scholarly journals Open source geoprocessing tools and meteorological satellite data for crop risk zones monitoring in Sub-Saharan Africa

2016 ◽  
Author(s):  
Tiziana De Filippis ◽  
Leandro Rocchi ◽  
Patrizio Vignaroli ◽  
Maurizio Bacci ◽  
Vieri Tarchiani ◽  
...  
Keyword(s):  
Food Security ◽  
Open Source ◽  
Early Warning Systems ◽  
Sub Saharan Africa ◽  
Precipitation Forecast ◽  
Drought Risk ◽  
Data Set ◽  
Web Based ◽  
Risk Zones ◽  
Sub Saharan

In Sub-Saharan Africa analysis tools and models based on meteorological satellites data have been developed within different national and international cooperation initiatives, with the aim of allowing a better monitoring of the cropping season. In most cases, the software was a stand-alone application and the upgrading, in terms of analysis functions, database and hardware maintenance, was difficult for the National Meteorological Services (NMSs) in charge of agro-hydro-meteorological monitoring. The web-based solution proposed in this work intends to improve and ensure the sustainability of applications to support national Early Warning Systems (EWSs) for food security. The Crop Risk Zones (CRZ) model for Niger and Mali, integrated in a web-based open source framework, has been implemented using PL/pgSQL & PostGIS functions to process different meteorological data sets: a) the rainfall precipitation forecast images from Global Forecast System (GFS) b) the Climate Prediction Center (CPC) Rainfall Estimation (RFE) for Africa c) Multi-Sensor Precipitation Estimate (MPE) images from EUMETSAT Earth Observation Portal d) the MOD16 Global Terrestrial Evapotranspiration Data Set. Restful Web Services upload raster images into the PostgreSQL/PostGIS database. PL/pgSQL functions are used to run the CRZ model to identify installation and phenological phases of the main crops in the Region and to create crop risk zones images. This model is focused on the early identification of risks and the production of information for food security within the time prescribed for decision-making. The challenge and the objective of this work is to set up an open access monitoring system, based on meteorological open data providers, targeting NMSs and any other local decision makers for drought risk reduction and resilience improvement.

scholarly journals Open source geoprocessing tools and meteorological satellite data for crop risk zones monitoring in Sub-Saharan Africa

2016 ◽  
Author(s):  
Tiziana De Filippis ◽  
Leandro Rocchi ◽  
Patrizio Vignaroli ◽  
Maurizio Bacci ◽  
Vieri Tarchiani ◽  
...  
Keyword(s):  
Food Security ◽  
Open Source ◽  
Early Warning Systems ◽  
Sub Saharan Africa ◽  
Precipitation Forecast ◽  
Drought Risk ◽  
Data Set ◽  
Web Based ◽  
Risk Zones ◽  
Sub Saharan

In Sub-Saharan Africa analysis tools and models based on meteorological satellites data have been developed within different national and international cooperation initiatives, with the aim of allowing a better monitoring of the cropping season. In most cases, the software was a stand-alone application and the upgrading, in terms of analysis functions, database and hardware maintenance, was difficult for the National Meteorological Services (NMSs) in charge of agro-hydro-meteorological monitoring. The web-based solution proposed in this work intends to improve and ensure the sustainability of applications to support national Early Warning Systems (EWSs) for food security. The Crop Risk Zones (CRZ) model for Niger and Mali, integrated in a web-based open source framework, has been implemented using PL/pgSQL & PostGIS functions to process different meteorological data sets: a) the rainfall precipitation forecast images from Global Forecast System (GFS) b) the Climate Prediction Center (CPC) Rainfall Estimation (RFE) for Africa c) Multi-Sensor Precipitation Estimate (MPE) images from EUMETSAT Earth Observation Portal d) the MOD16 Global Terrestrial Evapotranspiration Data Set. Restful Web Services upload raster images into the PostgreSQL/PostGIS database. PL/pgSQL functions are used to run the CRZ model to identify installation and phenological phases of the main crops in the Region and to create crop risk zones images. This model is focused on the early identification of risks and the production of information for food security within the time prescribed for decision-making. The challenge and the objective of this work is to set up an open access monitoring system, based on meteorological open data providers, targeting NMSs and any other local decision makers for drought risk reduction and resilience improvement.

scholarly journals Open source geoprocessing tools and meteorological satellite data for crop risk zones monitoring in Sub-Saharan Africa

