Groundnut Cake — 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
Groundnut Cake — Export Quantity is currently reported for 104 countries. The highest value is 18,018 t in Nicaragua; the lowest is 0 t in China, Macao SAR.
The median across all reporting countries is 0 t, and the mean is 859.78 t.
Over the past decade 7 countries rose and 22 fell. The largest increase was in Bulgaria (up 14,700.0%), and the largest decrease in Burkina Faso (down 100.0%).
Groundnut Cake — Export Quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Nicaragua | 18,018 t | 2013 | up 119.3% | volatile |
| 2 | Senegal | 17,949 t | 2013 | down 48.2% | volatile |
| 2 | Viet Nam | 343 t | 2013 | down 40.0% | volatile |
| 3 | Argentina | 13,666 t | 2013 | down 31.8% | volatile |
| 3 | Melanesia | 254 t | 2013 | — | volatile |
| 4 | India | 8,551 t | 2013 | down 94.0% | volatile |
| 5 | Belgium-Luxembourg | 7,670 t | 1999 | up 704.0% | volatile |
| 6 | Malaysia | 7,453 t | 2013 | — | volatile |
| 6 | Iran (Islamic Republic of) | 0 t | 2013 | — | volatile |
| 6 | Venezuela (Bolivarian Republic of) | 0 t | 2013 | — | volatile |
| 6 | United Republic of Tanzania | 0 t | 2013 | — | volatile |
| 7 | Netherlands (Kingdom of the) | 6,446 t | 2013 | up 71.5% | volatile |
| 8 | Myanmar | 3,000 t | 2013 | down 16.7% | volatile |
| 9 | Pakistan | 1,640 t | 2013 | up 1,507.8% | volatile |
| 10 | Belgium | 1,367 t | 2013 | down 67.1% | volatile |
| 11 | China, mainland | 854 t | 2013 | down 86.8% | volatile |
| 12 | Indonesia | 658 t | 2013 | up 135.0% | volatile |
| 13 | Saudi Arabia | 362 t | 2013 | up 4,425.0% | volatile |
| 14 | Bulgaria | 296 t | 2013 | up 14,700.0% | volatile |
| 15 | Solomon Islands | 254 t | 2013 | — | volatile |
| 16 | Norway | 200 t | 2013 | — | volatile |
| 17 | France | 70 t | 2013 | down 97.5% | volatile |
| 18 | South Africa | 66 t | 2013 | — | volatile |
| 19 | Ethiopia | 51 t | 2013 | — | volatile |
| 20 | Nigeria | 49 t | 2013 | down 45.6% | volatile |
| 21 | Sudan (former) | 30 t | 2011 | down 99.7% | volatile |
| 22 | Mozambique | 28 t | 2013 | — | volatile |
| 23 | Chad | 21 t | 2013 | — | volatile |
| 24 | Egypt | 19 t | 2013 | — | volatile |
| 25 | Jamaica | 17 t | 2013 | — | volatile |
| 26 | Caribbean | 17 t | 2013 | — | volatile |
| 26 | Sri Lanka | 16 t | 2013 | — | volatile |
| 26 | Nepal | 16 t | 2013 | down 95.6% | volatile |
| 26 | Thailand | 16 t | 2013 | — | volatile |
| 29 | Cameroon | 10 t | 2013 | — | volatile |
| 30 | Zimbabwe | 5 t | 2013 | — | volatile |
| 31 | United Kingdom of Great Britain and Northern Ireland | 3 t | 2013 | — | volatile |
| 32 | Canada | 1 t | 2013 | — | volatile |
| 32 | Serbia | 1 t | 2013 | — | volatile |
| 34 | Angola | 0 t | 2013 | — | volatile |
| 34 | Albania | 0 t | 2013 | — | volatile |
| 34 | United Arab Emirates | 0 t | 2013 | — | volatile |
| 34 | Australia | 0 t | 2013 | — | volatile |
| 34 | Austria | 0 t | 2013 | — | volatile |
| 34 | Burkina Faso | 0 t | 2013 | down 100.0% | volatile |
| 34 | Bangladesh | 0 t | 2013 | — | volatile |
| 34 | Brazil | 0 t | 2013 | — | volatile |
| 34 | Botswana | 0 t | 2013 | down 100.0% | volatile |
| 34 | Central African Republic | 0 t | 2013 | — | volatile |
| 34 | Switzerland | 0 t | 2013 | — | volatile |
| 34 | Chile | 0 t | 2013 | — | volatile |
| 34 | Congo | 0 t | 2013 | — | volatile |
