Copra Cake — Import 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
Copra Cake — Import Quantity is currently reported for 106 countries. The highest value is 589,535 t in Republic of Korea; the lowest is 0 t in China, Macao SAR.
The median across all reporting countries is 2.5 t, and the mean is 10,624 t.
Over the past decade 12 countries rose and 32 fell. The largest increase was in China, mainland (up 120,504.0%), and the largest decrease in Austria (down 100.0%).
Copra Cake — Import Quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Republic of Korea | 589,535 t | 2013 | up 61.0% | volatile |
| 2 | Viet Nam | 192,500 t | 2013 | up 94.2% | volatile |
| 2 | China, mainland | 129,046 t | 2013 | up 120,504.0% | volatile |
| 3 | Belgium-Luxembourg | 79,305 t | 1999 | up 2.3% | volatile |
| 3 | Iran (Islamic Republic of) | 667 t | 2013 | — | volatile |
| 4 | China, Taiwan Province of | 35,070 t | 2013 | up 51.1% | volatile |
| 5 | India | 27,219 t | 2013 | down 61.4% | volatile |
| 5 | Melanesia | 40 t | 2013 | up 60.0% | volatile |
| 6 | Japan | 13,893 t | 2013 | down 29.2% | volatile |
| 6 | United Republic of Tanzania | 2 t | 2013 | — | volatile |
| 7 | Australia and New Zealand | 12,215 t | 2013 | down 71.4% | volatile |
| 7 | Polynesia | 0 t | 2013 | — | volatile |
| 7 | Venezuela (Bolivarian Republic of) | 0 t | 2013 | — | volatile |
| 8 | Australia | 9,788 t | 2013 | down 76.2% | volatile |
| 9 | Belgium | 7,275 t | 2013 | down 87.4% | volatile |
| 10 | Poland | 6,475 t | 2013 | — | volatile |
| 11 | Netherlands (Kingdom of the) | 5,920 t | 2013 | down 96.8% | volatile |
| 12 | Italy | 4,386 t | 2013 | down 35.0% | volatile |
| 13 | South Africa | 2,681 t | 2013 | down 71.6% | volatile |
| 14 | New Zealand | 2,427 t | 2013 | up 49.4% | volatile |
| 15 | Madagascar | 1,752 t | 2013 | — | volatile |
| 16 | Indonesia | 1,330 t | 2013 | down 39.5% | volatile |
| 17 | France | 938 t | 2013 | down 90.9% | volatile |
| 18 | Nicaragua | 723 t | 2013 | up 1,506.7% | volatile |
| 19 | Malaysia | 605 t | 2013 | up 228.8% | volatile |
| 20 | United Arab Emirates | 395 t | 2013 | up 2,094.4% | volatile |
| 21 | Philippines | 300 t | 2013 | — | volatile |
| 22 | Eswatini | 278 t | 2013 | down 76.8% | volatile |
| 23 | United Kingdom of Great Britain and Northern Ireland | 249 t | 2013 | down 99.1% | volatile |
| 24 | Mali | 205 t | 2013 | — | volatile |
| 25 | Portugal | 178 t | 2013 | down 96.4% | volatile |
| 26 | Denmark | 114 t | 2013 | — | volatile |
| 26 | Caribbean | 36 t | 2013 | down 73.9% | volatile |
| 27 | Chile | 112 t | 2013 | — | volatile |
| 28 | Finland | 101 t | 2013 | — | volatile |
| 29 | Canada | 59 t | 2013 | — | volatile |
| 30 | Ethiopia | 53 t | 2013 | down 32.9% | volatile |
| 31 | Nigeria | 51 t | 2013 | — | volatile |
| 32 | Albania | 49 t | 2013 | — | volatile |
| 33 | Ireland | 42 t | 2013 | down 99.5% | volatile |
| 34 | New Caledonia | 40 t | 2013 | up 60.0% | volatile |
| 35 | Slovakia | 22 t | 2013 | up 69.2% | volatile |
| 36 | Saint Kitts and Nevis | 13 t | 2013 | — | volatile |
| 37 | Saint Lucia | 12 t | 2013 | down 68.4% | volatile |
| 38 | Trinidad and Tobago | 11 t | 2013 | down 89.0% | volatile |
| 39 | Czechia | 10 t | 2013 | down 82.1% | volatile |
| 39 | Romania | 10 t | 2013 | — | volatile |
| 41 | Morocco | 9 t | 2013 | — | volatile |
| 41 | Mexico | 9 t | 2013 | — | volatile |
| 43 | Bulgaria | 8 t | 2013 | — | volatile |
| 44 | Germany | 6 t | 2013 | down 89.1% | volatile |
| 45 | Latvia | 4 t | 2013 | — | volatile |
