Dataverse World Agroforestry (ICRAF)
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Replication Data for: Comprehensive Nutrient Analysis in Agricultural Organic Amendments Through Non-Destructive Assays Using Machine Learning
No full textPortable X-ray fluorescence (pXRF) and Diffuse Reflectance Fourier Transformed Mid-Infrared (DRIFT-MIR) spectroscopy are rapid and cost-effective analytical tools for material characterization. We developed machine learning methods to rapidly quantify the concentrations of macro- and micronutrient elements present in the samples and propose a novel system for the quality assessment of organic amendments. Two types of machine learning methods, forest regression and extreme gradient boosting, were used with data from both pXRF and DRIFT-MIR spectroscopy. Cross-validation trials were run to evaluate generalizability of models produced on each instrument. Both methods demonstrated similar broad capabilities in estimating nutrients using machine learning, with pXRF being suitable for nutrients and contaminants. The results make portable spectrometry in combination with machine learning a scalable solution to provide comprehensive nutrient analysis for organic amendments
Survey on diseases and pests of Uapaca kirkiana and Sclerocarya birrea in Field genebanks in Mangochi, Machinga and Zomba Districts, Malawi, 2016.
No full textPests and disease
Growth, flowering and fruiting of Dacryodes edulis in Mbalmayo field site, Cameroon 2002-2012
No full textGrowth evaluatio
Interactive Suitable Tree Species Selection and Management Tool for East Africa- Ethiopia
No full text1. The tool aims at promoting tree diversity on farm and in landscapes, including useful exotic tree species that the existing vegetation maps do not capture. The tool currently consists of 209 (147 native and 62 exotic) tree species in Ethiopia, disaggregated according to agro-ecological zone suitability. The database enables the user to easily access information either based on tree species, their agro-ecological zone suitability, products, environmental services, origin (native or exotic) and niche. The tool also provides specific details on the trees’ biophysical growth conditions and management requirements as well as links to other agroforestry databases.
2. The tool contains rich information from knowledge-intensive and detailed tree diversity studies: The tool is a composite of different studies and surveys done by working with different stakeholders such as researchers, farmers, extension workers and local partner organizations. These include:
o Tree diversity studies- shows the current tree diversity trends
o Local knowledge studies- captures tree species according to niche locations, most important tree and preferred tree niches. Historical timelines captures tree species that have been lost or are close to extinction, as well as reasons for these trends.
o Baseline studies- captures patterns of tree adoption on farms
o Seed and Seedling System surveys- captures what tree species farmers are planting currently, including the most popular tree species, which implies future trends
o Land Degradation Surveillance Framework: presents biophysical assessment of tree distribution, including tree density
o Literature review- such as the Useful trees and shrubs for Ethiopia- was used to provide additional information such as: biophysical growth conditions, management practices etc and in addition to triangulate information already captured through the other approaches
3. Tracking tree species’ trends: The tools provide an insight into the past, present and future tree species trends on landscapes. Source of information for each tree species, which is guided by the studies named in 2 above is provided (by an asterisk). Double asterisk signifies trees that are deemed most important by farmers in a given area.
4. Scalability: Information provided in the tool can be easily used to select suitable tree species for scaling up and scaling out agroforestry interventions to similar agro-ecologies.
5. Further it is possible to update information on the tool as more tree species are encountered.
Science with grass-root impacts: The tool is interactive and targets a wider audience for promoting ‘Research in Development’ agenda: The tool is easy to use and targets not only researchers but also local extension workers, who are key in scaling up and out agroforestry in interventions. It provides local names of tree species that can easily guide the users at the local level to identify the tree species. We hope to explore ways of packaging the information in forms that can be readily available to local partners like CDs etc
Replication Data for: Mbosso C Degrande A Villamor G van Damme P Tchoundjeu Z Tsafack S 2015 Factors affecting the adoption of agricultural innovation: the case of a Ricinodendron heudelotii kernel extraction machine in southern Cameroo
No full textAgroforestry is now accepted as a sustainable way of improving existing cropping systems. As with other agricultural innovations, the adoption of agroforestry practices depends on farmers’ perceptions of the benefits that would arise from the use of these practices. Ricinodendron heudelotii (Baill. Pierre ex Pax.) or njansang (in Bassa local language) is a tropical tree, the kernels of which are in high demand in Cameroon as a thickening ingredient. Njansang is suitable for integration in agroforestry systems in the area, but its expansion is constrained by difficulties in
kernel extraction, which has been exclusively manual so far. This paper investigates the factors that determine producers’ attitudes towards the introduction and use of
a kernel extraction machine. Among the issues investigated were characterization of users, comparison of mechanical and manual extraction, users’ appreciation of the machine and willingness to continue to use the machine. Using a structured questionnaire, 81 njansang producers from three categories were randomly selected from five villages in southern Cameroon. We further investigate howattributes of an innovation influence the adoption of the machine. Results from a principal component analysis and logistic regression suggest that the age and education of producers, annual income from njansang, the number of njansang trees exploited and the purchase price of the machine are important variables in determining its adoption. The use of the machine allows producers to spend less time on njansang kernel extraction, thereby increasing returns in labour and offering opportunities to increase the number of trees a household can exploit
Meteorological data for the study site
No full textMeteorological data (rainfall and temperature) useful in relating growth and productivity to influence of weather variabilit
Food Trees Project Data Collection Tools: Nutrition and Consumption
No full textExcel Form used to author the survey in ODK for the Food Trees Project for the Nutrition and Consumption dat
Baseline information data for the value Chain Innovation Platform Project (VIP4FS): Study undertaken Solwezi district Zambia
No full textThe study aimed at providing useful information for understanding initial status of households in Solwezi District Zambia. The assessment reviewed farmers basic characteristics, farmer sources of income, land ownership, asset ownership and agricultural production of soya beans, Solwezi beans and Village chicken. The three value chains of interest were pre-selected based on agreed upon criteria combined by the project team after extensive consultation with community understandings and preferences
