russian black and white dairy cattle

Mixed linear models have been applied for predicting breeding values of dairy cattle in most of the developed countries since the 1980s. However, the Russian Federation is still using the old contemporary comparison method. The objective of our study was to develop a best linear unbiased prediction (BLUP) for an animal model of breeding values for the Leningrad region. We tested both a first-lactation model (FLM) and a multi-lactation repeatability model (MLM). The data included milk records of 206 114 cows from 49 herds. Estimated heritabilities from FLM were 0.24, 0.20, and 0.20 for milk, protein, and fat yields, respectively, and 0.18, 0.19, and 0.20 from MLM. Repeatabilities were 0.34 for milk yield and 0.31 for both fat and protein yields. Genetic trends were similar for both models (FLM vs MLM): 59 vs 56 kg year(-1) for milk, 1.90 vs 1.84 kg year(-1) for fat, and 1.67 vs 1.62 kg year(-1) for protein yield during 2000-2016. Based on the difference between the genetic trends in FLM and MLM, the applied BLUP method passed the validation method I by Interbull.Peer reviewe

Investigation of reliability of genomic predictions in the admixed Nordic Red dairy cattle

The success of genomic selection (GS) in small breeds which are likely to have admixed structures has been minimal. This is because accuracy of GS depends on the extent of linkage disequilibrium (LD) between markers and quantitative trait loci (QTL) and LD depends on the genetic structure of the population and marker density. In the current study, we evaluate reliability of genomic predictions in young unproven bulls, when interactions between marker effects and breed of origin are accounted for in the Nordic Red dairy cattle (RDC). The population structure of the RDC is admixed. Data consisted of animal breed proportions calculated from the full pedigree, deregressed proofs (DRP) of published estimated breeding values (EBV) for yield traits and genotypic data for 37,595 SNP markers. Direct genomic breeding values (DGV) were estimated using 2 models, one accounting for breed-specific effects and other assuming uniform population. Validation reliabilities were calculated as the squared correlation between DRP and DGV (r2DRP, DGV), corrected by the mean reliability ofDRP. Using the breed-specific model increased the reliability of DGV by 2% and 3% for milk and protein, respectively, when compared to homogeneous population GBLUP model. The exception was for fat, where there was no gain in reliability. Estimated validation reliabilities were low for milk (0.32) and protein (0.32) and slightly higher (0.42) for fat

Early detection and information extraction for weather-induced floods using social media streams

Today we are using an unprecedented wealth of social media platforms to generate and share information regarding a wide class of events, which include extreme meteorological conditions and natural hazards such as floods. This paper proposes an automated set of services that start from the availability of weather forecasts, including both an event detection technique and a selective information retrieval from on-line social media. The envisioned services aim to provide qualitative feedback for meteorological models, detect the occurrence of an emergency event and extract informative content that can be used to complement the situational awareness. We implement such services and evaluate them during a recent weather induced flood. Our approach could be highly beneficial for monitoring agencies and meteorological offices, who act in the early warning phase, and also for authorities and first responders, who manage the emergency response phase

Implementation of BLUP for breeding value estimation in Russian Federation

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Capability model to improve infrastructure asset performance

Infrastructure organizations are operating in an increasingly challenging business environment as a result of globalization, privatization and deregulation. In an external business environment that is constantly changing, extant literature on strategic management advocates the need to focus on factors internal to the organization such as resources and capabilities to sustain their performance. Specifically, they need to develop dynamic capabilities in order to survive and prosper under conditions of change. The aim of this paper is to explore the dynamic capabilities needed in the management of transport infrastructure assets using a multiple case study research strategy. This paper produced a number of findings. First, the empirical evidence showed that the core infrastructure asset management processes are capacity management, options evaluation, procurement & delivery, maintenance management, and asset information management. Second, the study identified five dynamic capabilities namely stakeholder connectivity, cross-functional, relational, technology absorptive and integrated information capability as central to executing the strategic infrastructure asset management processes well. These findings culminate in the development of a capability model to improve the performance of infrastructure assets in an increasingly dynamic business environment