High sensitivity on-site early warning system monitoring of pesticides by photo-induced fluorescence.

This paper describes the prototype of an on-site High Sensitivity Early Warning Monitoring System, using Photo-Induced Fluorescence, for pesticide monitoring in natural waters (HSEWPIF). To obtain a high sensitivity, the prototype was designed with four main features. Four UV LEDs are used to excite the photoproducts at different wavelengths and select the most efficient one. Two UV LEDs are used simultaneously at each wavelength to increase the excitation power and then the fluorescence emission of the photoproducts. High-pass filters are used to avoid the saturation of the spectrophotometer and to increase the signal-to-noise ratio. The HSEWPIF prototype also employs UV absorption to detect any occasional increase of suspended and dissolved organic matter, which could disrupt the fluorescence measurement. The conception of this new experimental set-up is explained and described, then analytical applications are carried out online for the determination of fipronil and monolinuron. We obtained a linear calibration range from 0 to 3 µg mL-1 with limits of detection of 1.24 ng mL-1 for fipronil and 0.32 ng mL-1 for monolinuron. A mean recovery of 99.2% for fipronil and 100.9% for monolinuron show that the method is accurate, moreover a standard deviation of 1.96% for fipronil and 2.49% for monolinuron show that the method is repeatable. Compared to other methods for the determination of pesticides by photo-induced fluorescence, the HSEWPIF prototype has good sensitivity with better limits of detection, and good analytical performances. These results show that HSEWPIF can be used for monitoring pesticide in natural waters to protect industrial facilities against accidental contamination.

Higher sowing density of pearl millet increases productivity and water use efficiency in high evaporative demand seasons.

Introduction: Pearlmillet is themain subsistence crop for smallholder farmers systemswhere it is grown at low plant density. Intensifying pearl millet cultivation could boost productivity although it may have trade-offs. Increasing planting density would indeed increase the leaf area and the related water budget, whereas a denser canopy could create a more favorable canopymicroclimate to the benefit of the water use efficiency (WUE) of the crops. The first aim of this work was to test the yield response of popular pearlmillet varieties to an increased density and to assess possible genotypic variation in this response. The second aim was to measure the water use and the WUE of the crop in different densities. Method: To this end we designed several field and lysimetric experiments To increase the robustness of the results, these trials were carried out in India and Senegal, using two independent sets of genotypes adapted to both sites. Results: In the field, the higher sowing density significantly increased yield in all genotypes when trials were carried out in high evaporative demand conditions. There was no genotype x density interaction in these trials, suggesting no genotypic variation in the response to density increase. The high-density treatment also decreased the vapor pressure deficit (VPD) in the canopies, both in the field and in the lysimeter experiments. In the lysimeter trials, although the higher density treatment increased water use, the resulting increase in biomass was proportionally higher, hence increasingWUE of the crops in all genotypes under high density. The increase in yield under high density was closely related to the increase in WUE, although this link was more tight in the high- than in the low evaporative demand seasons. This confirmed a strong environmental effect on the response to density of all genotypes tested. Discussion: Although they did not open a scope for breeding density tolerant cultivars, these results highlight the possibility to improve pearl millet yield by increasing the density, targeting specifically areas facing high evaporative demand.

Identification of drivers of Rift Valley fever after the 2013-14 outbreak in Senegal using serological data in small ruminants.

