Palmkernel 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
Palmkernel Cake — Export Quantity is currently reported for 68 countries. The highest value is 3.57 million t in Indonesia; the lowest is 0 t in Czechia.
The median across all reporting countries is 0.5 t, and the mean is 98,871 t.
Over the past decade 18 countries rose and 9 fell. The largest increase was in C�te d'Ivoire (up 80,060.5%), and the largest decrease in United Arab Emirates (down 100.0%).
Palmkernel Cake — Export Quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Indonesia | 3.57 million t | 2013 | up 364.8% | volatile |
| 2 | Malaysia | 2.48 million t | 2013 | up 37.3% | volatile |
| 3 | Netherlands (Kingdom of the) | 403,903 t | 2013 | down 11.6% | volatile |
| 4 | Nigeria | 70,500 t | 2013 | up 10.0% | volatile |
| 5 | Ecuador | 30,632 t | 2013 | up 934.2% | volatile |
| 6 | C�te d'Ivoire | 30,461 t | 2013 | up 80,060.5% | volatile |
| 7 | Belgium | 26,071 t | 2013 | down 13.2% | falling |
| 8 | Germany | 22,724 t | 2013 | up 138.8% | volatile |
| 9 | Belgium-Luxembourg | 17,551 t | 1999 | up 919.2% | volatile |
| 10 | Ireland | 16,493 t | 2013 | up 4,507.0% | volatile |
| 11 | Spain | 13,921 t | 2013 | up 17,086.4% | volatile |
| 12 | United Kingdom of Great Britain and Northern Ireland | 13,653 t | 2013 | up 672.7% | volatile |
| 13 | Honduras | 12,810 t | 2013 | up 3,678.8% | volatile |
| 14 | Ghana | 3,097 t | 2013 | down 21.8% | volatile |
| 15 | Costa Rica | 2,721 t | 2013 | — | volatile |
| 16 | Denmark | 2,525 t | 2013 | — | volatile |
| 17 | Thailand | 1,570 t | 2013 | up 701.0% | volatile |
| 18 | Colombia | 1,497 t | 2013 | — | volatile |
| 19 | Guatemala | 1,179 t | 2013 | — | volatile |
| 20 | Portugal | 1,124 t | 2013 | up 1,305.0% | volatile |
| 21 | Cameroon | 492 t | 2013 | up 4,372.7% | volatile |
| 22 | Romania | 192 t | 2013 | — | volatile |
| 23 | Italy | 140 t | 2013 | up 259.0% | volatile |
| 24 | Canada | 119 t | 2013 | up 1,222.2% | volatile |
| 25 | Togo | 88 t | 2013 | — | volatile |
| 26 | France | 61 t | 2013 | up 1,425.0% | volatile |
| 27 | Luxembourg | 32 t | 2013 | — | volatile |
| 28 | Sweden | 29 t | 2013 | up 31.8% | volatile |
| 29 | Poland | 25 t | 2013 | — | volatile |
| 29 | Serbia and Montenegro | 25 t | 2005 | — | volatile |
| 31 | Sierra Leone | 20 t | 2013 | — | volatile |
| 32 | Hungary | 6 t | 2013 | — | volatile |
| 33 | Senegal | 2 t | 2013 | — | volatile |
| 34 | United Republic of Tanzania | 1 t | 2013 | — | volatile |
| 35 | Argentina | 0 t | 2013 | — | volatile |
| 35 | Switzerland | 0 t | 2013 | — | volatile |
| 35 | United Arab Emirates | 0 t | 2013 | down 100.0% | volatile |
| 35 | Angola | 0 t | 2013 | — | volatile |
| 35 | Brazil | 0 t | 2013 | — | volatile |
| 35 | Australia and New Zealand | 0 t | 2013 | — | volatile |
| 35 | Australia | 0 t | 2013 | — | volatile |
| 35 | China, mainland | 0 t | 2013 | — | volatile |
| 35 | Austria | 0 t | 2013 | — | volatile |
| 35 | Bulgaria | 0 t | 2013 | — | volatile |
| 35 | China, Taiwan Province of | 0 t | 2013 | — | volatile |
| 35 | Guinea | 0 t | 2013 | — | volatile |
| 35 | Benin | 0 t | 2013 | down 100.0% | volatile |
| 35 | Tunisia | 0 t | 2013 | — | volatile |
| 35 | Mali | 0 t | 2013 | — | volatile |
| 35 | Morocco | 0 t | 2013 | — | volatile |
| 35 | Nicaragua | 0 t | 2013 | — | volatile |
| 35 | Nepal | 0 t | 2013 | — | volatile |
| 35 | Pakistan | 0 t | 2013 | — | volatile |
| 35 | Peru | 0 t | 2013 | — | volatile |
| 35 | Philippines | 0 t | 2013 | down 100.0% | volatile |
| 35 | Latvia | 0 t | 2013 | — | volatile |
| 35 | Paraguay | 0 t | 2013 | down 100.0% | volatile |
| 35 | Slovakia | 0 t | 2013 | — | volatile |
| 35 | Iran (Islamic Republic of) | 0 t | 2013 | — | volatile |
| 35 | Uganda | 0 t | 2013 | — | volatile |
| 35 | Lithuania | 0 t | 2013 | — | volatile |
| 35 | Liberia | 0 t | 2013 | down 100.0% | volatile |
| 35 | Japan | 0 t | 2013 | down 100.0% | volatile |
| 35 | India | 0 t | 2013 | — | volatile |
| 35 | Greece | 0 t | 2013 | — | volatile |
| 35 | Malawi | 0 t | 2013 | — | volatile |
| 35 | Egypt | 0 t | 2013 | — | volatile |
| 35 | Czechia | 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 6.71 million t
- Asia 6.05 million t
- South-eastern Asia 6.05 million t
- Europe 500,899 t
- European Union (27) 487,246 t
- Western Europe 452,791 t
- Low Income Food Deficit Countries 104,661 t
- Africa 104,661 t
- Western Africa 104,168 t
- Americas 48,980 t
- Net Food Importing Developing Countries 43,382 t
- Northern Europe 32,700 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.