| 34 | Costa Rica | 0 t | 2013 | — | volatile |
| 34 | Czechia | 0 t | 2013 | — | volatile |
| 34 | Germany | 0 t | 2013 | down 100.0% | volatile |
| 34 | Denmark | 0 t | 2013 | — | volatile |
| 34 | Dominican Republic | 0 t | 2013 | — | volatile |
| 34 | Algeria | 0 t | 2013 | — | volatile |
| 34 | Spain | 0 t | 2013 | — | volatile |
| 34 | Georgia | 0 t | 2013 | — | volatile |
| 34 | Ghana | 0 t | 2013 | down 100.0% | volatile |
| 34 | Gambia | 0 t | 2013 | down 100.0% | volatile |
| 34 | Guinea-Bissau | 0 t | 2013 | — | volatile |
| 34 | Greece | 0 t | 2013 | — | volatile |
| 34 | Guatemala | 0 t | 2013 | — | volatile |
| 34 | Honduras | 0 t | 2013 | — | volatile |
| 34 | Hungary | 0 t | 2013 | — | volatile |
| 34 | Ireland | 0 t | 2013 | — | volatile |
| 34 | Italy | 0 t | 2013 | — | volatile |
| 34 | Jordan | 0 t | 2013 | — | volatile |
| 34 | Kenya | 0 t | 2013 | — | volatile |
| 34 | Lebanon | 0 t | 2013 | — | volatile |
| 34 | Lithuania | 0 t | 2013 | — | volatile |
| 34 | Morocco | 0 t | 2013 | — | volatile |
| 34 | Madagascar | 0 t | 2013 | down 100.0% | volatile |
| 34 | Mexico | 0 t | 2013 | — | volatile |
| 34 | Mali | 0 t | 2013 | down 100.0% | volatile |
| 34 | Malawi | 0 t | 2013 | — | volatile |
| 34 | Namibia | 0 t | 2013 | — | volatile |
| 34 | Niger | 0 t | 2013 | down 100.0% | volatile |
| 34 | Peru | 0 t | 2013 | — | volatile |
| 34 | Philippines | 0 t | 2013 | — | volatile |
| 34 | Poland | 0 t | 2013 | — | volatile |
| 34 | Portugal | 0 t | 2013 | — | volatile |
| 34 | Paraguay | 0 t | 2013 | — | volatile |
| 34 | Romania | 0 t | 2013 | — | volatile |
| 34 | Rwanda | 0 t | 2013 | — | volatile |
| 34 | El Salvador | 0 t | 2013 | — | volatile |
| 34 | Sweden | 0 t | 2013 | — | volatile |
| 34 | Eswatini | 0 t | 2013 | down 100.0% | volatile |
| 34 | Togo | 0 t | 2013 | down 100.0% | volatile |
| 34 | Trinidad and Tobago | 0 t | 2013 | — | volatile |
| 34 | Uganda | 0 t | 2013 | — | volatile |
| 34 | Ukraine | 0 t | 2013 | — | volatile |
| 34 | Uruguay | 0 t | 2013 | — | volatile |
| 34 | Zambia | 0 t | 2013 | — | volatile |
| 34 | Czechoslovakia | 0 t | 1992 | — | volatile |
| 34 | China, Hong Kong SAR | 0 t | 2013 | — | volatile |
| 34 | Republic of Korea | 0 t | 2013 | — | volatile |
| 34 | Australia and New Zealand | 0 t | 2013 | — | volatile |
| 34 | C�te d'Ivoire | 0 t | 2013 | — | volatile |
| 34 | Ethiopia PDR | 0 t | 1992 | down 100.0% | volatile |
| 34 | T�rkiye | 0 t | 2013 | — | volatile |
| 34 | China, Macao SAR | 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 94,621 t
- Asia 22,909 t
- Low Income Food Deficit Countries 51,320 t
- Americas 40,149 t
- Net Food Importing Developing Countries 27,739 t
- Land Locked Developing Countries 93 t
- Least developed countries 26,047 t
- Middle Africa 31 t
- Africa 22,926 t
- Central America 18,018 t
- Western Africa 17,998 t
- South America 13,666 t
- South-Eastern Asia 11,470 t
- Southern Asia 10,223 t
- Northern America 8,448 t
- United States of America 8,447 t
- Europe 8,383 t
- European Union (27) 8,179 t
- Western Europe 7,883 t
- Northern Africa 4,747 t
- Eastern Asia 854 t
- Western Asia 362 t
- Eastern Europe 296 t
- Small Island Developing States 271 t
- Oceania 254 t
- Northern Europe 203 t
- Eastern Africa 84 t
- Southern Africa 66 t
- Southern Europe 1 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.