Closing the data gap: A model for national-level food loss and waste data generation in the absence of existing data
In the UN many countries committed themselves to reduce FLW towards 20301. So-called national pathways are developed, written by governments, elaborating on how this will be established. In order to support and validate these efforts, FLW monitoring2 is required on national level. This is a complex...
| Autor principal: | |
|---|---|
| Formato: | Data Paper |
| Lenguaje: | Inglés |
| Publicado: |
CGIAR Initiative on Low-Emission Food Systems
2024
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/139054 |
| _version_ | 1855528218546667520 |
|---|---|
| author | Soethoudt, J.M. |
| author_browse | Soethoudt, J.M. |
| author_facet | Soethoudt, J.M. |
| author_sort | Soethoudt, J.M. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | In the UN many countries committed themselves to reduce FLW towards 20301. So-called national pathways are developed, written by governments, elaborating on how this will be established. In order to support and validate these efforts, FLW monitoring2 is required on national level. This is a complex task for LMIC, since it is difficult to get data from rural and remote areas. In addition, the variety in products, supply chain links (SCLs), climatic conditions (weather, water, soil) increases the workload of any monitoring approach dramatically. |
| format | Data Paper |
| id | CGSpace139054 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | CGIAR Initiative on Low-Emission Food Systems |
| publisherStr | CGIAR Initiative on Low-Emission Food Systems |
| record_format | dspace |
| spelling | CGSpace1390542024-10-18T13:01:22Z Closing the data gap: A model for national-level food loss and waste data generation in the absence of existing data Soethoudt, J.M. food supply waste management data analysis In the UN many countries committed themselves to reduce FLW towards 20301. So-called national pathways are developed, written by governments, elaborating on how this will be established. In order to support and validate these efforts, FLW monitoring2 is required on national level. This is a complex task for LMIC, since it is difficult to get data from rural and remote areas. In addition, the variety in products, supply chain links (SCLs), climatic conditions (weather, water, soil) increases the workload of any monitoring approach dramatically. 2024-01 2024-02-07T19:01:39Z 2024-02-07T19:01:39Z Data Paper https://hdl.handle.net/10568/139054 en Open Access application/pdf CGIAR Initiative on Low-Emission Food Systems Soethoudt, JM. 2024. Closing the Data Gap: A Model for National-Level Food Loss and Waste Data Generation in the absence of Existing Data. |
| spellingShingle | food supply waste management data analysis Soethoudt, J.M. Closing the data gap: A model for national-level food loss and waste data generation in the absence of existing data |
| title | Closing the data gap: A model for national-level food loss and waste data generation in the absence of existing data |
| title_full | Closing the data gap: A model for national-level food loss and waste data generation in the absence of existing data |
| title_fullStr | Closing the data gap: A model for national-level food loss and waste data generation in the absence of existing data |
| title_full_unstemmed | Closing the data gap: A model for national-level food loss and waste data generation in the absence of existing data |
| title_short | Closing the data gap: A model for national-level food loss and waste data generation in the absence of existing data |
| title_sort | closing the data gap a model for national level food loss and waste data generation in the absence of existing data |
| topic | food supply waste management data analysis |
| url | https://hdl.handle.net/10568/139054 |
| work_keys_str_mv | AT soethoudtjm closingthedatagapamodelfornationallevelfoodlossandwastedatagenerationintheabsenceofexistingdata |