Sunflowerseed Oil — Export 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
Sunflowerseed Oil — Export quantity is currently reported for 142 countries. The highest value is 5,741 1000 t in Ukraine; the lowest is 0 1000 t in China, Macao SAR.
The median across all reporting countries is 0 1000 t, and the mean is 114.86 1000 t.
Over the past decade 34 countries rose and 24 fell. The largest increase was in Kazakhstan (up 3,630.0%), and the largest decrease in Albania (down 100.0%).
Sunflowerseed Oil — Export quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Ukraine | 5,741 1000 t | 2023 | up 78.9% | rising |
| 2 | Russian Federation | 3,132 1000 t | 2023 | up 127.9% | rising |
| 3 | Türkiye | 1,090 1000 t | 2023 | up 215.0% | volatile |
| 4 | Argentina | 909 1000 t | 2023 | up 111.9% | flat |
| 5 | Netherlands (Kingdom of the) | 859 1000 t | 2023 | up 65.8% | rising |
| 6 | Bulgaria | 776 1000 t | 2023 | up 302.1% | volatile |
| 7 | Hungary | 659 1000 t | 2023 | up 31.8% | rising |
| 8 | France | 433 1000 t | 2023 | up 25.5% | flat |
| 9 | Kazakhstan | 373 1000 t | 2023 | up 3,630.0% | volatile |
| 10 | Romania | 355 1000 t | 2023 | up 84.9% | rising |
| 11 | Spain | 271 1000 t | 2023 | up 155.7% | rising |
| 12 | Republic of Moldova | 252 1000 t | 2023 | up 486.0% | volatile |
| 13 | Belgium | 181 1000 t | 2023 | up 34.1% | rising |
| 14 | Poland | 153 1000 t | 2023 | up 1,430.0% | volatile |
| 15 | Serbia | 149 1000 t | 2023 | up 19.2% | rising |
| 16 | Germany | 134 1000 t | 2023 | up 8.1% | rising |
| 17 | Bolivia (Plurinational State of) | 113 1000 t | 2023 | up 54.8% | rising |
| 18 | Czechia | 101 1000 t | 2023 | up 248.3% | volatile |
| 19 | Malaysia | 63 1000 t | 2023 | up 50.0% | rising |
| 20 | Egypt | 51 1000 t | 2023 | up 45.7% | falling |
| 21 | Slovenia | 47 1000 t | 2023 | up 135.0% | volatile |
| 22 | Italy | 46 1000 t | 2023 | down 9.8% | rising |
| 23 | Austria | 44 1000 t | 2023 | down 13.7% | falling |
| 24 | Portugal | 40 1000 t | 2023 | down 42.0% | flat |
| 25 | Croatia | 38 1000 t | 2023 | up 1,800.0% | volatile |
| 26 | Bosnia and Herzegovina | 36 1000 t | 2023 | up 9.1% | rising |
| 27 | Saudi Arabia | 30 1000 t | 2023 | up 30.4% | rising |
| 28 | United Arab Emirates | 26 1000 t | 2023 | up 85.7% | falling |
| 29 | Mexico | 20 1000 t | 2023 | down 39.4% | falling |
| 30 | Oman | 17 1000 t | 2023 | down 10.5% | rising |
| 31 | United Kingdom of Great Britain and Northern Ireland | 15 1000 t | 2023 | up 150.0% | volatile |
| 32 | India | 13 1000 t | 2023 | up 1,200.0% | volatile |
| 32 | Morocco | 13 1000 t | 2023 | up 225.0% | volatile |
| 32 | Slovakia | 13 1000 t | 2023 | down 63.9% | volatile |
| 35 | Uzbekistan | 12 1000 t | 2023 | — | volatile |
| 36 | Greece | 10 1000 t | 2023 | up 900.0% | volatile |
| 36 | Lithuania | 10 1000 t | 2023 | unchanged | rising |
| 38 | Uganda | 9 1000 t | 2023 | up 125.0% | volatile |
| 39 | Mozambique | 7 1000 t | 2023 | unchanged | volatile |
