Oilcrops, Other — Import quantity by country
A 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
Oilcrops, Other — Import quantity is currently reported for 179 countries. The highest value is 1,389 1000 t in China; the lowest is 0 1000 t in China, Macao SAR.
The median across all reporting countries is 1 1000 t, and the mean is 33.79 1000 t.
Over the past decade 41 countries rose and 36 fell. The largest increase was in Viet Nam (up 9,366.7%), and the largest decrease in Belarus (down 100.0%).
Oilcrops, Other — Import quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 1,389 1000 t | 2023 | up 476.3% | volatile |
| 2 | China, mainland | 1,359 1000 t | 2023 | up 509.4% | volatile |
| 3 | Belgium | 646 1000 t | 2023 | up 17.2% | rising |
| 4 | Republic of Korea | 309 1000 t | 2023 | up 159.7% | rising |
| 5 | Ghana | 290 1000 t | 2023 | — | volatile |
| 6 | Viet Nam | 284 1000 t | 2023 | up 9,366.7% | volatile |
| 7 | Türkiye | 172 1000 t | 2023 | up 26.5% | volatile |
| 8 | Germany | 151 1000 t | 2023 | down 8.5% | rising |
| 9 | Poland | 148 1000 t | 2023 | up 300.0% | volatile |
| 10 | Netherlands (Kingdom of the) | 131 1000 t | 2023 | up 28.4% | rising |
| 11 | Peru | 86 1000 t | 2023 | up 4,200.0% | volatile |
| 12 | India | 79 1000 t | 2023 | up 23.4% | rising |
| 13 | Spain | 69 1000 t | 2023 | up 72.5% | rising |
| 14 | France | 68 1000 t | 2023 | down 30.6% | falling |
| 15 | Kazakhstan | 59 1000 t | 2023 | up 1,866.7% | volatile |
| 16 | Italy | 54 1000 t | 2023 | up 68.8% | rising |
| 16 | Russian Federation | 54 1000 t | 2023 | up 134.8% | rising |
| 18 | Uzbekistan | 51 1000 t | 2023 | — | volatile |
| 19 | Afghanistan | 45 1000 t | 2023 | up 114.3% | volatile |
| 20 | Tajikistan | 40 1000 t | 2023 | — | volatile |
| 21 | United Kingdom of Great Britain and Northern Ireland | 38 1000 t | 2023 | down 15.6% | falling |
| 22 | Austria | 35 1000 t | 2023 | up 40.0% | rising |
| 23 | Bulgaria | 31 1000 t | 2023 | up 675.0% | volatile |
| 24 | China, Taiwan Province of | 30 1000 t | 2023 | up 76.5% | rising |
| 25 | Czechia | 27 1000 t | 2023 | up 170.0% | rising |
| 26 | Egypt | 25 1000 t | 2023 | up 127.3% | volatile |
| 27 | Canada | 23 1000 t | 2023 | down 14.8% | rising |
| 27 | Sweden | 23 1000 t | 2023 | down 4.2% | rising |
| 29 | Mexico | 19 1000 t | 2023 | up 72.7% | rising |
| 30 | Zimbabwe | 16 1000 t | 2023 | up 14.3% | volatile |
| 31 | Argentina | 15 1000 t | 2023 | up 1,400.0% | volatile |
| 31 | Chile | 15 1000 t | 2023 | up 275.0% | volatile |
| 33 | Iceland | 13 1000 t | 2023 | up 116.7% | rising |
| 34 | Australia and New Zealand | 12 1000 t | 2023 | down 20.0% | falling |
| 35 | Australia | 11 1000 t | 2023 | up 10.0% | rising |
| 36 | Eswatini | 10 1000 t | 2023 | — | volatile |
| 37 | Lithuania | 9 1000 t | 2023 | up 350.0% | volatile |
| 37 | Romania | 9 1000 t | 2023 | up 80.0% | rising |
| 39 | Brazil | 8 1000 t | 2023 | down 57.9% | falling |
| 39 | Switzerland | 8 1000 t | 2023 | unchanged | rising |
| 39 | Denmark | 8 1000 t | 2023 | down 38.5% | falling |
| 39 | Jordan | 8 1000 t | 2023 | up 33.3% | rising |
| 43 | Gambia | 7 1000 t | 2023 | up 600.0% | volatile |
| 43 | Hungary | 7 1000 t | 2023 | up 75.0% | rising |
| 43 | Kenya | 7 1000 t | 2023 | down 56.2% | volatile |
| 43 | Malaysia | 7 1000 t | 2023 | down 88.5% | volatile |
| 43 | Slovenia | 7 1000 t | 2023 | up 250.0% | rising |
| 48 | Iraq | 6 1000 t | 2023 | — | volatile |
| 48 | Libya | 6 1000 t | 2023 | up 500.0% | volatile |
| 48 | Philippines | 6 1000 t | 2023 | down 62.5% | volatile |
| 51 | Latvia | 5 1000 t | 2023 | up 150.0% | volatile |