2016 ◽  
Author(s):  
Tiziana De Filippis ◽  
Leandro Rocchi ◽  
Patrizio Vignaroli ◽  
Maurizio Bacci ◽  
Vieri Tarchiani ◽  
...  
Keyword(s):  
Food Security ◽  
Open Source ◽  
Early Warning Systems ◽  
Sub Saharan Africa ◽  
Precipitation Forecast ◽  
Drought Risk ◽  
Data Set ◽  
Web Based ◽  
Risk Zones ◽  
Sub Saharan

In Sub-Saharan Africa analysis tools and models based on meteorological satellites data have been developed within different national and international cooperation initiatives, with the aim of allowing a better monitoring of the cropping season. In most cases, the software was a stand-alone application and the upgrade, in terms of analysis functions, database and hardware maintenance, was difficult for National Meteorological Services (NMSs) in charge of the agro-hydro-meteorological monitoring. The web based solution proposed in this work intends to improve and ensure the sustainability of applications so to support national Early Warning Systems (EWSs) for food security. The Crop Risk Zones (CRZ) model for Niger and Mali, integrated in a web-based open source framework, has been implemented using PL/pgSQL & PostGIS functions to process different meteorological data set: a) the rainfall precipitation forecast images from Global Forecast System (GFS) b) the Climate Prediction Center (CPC) Rainfall Estimator (RFE) for Africa c) MSG images from EUMETSAT Earth Observation Portal d) the MOD 16 Global Terrestrial Evapotranspiration Data Set. Restful Web Services uploads raster images into the PostGIS spatial database for PostgreSQL and PL/pgSQL functions were employed to run CRZ model to identify for the main crops of the Region, the installation phases, the crops phenological phases and risk production zones images. This model is focused on the early identification of risks and the production of information for food security within the time prescribed for decision-making. The challenge and the objective of this work is to set up an open access monitoring system, based on meteorological open data providers, targeting NMSs and any other local decision makers for drought risk reduction and resilience improvement.

scholarly journals MAIP: A Prediction Platform for Predicting Blood-Stage Malaria Inhibitors

2020 ◽  
Author(s):  
Nicolas Bosc ◽  
Eloy Felix ◽  
Ricardo Arcila ◽  
David Mendez ◽  
Martin Saunders ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Comprehensive Evaluation ◽  
Sub Saharan Africa ◽  
Data Set ◽  
Practical Challenge ◽  
Qsar Models ◽  
Data Points ◽  
Sub Saharan

Abstract Malaria is a disease affecting hundreds of millions of people across the world, mainly in developing countries and especially in Sub-Saharan Africa. It is the cause of hundreds of thousands of deaths each year and there is an ever-present need to identify and develop effective new therapies to tackle the disease and overcome increasing drug resistance. Here, we extend a previous study in which a number of partners collaborated to develop a consensus in silico model that can be used to identify novel molecules that may have antimalarial properties. The performance of machine learning methods generally improves with the number of data points available for training. One practical challenge in building large training sets is that the data is often proprietary and cannot be straightforwardly integrated. Here, this was addressed by sharing QSAR models, each built on a private data set. We describe the development of an open-source software platform for creating such models, a comprehensive evaluation of methods to create a single consensus model and a web platform called MAIP available at https://www.ebi.ac.uk/chembl/maip/. MAIP is freely available for the wider community to make large-scale predictions of potential malaria inhibiting compounds. This project also highlights some of the practical challenges in reproducing published computational methods and the opportunities that open source software can offer to the community.

scholarly journals MAIP: A web service for predicting blood-stage malaria inhibitors

2020 ◽  
Author(s):  
Nicolas Bosc ◽  
Eloy Felix ◽  
Ricardo Arcila ◽  
David Mendez ◽  
Martin Saunders ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Comprehensive Evaluation ◽  
Sub Saharan Africa ◽  
Data Set ◽  
Practical Challenge ◽  
Qsar Models ◽  
Data Points ◽  
Sub Saharan

Abstract Malaria is a disease affecting hundreds of millions of people across the world, mainly in developing countries and especially in Sub-Saharan Africa. It is the cause of hundreds of thousands of deaths each year and there is an ever-present need to identify and develop effective new therapies to tackle the disease and overcome increasing drug resistance. Here, we extend a previous study in which a number of partners collaborated to develop a consensus in silico model that can be used to identify novel molecules that may have antimalarial properties. The performance of machine learning methods generally improves with the number of data points available for training. One practical challenge in building large training sets is that the data are often proprietary and cannot be straightforwardly integrated. Here, this was addressed by sharing QSAR models, each built on a private data set. We describe the development of an open-source software platform for creating such models, a comprehensive evaluation of methods to create a single consensus model and a web platform called MAIP available at https://www.ebi.ac.uk/chembl/maip/. MAIP is freely available for the wider community to make large-scale predictions of potential malaria inhibiting compounds. This project also highlights some of the practical challenges in reproducing published computational methods and the opportunities that open-source software can offer to the community.