| 39 | Sweden | 7 1000 t | 2023 | up 75.0% | flat |
| 39 | United Republic of Tanzania | 7 1000 t | 2023 | unchanged | volatile |
| 42 | Belarus | 6 1000 t | 2023 | — | volatile |
| 42 | North Macedonia | 6 1000 t | 2023 | down 14.3% | volatile |
| 44 | Canada | 4 1000 t | 2023 | unchanged | volatile |
| 44 | Lebanon | 4 1000 t | 2023 | down 33.3% | volatile |
| 44 | Zambia | 4 1000 t | 2023 | down 55.6% | volatile |
| 47 | China | 3 1000 t | 2023 | up 50.0% | rising |
| 47 | Guatemala | 3 1000 t | 2023 | up 50.0% | volatile |
| 47 | China, mainland | 3 1000 t | 2023 | up 200.0% | volatile |
| 50 | Azerbaijan | 2 1000 t | 2023 | down 89.5% | volatile |
| 50 | Ecuador | 2 1000 t | 2023 | — | volatile |
| 50 | Estonia | 2 1000 t | 2023 | down 50.0% | flat |
| 50 | Georgia | 2 1000 t | 2023 | down 50.0% | volatile |
| 50 | Nepal | 2 1000 t | 2023 | — | volatile |
| 55 | Australia | 1 1000 t | 2023 | down 75.0% | volatile |
| 55 | Switzerland | 1 1000 t | 2023 | unchanged | volatile |
| 55 | Colombia | 1 1000 t | 2023 | — | volatile |
| 55 | Djibouti | 1 1000 t | 2023 | — | volatile |
| 55 | Algeria | 1 1000 t | 2023 | unchanged | volatile |
| 55 | Ireland | 1 1000 t | 2023 | — | volatile |
| 55 | Jordan | 1 1000 t | 2022 | unchanged | volatile |
| 55 | Kenya | 1 1000 t | 2023 | unchanged | volatile |
| 55 | Latvia | 1 1000 t | 2023 | down 66.7% | volatile |
| 55 | Thailand | 1 1000 t | 2023 | — | volatile |
| 55 | Tunisia | 1 1000 t | 2023 | — | volatile |
| 55 | Australia and New Zealand | 1 1000 t | 2023 | down 80.0% | volatile |
| 67 | Angola | 0 1000 t | 2023 | — | flat |
| 67 | Albania | 0 1000 t | 2023 | down 100.0% | volatile |
| 67 | Armenia | 0 1000 t | 2023 | — | flat |
| 67 | Burkina Faso | 0 1000 t | 2015 | — | flat |
| 67 | Bangladesh | 0 1000 t | 2023 | — | flat |
| 67 | Bahrain | 0 1000 t | 2023 | — | flat |
| 67 | Bahamas | 0 1000 t | 2019 | — | flat |
| 67 | Brazil | 0 1000 t | 2023 | down 100.0% | volatile |
| 67 | Botswana | 0 1000 t | 2023 | — | volatile |
| 67 | Chile | 0 1000 t | 2023 | — | volatile |
| 67 | Cameroon | 0 1000 t | 2022 | — | flat |
| 67 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 67 | Cuba | 0 1000 t | 2015 | — | flat |
| 67 | Cyprus | 0 1000 t | 2023 | — | volatile |
| 67 | Denmark | 0 1000 t | 2023 | — | flat |
| 67 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 67 | Ethiopia | 0 1000 t | 2023 | — | flat |
| 67 | Finland | 0 1000 t | 2023 | — | flat |
| 67 | Fiji | 0 1000 t | 2023 | — | flat |
| 67 | Gabon | 0 1000 t | 2023 | — | flat |
| 67 | Ghana | 0 1000 t | 2023 | — | flat |
| 67 | Guyana | 0 1000 t | 2022 | — | flat |
| 67 | Honduras | 0 1000 t | 2017 | — | flat |
| 67 | Indonesia | 0 1000 t | 2023 | — | volatile |
| 67 | Iraq | 0 1000 t | 2023 | — | flat |
| 67 | Israel | 0 1000 t | 2023 | — | flat |
| 67 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 67 | Kuwait | 0 1000 t | 2023 | — | volatile |
