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Resultados de la búsqueda

Mostrando ítems 1 a 9 de 2810.
  1. Library Resource
    Enero, 2023
    Global

    play a key role in building smallholders’ resilience. However, the impact of PSNP on on-
    farm agrobiodiversity is not yet well investigated. In this paper, we develop an analytical
    framework that links PSNP participation to on-farm agrobiodiversity. Both diverse farm-
    ing systems and PSNP require labour inputs while providing income stabilization, which
    might result in a negative relationship between the two. Conversely, higher income from
    PSNP might allow farmers to increase their long-term on-farm investments, as opposed to

  2. Library Resource
    Enero, 2023
    Global

    Smallholder irrigation is emerging as a development priority in Sub-Saharan Africa. Based on a survey of 1554 smallholders from nine countries, this paper compares rainfed farming with gravity-flow, manual-lift and motor-pump irrigation. Motor-pump-irrigation farmers reported the highest net value added per acre and per family worker, with gravity-flow and manual-irrigation farmers earning marginally more than rainfed-only farmers.

  3. Library Resource
    Enero, 2023
    Níger

    Land-use-change-induced increases in shallow groundwater levels across parts of the Sahel in recent years have coincided with expanded use of groundwater for irrigation. This study was conducted to assess the potential linkages and livelihood implications based on a field survey of nine villages building on previous hydrological studies. The results show that irrigators lack effective means of production and mostly rely on manual methods. Borehole usage is more profitable and reliable than shallower wells.

  4. Library Resource
    Enero, 2023
    Global

    This study uses maize as the test crop. Maize is the key focus of most studies on crop response to micronutrients in SSA with a limited number of studies on wheat, rice, cowpea, sorghum, and soybean responses. Maize, constituting 45% of the cereal production in SSA in 2014, is the staple food crop (accounting for over 40% of the calories consumed in some countries such as Malawi and Zambia (http://www.fao.org/faostat/en/#data)) and the main component of food aid interventions in SSA (Leonardo et al. 2015).

  5. Library Resource
    Enero, 2023
    Global

    The objective of this note is to map the global finance landscape that is relevant to the CGIAR Research Initiative on Low-Emission Food Systems (the Project). The note is part of the initial research phase of the project’s work stream on financial instruments as a tool for scaling of measures for achieving lower emissions in food systems (WP4). The objective of this research phase is to develop a typology of most adopted financial instruments for low-emission investments.

  6. Library Resource
    Enero, 2023
    India

    Until recent decades, labour-intensive subsistence farming was a way of life and livelihood in the hill communities of Uttarakhand, India. However, the nature of agriculture falls far short of the expectations of the main labour force, the rural youth, leading to their mass migration to non-agricultural occupations. The large-scale youth migration has left many hill farming landscapes depopulated and farmlands abandoned. As youth have special stakes in food systems, they must be included in the sustainable transformation of food systems.

  7. Library Resource
    Enero, 2023
    Benin

    Food insecurity and child malnutrition remain persistent problems in sub-Saharan Africa. Rice is a staple food for more than half of the world’s population. However, white rice is poor in micronutrients and records higher glycemic values compared to parboiled rice. An improved parboiling system called “Grain quality enhancer, Energy-efficient and durable Material” (GEM in short) allows the processing of quality rice with better physical and nutritional properties compared to traditional systems.

  8. Library Resource
    Enero, 2023
    Global

    The potential for operations research with farmer supplied data coupled with machine learning to improve crop management is explored through a series of case studies from developing countries. The information provided by the farmers ranged from solely yield to a description of the management of the crop and some details of the growth environment. The climate or weather conditions of the georeferenced farms were estimated from publicly available data bases. Two principle analytical approaches were used.

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