Rape and Mustardseed — 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
Rape and Mustardseed — Export quantity is currently reported for 143 countries. The highest value is 7,213 1000 t in Canada; the lowest is 0 1000 t in China, Macao SAR.
The median across all reporting countries is 0 1000 t, and the mean is 228.22 1000 t.
Over the past decade 28 countries rose and 25 fell. The largest increase was in Brazil (up 1,100.0%), and the largest decrease in Belarus (down 100.0%).
Rape and Mustardseed — Export quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Canada | 7,213 1000 t | 2023 | up 1.1% | flat |
| 2 | Australia and New Zealand | 5,801 1000 t | 2023 | up 52.6% | rising |
| 3 | Australia | 5,796 1000 t | 2023 | up 52.6% | rising |
| 4 | Ukraine | 3,041 1000 t | 2023 | up 28.6% | rising |
| 5 | Romania | 2,409 1000 t | 2023 | up 404.0% | volatile |
| 6 | Belgium | 1,296 1000 t | 2023 | up 72.1% | rising |
| 7 | France | 1,138 1000 t | 2023 | down 16.4% | falling |
| 8 | Poland | 891 1000 t | 2023 | up 15.9% | volatile |
| 9 | Netherlands (Kingdom of the) | 788 1000 t | 2023 | down 18.9% | rising |
| 10 | Lithuania | 563 1000 t | 2023 | up 51.8% | rising |
| 11 | Russian Federation | 468 1000 t | 2023 | up 244.1% | volatile |
| 12 | Hungary | 456 1000 t | 2023 | up 7.3% | flat |
| 13 | Latvia | 421 1000 t | 2023 | up 77.6% | rising |
| 14 | Slovakia | 338 1000 t | 2023 | down 12.2% | falling |
| 15 | Uruguay | 331 1000 t | 2023 | — | volatile |
| 16 | Czechia | 314 1000 t | 2023 | down 40.3% | flat |
| 17 | Republic of Moldova | 272 1000 t | 2023 | up 504.4% | volatile |
| 18 | Bulgaria | 148 1000 t | 2023 | down 56.1% | falling |
| 19 | Serbia | 141 1000 t | 2023 | up 464.0% | volatile |
| 20 | Denmark | 136 1000 t | 2023 | down 2.2% | falling |
| 21 | Germany | 133 1000 t | 2023 | down 18.4% | falling |
| 22 | Kazakhstan | 74 1000 t | 2023 | down 24.5% | rising |
| 23 | Mongolia | 68 1000 t | 2023 | up 257.9% | volatile |
| 24 | Spain | 56 1000 t | 2023 | up 154.5% | volatile |
| 25 | United Kingdom of Great Britain and Northern Ireland | 47 1000 t | 2023 | down 89.2% | volatile |
| 26 | India | 42 1000 t | 2023 | up 16.7% | rising |
| 27 | Austria | 35 1000 t | 2023 | down 58.8% | falling |
| 28 | Ireland | 31 1000 t | 2023 | up 93.8% | volatile |
| 29 | Croatia | 27 1000 t | 2023 | up 42.1% | volatile |
| 30 | Argentina | 22 1000 t | 2023 | down 82.9% | volatile |
| 31 | Chile | 20 1000 t | 2023 | up 100.0% | volatile |
| 32 | Estonia | 18 1000 t | 2023 | down 70.0% | falling |
| 33 | Brazil | 12 1000 t | 2023 | up 1,100.0% | volatile |
| 34 | Greece | 10 1000 t | 2023 | — | volatile |
| 34 | Luxembourg | 10 1000 t | 2023 | down 28.6% | falling |
| 36 | Sweden | 9 1000 t | 2023 | down 76.9% | volatile |
| 37 | Slovenia | 7 1000 t | 2023 | down 46.2% | falling |
| 38 | Senegal | 6 1000 t | 2023 | up 200.0% | rising |
| 39 | United Arab Emirates | 4 1000 t | 2023 | up 300.0% | volatile |