| 45 | Brunei Darussalam | 4 t | 2013 | — | volatile |
| 47 | Colombia | 3 t | 2013 | — | volatile |
| 47 | Kazakhstan | 3 t | 2013 | — | volatile |
| 47 | Zambia | 3 t | 2013 | — | volatile |
| 50 | Switzerland | 2 t | 2013 | — | volatile |
| 50 | Uganda | 2 t | 2013 | — | volatile |
| 52 | Burkina Faso | 1 t | 2013 | down 98.0% | volatile |
| 52 | Rwanda | 1 t | 2013 | — | volatile |
| 52 | Sweden | 1 t | 2013 | — | volatile |
| 55 | Argentina | 0 t | 2013 | — | volatile |
| 55 | Austria | 0 t | 2013 | down 100.0% | volatile |
| 55 | Brazil | 0 t | 2013 | — | volatile |
| 55 | Barbados | 0 t | 2013 | — | volatile |
| 55 | Botswana | 0 t | 2013 | down 100.0% | volatile |
| 55 | Costa Rica | 0 t | 2013 | — | volatile |
| 55 | Cyprus | 0 t | 2013 | — | volatile |
| 55 | Ecuador | 0 t | 2013 | — | volatile |
| 55 | Spain | 0 t | 2013 | down 100.0% | volatile |
| 55 | Fiji | 0 t | 2013 | — | volatile |
| 55 | Georgia | 0 t | 2013 | — | volatile |
| 55 | Ghana | 0 t | 2013 | — | volatile |
| 55 | Greece | 0 t | 2013 | — | volatile |
| 55 | Grenada | 0 t | 2013 | — | volatile |
| 55 | Guatemala | 0 t | 2013 | — | volatile |
| 55 | Guyana | 0 t | 2013 | — | volatile |
| 55 | Honduras | 0 t | 2013 | down 100.0% | volatile |
| 55 | Croatia | 0 t | 2013 | — | volatile |
| 55 | Hungary | 0 t | 2013 | — | volatile |
| 55 | Kenya | 0 t | 2013 | — | volatile |
| 55 | Sri Lanka | 0 t | 2013 | down 100.0% | volatile |
| 55 | Lithuania | 0 t | 2013 | — | volatile |
| 55 | Luxembourg | 0 t | 2013 | down 100.0% | volatile |
| 55 | North Macedonia | 0 t | 2013 | — | volatile |
| 55 | Mauritania | 0 t | 2013 | — | volatile |
| 55 | Mauritius | 0 t | 2013 | — | volatile |
| 55 | Malawi | 0 t | 2013 | down 100.0% | volatile |
| 55 | Niger | 0 t | 2013 | — | volatile |
| 55 | Norway | 0 t | 2013 | — | volatile |
| 55 | Nepal | 0 t | 2013 | — | volatile |
| 55 | Pakistan | 0 t | 2013 | — | volatile |
| 55 | Paraguay | 0 t | 2013 | — | volatile |
| 55 | French Polynesia | 0 t | 2013 | — | volatile |
| 55 | Saudi Arabia | 0 t | 2013 | down 100.0% | volatile |
| 55 | Senegal | 0 t | 2013 | — | volatile |
| 55 | El Salvador | 0 t | 2013 | down 100.0% | volatile |
| 55 | Slovenia | 0 t | 2013 | — | volatile |
| 55 | Thailand | 0 t | 2013 | — | volatile |
| 55 | Ukraine | 0 t | 2013 | — | volatile |
| 55 | Zimbabwe | 0 t | 2013 | down 100.0% | volatile |
| 55 | Serbia and Montenegro | 0 t | 2005 | — | volatile |
| 55 | China, Hong Kong SAR | 0 t | 2013 | — | volatile |
| 55 | Russian Federation | 0 t | 2013 | — | volatile |
| 55 | C�te d'Ivoire | 0 t | 2013 | — | volatile |
| 55 | China, Macao SAR | 0 t | 2013 | down 100.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 1.04 million t
- Asia 990,567 t
- Eastern Asia 767,544 t
- South-Eastern Asia 194,739 t
- Low Income Food Deficit Countries 30,009 t
- Land Locked Developing Countries 546 t
- Southern Asia 27,886 t
- Europe 25,790 t
- European Union (27) 25,490 t
- Western Europe 14,141 t
- Oceania 12,255 t
- Eastern Europe 6,525 t
- Africa 5,038 t
- Southern Europe 4,613 t
- Americas 3,072 t
- Southern Africa 2,959 t
- Net Food Importing Developing Countries 2,342 t
- Northern America 2,189 t
- United States of America 2,130 t
- Least developed countries 2,019 t
- Eastern Africa 1,813 t
- Central America 732 t
- Northern Europe 511 t
- Western Asia 395 t
- Western Africa 257 t
- South America 115 t
- Small Island Developing States 76 t
- Northern Africa 9 t
- Central Asia 3 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.