scholarly journals MAIP: a web service for predicting blood‐stage malaria inhibitors

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Nicolas Bosc ◽  
Eloy Felix ◽  
Ricardo Arcila ◽  
David Mendez ◽  
Martin R. Saunders ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Comprehensive Evaluation ◽  
Sub Saharan Africa ◽  
Data Set ◽  
Practical Challenge ◽  
Qsar Models ◽  
Data Points ◽  
Sub Saharan

AbstractMalaria is a disease affecting hundreds of millions of people across the world, mainly in developing countries and especially in sub-Saharan Africa. It is the cause of hundreds of thousands of deaths each year and there is an ever-present need to identify and develop effective new therapies to tackle the disease and overcome increasing drug resistance. Here, we extend a previous study in which a number of partners collaborated to develop a consensus in silico model that can be used to identify novel molecules that may have antimalarial properties. The performance of machine learning methods generally improves with the number of data points available for training. One practical challenge in building large training sets is that the data are often proprietary and cannot be straightforwardly integrated. Here, this was addressed by sharing QSAR models, each built on a private data set. We describe the development of an open-source software platform for creating such models, a comprehensive evaluation of methods to create a single consensus model and a web platform called MAIP available at https://www.ebi.ac.uk/chembl/maip/. MAIP is freely available for the wider community to make large-scale predictions of potential malaria inhibiting compounds. This project also highlights some of the practical challenges in reproducing published computational methods and the opportunities that open-source software can offer to the community.

scholarly journals Is High Whitefly Abundance on Cassava in Sub-Saharan Africa Driven by Biological Traits of a Specific, Cryptic Bemisia tabaci Species?

Insects ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 260
Author(s):  
Habibu Mugerwa ◽  
Peter Sseruwagi ◽  
John Colvin ◽  
Susan Seal
Keyword(s):  
Food Security ◽  
Bemisia Tabaci ◽  
Development Time ◽  
Adult Emergence ◽  
Sub Saharan Africa ◽  
Biological Traits ◽  
Population Development ◽  
Species Classification ◽  
First Instar ◽  
Sub Saharan

In East Africa, the prevalent Bemisia tabaci whiteflies on the food security crop cassava are classified as sub-Saharan Africa (SSA) species. Economically damaging cassava whitefly populations were associated with the SSA2 species in the 1990s, but more recently, it has been to SSA1 species. To investigate whether biological traits (number of first instar nymphs, emerged adults, proportion of females in progeny and development time) of the cassava whitefly species are significant drivers of the observed field abundance, our study determined the development of SSA1 sub-group (SG) 1 (5 populations), SG2 (5 populations), SG3 (1 population) and SSA2 (1 population) on cassava and eggplant under laboratory conditions. SSA1-(SG1-SG2) and SSA2 populations’ development traits were similar. Regardless of the host plant, SSA1-SG2 populations had the highest number of first instar nymphs (60.6 ± 3.4) and emerged adults (50.9 ± 3.6), followed by SSA1-SG1 (55.5 ± 3.2 and 44.6 ± 3.3), SSA2 (45.8 ± 5.7 and 32.6 ± 5.1) and the lowest were SSA1-SG3 (34.2 ± 6.1 and 32.0 ± 7.1) populations. SSA1-SG3 population had the shortest egg–adult emergence development time (26.7 days), followed by SSA1-SG1 (29.1 days), SSA1-SG2 (29.6 days) and SSA2 (32.2 days). Regardless of the whitefly population, development time was significantly shorter on eggplant (25.1 ± 0.9 days) than cassava (34.6 ± 1.0 days). These results support that SSA1-(SG1-SG2) and SSA2 B. tabaci can become highly abundant on cassava, with their species classification alone not correlating with observed abundance and prevalence.

scholarly journals National Culture and Africa Revisited: Ethnolinguistic Group Data From 35 African Countries

2019 ◽  
Vol 54 (1) ◽  
pp. 73-91 ◽  
Author(s):  
Bert van Pinxteren
Keyword(s):  
Survey Data ◽  
National Culture ◽  
Cultural Psychology ◽  
Sub Saharan Africa ◽  
African Countries ◽  
Data Set ◽  
Group Data ◽  
Sub Saharan ◽  
National Boundaries ◽  
Ethnolinguistic Group