| 51 | Portugal | 5 1000 t | 2023 | down 91.5% | volatile |
| 51 | Slovakia | 5 1000 t | 2023 | up 150.0% | rising |
| 51 | Thailand | 5 1000 t | 2023 | down 16.7% | falling |
| 55 | United Arab Emirates | 4 1000 t | 2023 | up 300.0% | volatile |
| 55 | Burkina Faso | 4 1000 t | 2023 | up 300.0% | volatile |
| 55 | Dominican Republic | 4 1000 t | 2023 | — | volatile |
| 55 | Guyana | 4 1000 t | 2023 | — | volatile |
| 55 | Namibia | 4 1000 t | 2023 | — | volatile |
| 55 | Norway | 4 1000 t | 2023 | unchanged | rising |
| 55 | Saudi Arabia | 4 1000 t | 2023 | — | volatile |
| 55 | Caribbean | 4 1000 t | 2023 | — | volatile |
| 55 | Bolivia (Plurinational State of) | 4 1000 t | 2023 | — | volatile |
| 64 | Bangladesh | 3 1000 t | 2023 | — | volatile |
| 64 | Greece | 3 1000 t | 2023 | down 82.4% | volatile |
| 64 | Croatia | 3 1000 t | 2023 | up 200.0% | rising |
| 64 | Indonesia | 3 1000 t | 2023 | up 200.0% | volatile |
| 64 | Ireland | 3 1000 t | 2023 | down 40.0% | falling |
| 64 | Israel | 3 1000 t | 2023 | down 25.0% | rising |
| 64 | Morocco | 3 1000 t | 2023 | down 40.0% | volatile |
| 64 | Serbia | 3 1000 t | 2023 | up 50.0% | rising |
| 64 | Ukraine | 3 1000 t | 2023 | down 62.5% | falling |
| 64 | Côte d'Ivoire | 3 1000 t | 2023 | — | volatile |
| 64 | United Republic of Tanzania | 3 1000 t | 2023 | unchanged | volatile |
| 75 | Colombia | 2 1000 t | 2023 | up 100.0% | rising |
| 75 | Algeria | 2 1000 t | 2023 | down 50.0% | falling |
| 75 | Finland | 2 1000 t | 2023 | unchanged | rising |
| 75 | Kyrgyzstan | 2 1000 t | 2023 | — | volatile |
| 75 | Mozambique | 2 1000 t | 2023 | — | volatile |
| 75 | Pakistan | 2 1000 t | 2023 | — | volatile |
| 75 | Iran (Islamic Republic of) | 2 1000 t | 2023 | down 87.5% | volatile |
| 82 | Bosnia and Herzegovina | 1 1000 t | 2023 | — | volatile |
| 82 | Congo | 1 1000 t | 2023 | — | volatile |
| 82 | Costa Rica | 1 1000 t | 2023 | unchanged | volatile |
| 82 | Ecuador | 1 1000 t | 2023 | unchanged | rising |
| 82 | Estonia | 1 1000 t | 2023 | unchanged | volatile |
| 82 | Guatemala | 1 1000 t | 2023 | down 50.0% | volatile |
| 82 | Kuwait | 1 1000 t | 2023 | down 87.5% | volatile |
| 82 | Lebanon | 1 1000 t | 2023 | unchanged | volatile |
| 82 | North Macedonia | 1 1000 t | 2023 | unchanged | falling |
| 82 | Nepal | 1 1000 t | 2023 | — | volatile |
| 82 | New Zealand | 1 1000 t | 2023 | down 80.0% | volatile |
| 82 | Oman | 1 1000 t | 2023 | — | volatile |
| 82 | El Salvador | 1 1000 t | 2023 | unchanged | volatile |
| 82 | Tunisia | 1 1000 t | 2023 | — | volatile |
| 82 | Yemen | 1 1000 t | 2023 | — | volatile |
| 82 | Republic of Moldova | 1 1000 t | 2023 | — | volatile |
| 98 | Angola | 0 1000 t | 2023 | — | volatile |
| 98 | Albania | 0 1000 t | 2023 | — | flat |
| 98 | Armenia | 0 1000 t | 2023 | — | flat |
| 98 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 98 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 98 | Bahrain | 0 1000 t | 2023 | — | flat |
| 98 | Bahamas | 0 1000 t | 2023 | — | flat |
| 98 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | Belize | 0 1000 t | 2023 | — | flat |
| 98 | Barbados | 0 1000 t | 2023 | — | flat |
| 98 | Bhutan | 0 1000 t | 2023 | — | flat |
| 98 | Botswana | 0 1000 t | 2023 | — | flat |
| 98 | Cameroon | 0 1000 t | 2023 | — | volatile |
| 98 | Comoros | 0 1000 t | 2023 | — | flat |
| 98 | Cuba | 0 1000 t | 2019 | — | flat |
| 98 | Cyprus | 0 1000 t | 2023 | — | volatile |
| 98 | Djibouti | 0 1000 t | 2023 | — | flat |
| 98 | Ethiopia | 0 1000 t | 2023 | — | volatile |
| 98 | Fiji | 0 1000 t | 2023 | — | volatile |
| 98 | Gabon | 0 1000 t | 2023 | — | flat |
