This report describes the findings of the country study carried out for the design of IFAD project on Restoration of Landscapes and Livelihoods (ROLL P) in Lesotho. Following an IFAD designed project to develop an integrated approach for designing climate-smart and nutrition-sensitive investments, support was provided to undertake a thorough situation analysis for climate, nutrition and their interlinkages and to identify potential pathways and interventions to achieve both climate action and nutrition outcomes.
This report describes the findings of the country study carried out for the design of IFAD Smallholder Agriculture Cluster Project (SACP) in Zimbabwe. Following an IFAD designed project to develop an integrated approach for designing climate-smart and nutrition-sensitive investments, support was provided to undertake a thorough situation analysis for climate, nutrition and their interlinkages and to identify potential pathways and interventions to achieve both climate action and nutrition outcomes.
Dans le cadre du Projet de développement agropastoral et des filières associées dans le Gouvernorat de Médenine (PRODEFIL) en Tunisie, par exemple, plus de 140 kilomètres de route ont été construits. Il aurait fallu deux jours sur place pour passer en revue ces routes sur toute leur longueur. Google Earth a permis de le faire en quelques heures seulement. D’autres installations ayant fait l’objet d’investissements dans le cadre du projet, tels que des barrages et des serres, sont également visibles par satellite.
This case study presents an analysis undertaken for the IFAD-funded Agropastoral Value Chains Project in the Governorate of Médenine, Tunisia. High-resolution imagery makes it possible to track the development of roads, buildings, irrigation schemes, and other types of investments. Over 140 km of road constructed or rehabilitated by the project are easily detectable on satellite imagery.
Geographic information system (GIS) data is often used to map socio-economic data with a spatial component. This data, which is obtained from multiple open-source databases, complements official statistics and generates additional spatial inputs to statistical and econometric analyses. IFAD uses impact assessments using data from face-to-face interviews in order to determine the impact of their projects on strategic goal and objectives. However, the COVID-19 pandemic meant these interviews could no longer take place.
Accurate and operational indicators of the start of growing season (SOS) are critical for crop modeling, famine early warning, and agricultural management in the developing world. Erroneous SOS estimates–late, or early, relative to actual planting dates–can lead to inaccurate crop production and food-availability forecasts. Adapting rainfed agriculture to climate change requires improved harmonization of planting with the onset of rains, and the rising ubiquity of mobile phones in east Africa enables real-time monitoring of this important agricultural decision.
Climate smart agriculture (CSA) technologies are innovations meant to reduce the risks in agricultural production among smallholder farmers. Among the factors that influence farmer adoption of agricultural technologies are farmers' risk attitudes and household livelihood diversification. This study, focused on determining how farmers' risk attitudes and household livelihood diversification influenced the adoption of CSA technologies in the Nyando basin. The study utilized primary data from 122 households from two administrative regions of Kisumu and Kericho counties in Kenya.
The COVID-19 pandemic and the measures taken by governments on social distancing and mobility restrictions have contributed to boosting the use of digital technology to bridge some of the physical access gaps. An increasing number of services and extension/information activities are delivered through digital tools and applications. E-commerce has also flourished. As a result, the potential of digital technologies has gained prominence in immediate response and recovery strategies and programmes.
The spatial and temporal variability of soil properties (fluid composition, structure, and water content) and hydrogeological properties employed for sustainable precision agriculture can be obtained from geoelectrical resistivity methods. For sustainable precision agricultural practices, site-specific information is paramount, especially during the planting season.
The determination of bunch features that are relevant for bunch weight estimation is an important step in automatic vineyard yield estimation using image analysis. The conversion of 2D image features into mass can be highly dependent on grapevine cultivar, as the bunch morphology varies greatly. This paper aims to explore the relationships between bunch weight and bunch features obtained from image analysis considering a multicultivar approach.