| 67 | Liberia | 0 1000 t | 2023 | — | flat |
| 67 | Sri Lanka | 0 1000 t | 2019 | — | flat |
| 67 | Lesotho | 0 1000 t | 2020 | — | flat |
| 67 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 67 | Madagascar | 0 1000 t | 2023 | — | flat |
| 67 | Malta | 0 1000 t | 2022 | — | flat |
| 67 | Montenegro | 0 1000 t | 2023 | down 100.0% | volatile |
| 67 | Mongolia | 0 1000 t | 2022 | — | flat |
| 67 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 67 | Malawi | 0 1000 t | 2023 | — | flat |
| 67 | Namibia | 0 1000 t | 2023 | — | volatile |
| 67 | New Caledonia | 0 1000 t | 2015 | — | flat |
| 67 | Nigeria | 0 1000 t | 2023 | — | flat |
| 67 | Nicaragua | 0 1000 t | 2017 | — | flat |
| 67 | Norway | 0 1000 t | 2023 | — | flat |
| 67 | New Zealand | 0 1000 t | 2023 | down 100.0% | volatile |
| 67 | Pakistan | 0 1000 t | 2022 | — | flat |
| 67 | Panama | 0 1000 t | 2020 | — | flat |
| 67 | Peru | 0 1000 t | 2023 | — | flat |
| 67 | Philippines | 0 1000 t | 2021 | — | flat |
| 67 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 67 | Paraguay | 0 1000 t | 2023 | down 100.0% | volatile |
| 67 | Qatar | 0 1000 t | 2023 | — | volatile |
| 67 | Rwanda | 0 1000 t | 2022 | — | volatile |
| 67 | Senegal | 0 1000 t | 2023 | — | volatile |
| 67 | El Salvador | 0 1000 t | 2022 | — | flat |
| 67 | Suriname | 0 1000 t | 2021 | — | flat |
| 67 | Eswatini | 0 1000 t | 2017 | down 100.0% | volatile |
| 67 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 67 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 67 | Vanuatu | 0 1000 t | 2014 | — | flat |
| 67 | Samoa | 0 1000 t | 2019 | — | flat |
| 67 | Yemen | 0 1000 t | 2020 | — | volatile |
| 67 | Zimbabwe | 0 1000 t | 2022 | down 100.0% | volatile |
| 67 | Micronesia | 0 1000 t | 2022 | — | flat |
| 67 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 67 | Melanesia | 0 1000 t | 2023 | — | flat |
| 67 | Polynesia | 0 1000 t | 2019 | — | flat |
| 67 | Caribbean | 0 1000 t | 2023 | — | flat |
| 67 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 67 | Iran (Islamic Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 67 | Republic of Korea | 0 1000 t | 2023 | — | flat |
| 67 | Syrian Arab Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 67 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2021 | — | flat |
| 67 | Viet Nam | 0 1000 t | 2023 | — | flat |
| 67 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 67 | China, Taiwan Province of | 0 1000 t | 2023 | — | volatile |
| 67 | China, Macao SAR | 0 1000 t | 2018 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 16,418 1000 t
- Europe 13,519 1000 t
- Eastern Europe 11,188 1000 t
- European Union (27) 4,182 1000 t
- Western Europe 1,652 1000 t
- Asia 1,639 1000 t
- Western Asia 1,172 1000 t
- Americas 1,110 1000 t
- South America 1,026 1000 t
- Land Locked Developing Countries (LLDCs) 774 1000 t
- Southern Europe 643 1000 t
- Central Asia 385 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.