| 98 | Georgia | 0 1000 t | 2023 | — | volatile |
| 98 | Guinea | 0 1000 t | 2023 | — | flat |
| 98 | Guinea-Bissau | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | Grenada | 0 1000 t | 2023 | — | flat |
| 98 | Honduras | 0 1000 t | 2023 | — | flat |
| 98 | Haiti | 0 1000 t | 2023 | — | volatile |
| 98 | Jamaica | 0 1000 t | 2023 | — | flat |
| 98 | Cambodia | 0 1000 t | 2023 | — | flat |
| 98 | Kiribati | 0 1000 t | 2023 | — | flat |
| 98 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 98 | Liberia | 0 1000 t | 2023 | — | volatile |
| 98 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 98 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 98 | Lesotho | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | Luxembourg | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 98 | Maldives | 0 1000 t | 2023 | — | flat |
| 98 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 98 | Malta | 0 1000 t | 2023 | — | volatile |
| 98 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 98 | Montenegro | 0 1000 t | 2023 | — | volatile |
| 98 | Mongolia | 0 1000 t | 2023 | — | flat |
| 98 | Mauritania | 0 1000 t | 2023 | — | volatile |
| 98 | Mauritius | 0 1000 t | 2023 | — | flat |
| 98 | Malawi | 0 1000 t | 2023 | — | flat |
| 98 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 98 | Niger | 0 1000 t | 2023 | — | volatile |
| 98 | Nigeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | Nicaragua | 0 1000 t | 2023 | — | flat |
| 98 | Panama | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | Papua New Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | Paraguay | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | French Polynesia | 0 1000 t | 2023 | — | volatile |
| 98 | Qatar | 0 1000 t | 2023 | — | volatile |
| 98 | Rwanda | 0 1000 t | 2023 | — | volatile |
| 98 | Senegal | 0 1000 t | 2023 | — | volatile |
| 98 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 98 | Sierra Leone | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 98 | Suriname | 0 1000 t | 2023 | — | flat |
| 98 | Seychelles | 0 1000 t | 2023 | — | flat |
| 98 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 98 | Tonga | 0 1000 t | 2023 | — | flat |
| 98 | Trinidad and Tobago | 0 1000 t | 2023 | — | volatile |
| 98 | Uganda | 0 1000 t | 2023 | — | flat |
| 98 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 98 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 98 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 98 | Samoa | 0 1000 t | 2023 | — | flat |
| 98 | Zambia | 0 1000 t | 2023 | — | flat |
| 98 | Micronesia | 0 1000 t | 2023 | — | flat |
| 98 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 98 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 98 | Melanesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | Polynesia | 0 1000 t | 2023 | — | volatile |
| 98 | Democratic Republic of the Congo | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 98 | Syrian Arab Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 98 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 98 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | flat |
| 98 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 4,865 1000 t
- Asia 2,494 1000 t
- Eastern Asia 1,703 1000 t
- Europe 1,577 1000 t
- European Union (27) 1,450 1000 t
- Western Europe 1,040 1000 t
- Africa 406 1000 t
- Americas 374 1000 t
- Western Africa 318 1000 t
- South-eastern Asia 305 1000 t
- Eastern Europe 286 1000 t
- Land Locked Developing Countries (LLDCs) 236 1000 t
About this data
A 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 capita 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.