Rift Valley fever (RVF) is a mosquito-borne disease mostly affecting wild and domestic ruminants. It is widespread in Africa, with spillovers in the Arab Peninsula and the southwestern Indian Ocean. Although RVF has been circulating in West Africa for more than 30 years, its epidemiology is still not clearly understood. In 2013, an RVF outbreak hit Senegal in new areas that weren't ever affected before. To assess the extent of the spread of RVF virus, a national serological survey was implemented in young small ruminants (6-18 months old), between November 2014 and January 2015 (after the rainy season) in 139 villages. Additionally, the drivers of this spread were identified. For this purpose, we used a beta-binomial ([Formula: see text]) logistic regression model. An Integrated Nested Laplace Approximation (INLA) approach was used to fit the spatial model. Lower cumulative rainfall, and higher accessibility were both associated with a higher RVFV seroprevalence. The spatial patterns of fitted RVFV seroprevalence pointed densely populated areas of western Senegal as being at higher risk of RVFV infection in small ruminants than rural or southeastern areas. Thus, because slaughtering infected animals and processing their fresh meat is an important RVFV transmission route for humans, more human populations might have been exposed to RVFV during the 2013-2014 outbreak than in previous outbreaks in Senegal.

Combining viral genetic and animal mobility network data to unravel peste des petits ruminants transmission dynamics in West Africa.

Peste des petits ruminants (PPR) is a deadly viral disease that mainly affects small domestic ruminants. This disease threaten global food security and rural economy but its control is complicated notably because of extensive, poorly monitored animal movements in infected regions. Here we combined the largest PPR virus genetic and animal mobility network data ever collected in a single region to improve our understanding of PPR endemic transmission dynamics in West African countries. Phylogenetic analyses identified the presence of multiple PPRV genetic clades that may be considered as part of different transmission networks evolving in parallel in West Africa. A strong correlation was found between virus genetic distance and network-related distances. Viruses sampled within the same mobility communities are significantly more likely to belong to the same genetic clade. These results provide evidence for the importance of animal mobility in PPR transmission in the region. Some nodes of the network were associated with PPRV sequences belonging to different clades, representing potential "hotspots" for PPR circulation. Our results suggest that combining genetic and mobility network data could help identifying sites that are key for virus entrance and spread in specific areas. Such information could enhance our capacity to develop locally adapted control and surveillance strategies, using among other risk factors, information on animal mobility.

Assessing the Risk of Occurrence of Bluetongue in Senegal.

Bluetongue is a non-contagious viral disease affecting small ruminants and cattle that can cause severe economic losses in the livestock sector. The virus is transmitted by certain species of the genus Culicoides and consequently, understanding their distribution is essential to enable the identification of high-risk transmission areas. In this work we use bioclimatic and environmental variables to predict vector abundance, and estimate spatial variations in the basic reproductive ratio  R0. The resulting estimates were combined with livestock mobility and serological data to assess the risk of Bluetongue outbreaks in Senegal. The results show an increasing abundance of C. imicola, C. oxystoma, C. enderleini, and C. miombo from north to south. R0 < 1 for most areas of Senegal, whilst southern (Casamance) and southeastern (Kedougou and part of Tambacounda) agro-pastoral areas have the highest risk of outbreak (R0 = 2.7 and 2.9, respectively). The next higher risk areas are in the Senegal River Valley (R0 = 1.07), and the Atlantic coast zones. Seroprevalence rates, shown by cELISA, weren't positively correlated with outbreak probability. Future works should include follow-up studies of competent vector abundancies and serological surveys based on the results of the risk analysis conducted here to optimize the national epidemiological surveillance system.

Mapping livestock movements in Sahelian Africa.

In the dominant livestock systems of Sahelian countries herds have to move across territories. Their mobility is often a source of conflict with farmers in the areas crossed, and helps spread diseases such as Rift Valley Fever. Knowledge of the routes followed by herds is therefore core to guiding the implementation of preventive and control measures for transboundary animal diseases, land use planning and conflict management. However, the lack of quantitative data on livestock movements, together with the high temporal and spatial variability of herd movements, has so far hampered the production of fine resolution maps of animal movements. This paper proposes a general framework for mapping potential paths for livestock movements and identifying areas of high animal passage potential for those movements. The method consists in combining the information contained in livestock mobility networks with landscape connectivity, based on different mobility conductance layers. We illustrate our approach with a livestock mobility network in Senegal and Mauritania in the 2014 dry and wet seasons.