Africa is a continent of considerable cultural diversity. This diversity does not necessarily run in parallel to the national boundaries that were created in Africa in the colonial period. However, decades of nation building in Africa must have made their mark. Is it possible nowadays to distinguish national cultures in Africa, or are the traditional ethnolinguistic distinctions more important? This article uses an approach developed in cross-cultural psychology to examine these questions. In 2012, Minkov and Hofstede published an article in this journal analyzing World Values Survey data from seven countries in Sub-Saharan Africa at the level of subnational administrative regions. They argued that national culture is also a meaningful concept in this region. This study reexamines the matter. It uses an innovative approach, looking at ethnolinguistic groups instead of at administrative regions and using the much more extensive Afrobarometer survey data set. It finds that although the Minkov/Hofstede study still has merit, the picture is more nuanced in several important ways. There is not one pattern that adequately describes the situation in the whole of Africa.1

scholarly journals Geographic information analysis and web-based geoportals to explore malnutrition in Sub-Saharan Africa: a systematic review of approaches

2014 ◽  
Vol 14 (1) ◽  
Author(s):  
Sabrina Marx ◽  
Revati Phalkey ◽  
Clara B Aranda-Jan ◽  
Jörn Profe ◽  
Rainer Sauerborn ◽  
...  
Keyword(s):  
Systematic Review ◽  
Geographic Information ◽  
Sub Saharan Africa ◽  
Information Analysis ◽  
Web Based ◽  
Sub Saharan

Cassava Processing in Sub-Saharan Africa: the Implications for Expanding Cassava Production

1994 ◽  
Vol 23 (3) ◽  
pp. 197-205 ◽  
Author(s):  
Felix Izu Nweke
Keyword(s):  
Food Security ◽  
Water Supply ◽  
Sub Saharan Africa ◽  
Wide Range ◽  
Intensive Use ◽  
Cassava Production ◽  
Sub Saharan ◽  
Processing Techniques ◽  
Technical Solutions ◽  
Poor Soil

Cassava makes an important contribution to improving food security and rural incomes in sub-Saharan Africa, as it is tolerant of drought and poor soil and its cultivation does not require much labour. However, the fresh roots are bulky and perishable and need to be processed before they can be marketed; processing also removes the cyanogens which make many varieties poisonous in their raw form. Cassava roots are turned into granules, flours, pastes and chips, with a wide range of flavours and appearances for different areas and markets. Many different processing techniques are used, some of which make intensive use of fuelwood while others require a plentiful water supply. These requirements, as well as the need for a good transport and marketing infrastructure, limit the expansion of cassava production in sub-Saharan Africa, but technical solutions are being found.

scholarly journals Climate Smart Agriculture as Final Goal: Use of Improved Cereals Varieties in Cinzana, Mali.

2017 ◽  
Vol 5 (1) ◽  
pp. 50
Author(s):  
Kalifa TRAORE ◽  
Daouda SIDIBE ◽  
Harouna COULIBALY
Keyword(s):  
Food Security ◽  
Water Conservation ◽  
Crop Production ◽  
Heavy Rain ◽  
Sub Saharan Africa ◽  
Improved Varieties ◽  
Farmer Organizations ◽  
Conservation Technology ◽  
Sub Saharan ◽  
Smart Agriculture

Climate variability and change are recognized as the greatest challenge to crop production and food security in sub-Saharan Africa. This work assesses farmers’ perception on the contribution of improved varieties of sorghum and millet in the search for food security in Cinzana rural commune of Mali in the current context of climate change.The methodology was based on focus group surveys with both, the decentralized technical services, administrative and municipal authorities, NGOs, farmer organizations and producers but also farmer exchanges visits on improved varieties tested in farmer’s field.The result shows that climate change is described by the majority of farmers (87%) as decrease in rainfall amount and length of rainy seasons, high increases in temperature and high deforestation and water scarcity. Unpredictability of climate, (80%), drought (70%) and heavy rain (65%) occurrence were identified as major perception of farmers on risks in climate for crop production and soil degradation. After farmers’ study tour, 80% of the participants mentioned a better growth of plants and increase of soil moisture with the use of contour ridges tillage as a water conservation technology. Adapted cycle (55%) and higher yield (37%) of improved varieties were farmer’s main drivers for adoption of improved millet and sorghum varieties.The study revealed that local farmers have substantial knowledge on climate variabilities and risks and also are aware of some adaptation strategies. However, for wide scale adoption of effective strategies, capacity strengthening appeared a prerequisite.

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