Sisal — Export Quantity by country
Food Balance Sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply...
What the numbers show
Sisal — Export Quantity is currently reported for 76 countries. The highest value is 16,655 t in Kenya; the lowest is 0 t in T�rkiye.
The median across all reporting countries is 0 t, and the mean is 277.66 t.
Over the past decade 1 countries rose and 32 fell. The largest increase was in Philippines (up 4,582.5%), and the largest decrease in Austria (down 100.0%).
Sisal — Export Quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Kenya | 16,655 t | 2013 | down 29.8% | volatile |
| 2 | Philippines | 3,746 t | 2013 | up 4,582.5% | volatile |
| 3 | Belgium-Luxembourg | 685 t | 1999 | down 65.1% | volatile |
| 4 | Morocco | 6 t | 2013 | down 95.1% | volatile |
| 5 | Haiti | 4 t | 2013 | — | volatile |
| 5 | Caribbean | 4 t | 2013 | — | volatile |
| 7 | Nepal | 2 t | 2013 | down 80.0% | volatile |
| 8 | Angola | 0 t | 2013 | — | volatile |
| 8 | United Arab Emirates | 0 t | 2013 | — | volatile |
| 8 | Australia | 0 t | 2013 | — | volatile |
| 8 | Austria | 0 t | 2013 | down 100.0% | volatile |
| 8 | Belgium | 0 t | 2013 | down 100.0% | volatile |
| 8 | Bangladesh | 0 t | 2013 | — | volatile |
| 8 | Bulgaria | 0 t | 2013 | — | volatile |
| 8 | Brazil | 0 t | 2013 | down 100.0% | volatile |
| 8 | Botswana | 0 t | 2013 | — | volatile |
| 8 | Canada | 0 t | 2013 | down 100.0% | volatile |
| 8 | Switzerland | 0 t | 2013 | — | volatile |
| 8 | Chile | 0 t | 2013 | down 100.0% | volatile |
| 8 | Costa Rica | 0 t | 2013 | — | volatile |
| 8 | Czechia | 0 t | 2013 | — | volatile |
| 8 | Germany | 0 t | 2013 | down 100.0% | volatile |
| 8 | Denmark | 0 t | 2013 | — | volatile |
| 8 | Dominican Republic | 0 t | 2013 | — | volatile |
| 8 | Ecuador | 0 t | 2013 | down 100.0% | volatile |
| 8 | Egypt | 0 t | 2013 | down 100.0% | volatile |
| 8 | Spain | 0 t | 2013 | down 100.0% | volatile |
| 8 | France | 0 t | 2013 | down 100.0% | volatile |
| 8 | Greece | 0 t | 2013 | down 100.0% | volatile |
| 8 | Guatemala | 0 t | 2013 | — | volatile |
| 8 | Honduras | 0 t | 2013 | — | volatile |
| 8 | Croatia | 0 t | 2013 | — | volatile |
| 8 | Indonesia | 0 t | 2013 | down 100.0% | volatile |
| 8 | India | 0 t | 2013 | down 100.0% | volatile |
| 8 | Ireland | 0 t | 2013 | — | volatile |
| 8 | Iceland | 0 t | 2013 | — | volatile |
| 8 | Israel | 0 t | 2013 | — | volatile |
| 8 | Italy | 0 t | 2013 | down 100.0% | volatile |
| 8 | Jamaica | 0 t | 2013 | — | volatile |
| 8 | Jordan | 0 t | 2013 | — | volatile |
| 8 | Japan | 0 t | 2013 | — | volatile |
| 8 | Sri Lanka | 0 t | 2013 | — | volatile |
| 8 | Lithuania | 0 t | 2013 | — | volatile |
| 8 | Madagascar | 0 t | 2013 | down 100.0% | volatile |
| 8 | Mexico | 0 t | 2013 | down 100.0% | volatile |
| 8 | Mali | 0 t | 2013 | — | volatile |
| 8 | Mozambique | 0 t | 2013 | down 100.0% | volatile |
| 8 | Malawi | 0 t | 2013 | — | volatile |
| 8 | Malaysia | 0 t | 2013 | — | volatile |
| 8 | Nicaragua | 0 t | 2013 | — | volatile |
| 8 | Norway | 0 t | 2013 | — | volatile |
| 8 | New Zealand | 0 t | 2013 | — | volatile |
| 8 | Pakistan | 0 t | 2013 | — | volatile |
| 8 | Peru | 0 t | 2013 | — | volatile |
| 8 | Poland | 0 t | 2013 | — | volatile |
| 8 | Portugal | 0 t | 2013 | down 100.0% | volatile |
| 8 | Romania | 0 t | 2013 | — | volatile |
| 8 | Saudi Arabia | 0 t | 2013 | down 100.0% | volatile |
| 8 | Senegal | 0 t | 2013 | — | volatile |
| 8 | Slovenia | 0 t | 2013 | — | volatile |
| 8 | Sweden | 0 t | 2013 | down 100.0% | volatile |
| 8 | Thailand | 0 t | 2013 | — | volatile |
| 8 | Tunisia | 0 t | 2013 | — | volatile |
| 8 | Uganda | 0 t | 2013 | — | volatile |
| 8 | China, Hong Kong SAR | 0 t | 2013 | down 100.0% | volatile |
| 8 | Republic of Korea | 0 t | 2013 | down 100.0% | volatile |
| 8 | Venezuela (Bolivarian Republic of) | 0 t | 2013 | down 100.0% | volatile |
| 8 | Australia and New Zealand | 0 t | 2013 | — | volatile |
| 8 | China, mainland | 0 t | 2013 | down 100.0% | volatile |
| 8 | United Republic of Tanzania | 0 t | 2013 | down 100.0% | volatile |
| 8 | China, Taiwan Province of | 0 t | 2013 | down 100.0% | volatile |
| 8 | Netherlands (Kingdom of the) | 0 t | 2013 | down 100.0% | volatile |
| 8 | United Kingdom of Great Britain and Northern Ireland | 0 t | 2013 | down 100.0% | volatile |
| 8 | C�te d'Ivoire | 0 t | 2013 | — | volatile |
| 8 | Ethiopia PDR | 0 t | 1992 | — | volatile |
| 8 | T�rkiye | 0 t | 2013 | — | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 20,413 t
- Net Food Importing Developing Countries 16,667 t
- Africa 16,661 t
- Low Income Food Deficit Countries 16,661 t
- Eastern Africa 16,655 t
- Asia 3,748 t
- South-eastern Asia 3,746 t
- Least Developed Countries 6 t
- Northern Africa 6 t
- Americas 4 t
- Small Island Developing States 4 t
- Southern Asia 2 t
About this data
Food Balance Sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per caput food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content.