| 39 | Guatemala | 4 1000 t | 2023 | up 100.0% | rising |
| 39 | New Zealand | 4 1000 t | 2023 | up 100.0% | rising |
| 39 | Paraguay | 4 1000 t | 2023 | down 83.3% | volatile |
| 39 | Thailand | 4 1000 t | 2023 | — | volatile |
| 44 | China | 3 1000 t | 2023 | down 25.0% | falling |
| 44 | Italy | 3 1000 t | 2023 | unchanged | volatile |
| 44 | Trinidad and Tobago | 3 1000 t | 2023 | up 200.0% | volatile |
| 44 | Caribbean | 3 1000 t | 2023 | up 200.0% | volatile |
| 48 | Costa Rica | 2 1000 t | 2023 | unchanged | rising |
| 48 | Portugal | 2 1000 t | 2023 | up 100.0% | volatile |
| 48 | El Salvador | 2 1000 t | 2023 | up 100.0% | rising |
| 48 | China, mainland | 2 1000 t | 2023 | unchanged | rising |
| 52 | Bosnia and Herzegovina | 1 1000 t | 2023 | — | volatile |
| 52 | Finland | 1 1000 t | 2023 | down 50.0% | rising |
| 52 | Morocco | 1 1000 t | 2023 | — | volatile |
| 52 | Nigeria | 1 1000 t | 2023 | — | volatile |
| 52 | Tunisia | 1 1000 t | 2023 | — | volatile |
| 52 | China, Hong Kong SAR | 1 1000 t | 2023 | down 50.0% | falling |
| 52 | Republic of Korea | 1 1000 t | 2023 | — | volatile |
| 52 | Türkiye | 1 1000 t | 2023 | — | volatile |
| 60 | Albania | 0 1000 t | 2023 | — | flat |
| 60 | Armenia | 0 1000 t | 2023 | — | flat |
| 60 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 60 | Burkina Faso | 0 1000 t | 2022 | — | volatile |
| 60 | Bangladesh | 0 1000 t | 2023 | — | flat |
| 60 | Bahrain | 0 1000 t | 2023 | — | flat |
| 60 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | Belize | 0 1000 t | 2022 | — | flat |
| 60 | Barbados | 0 1000 t | 2022 | — | flat |
| 60 | Bhutan | 0 1000 t | 2023 | — | flat |
| 60 | Botswana | 0 1000 t | 2023 | — | flat |
| 60 | Switzerland | 0 1000 t | 2023 | down 100.0% | falling |
| 60 | Cameroon | 0 1000 t | 2023 | — | flat |
| 60 | Colombia | 0 1000 t | 2023 | — | flat |
| 60 | Cuba | 0 1000 t | 2019 | — | flat |
| 60 | Cyprus | 0 1000 t | 2021 | — | flat |
| 60 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 60 | Algeria | 0 1000 t | 2023 | — | flat |
| 60 | Ecuador | 0 1000 t | 2023 | — | flat |
| 60 | Egypt | 0 1000 t | 2023 | — | volatile |
| 60 | Ethiopia | 0 1000 t | 2023 | — | volatile |
| 60 | Fiji | 0 1000 t | 2023 | — | flat |
| 60 | Georgia | 0 1000 t | 2023 | — | volatile |
| 60 | Ghana | 0 1000 t | 2022 | — | flat |
| 60 | Guinea | 0 1000 t | 2023 | — | flat |
| 60 | Gambia | 0 1000 t | 2023 | — | flat |
| 60 | Guyana | 0 1000 t | 2023 | — | flat |
| 60 | Honduras | 0 1000 t | 2023 | — | flat |
| 60 | Indonesia | 0 1000 t | 2023 | — | volatile |
| 60 | Iceland | 0 1000 t | 2023 | — | flat |
| 60 | Israel | 0 1000 t | 2023 | — | flat |
| 60 | Jamaica | 0 1000 t | 2023 | — | flat |
| 60 | Jordan | 0 1000 t | 2020 | — | flat |
| 60 | Kenya | 0 1000 t | 2023 | — | flat |
| 60 | Kyrgyzstan | 0 1000 t | 2019 | — | flat |
| 60 | Cambodia | 0 1000 t | 2023 | — | flat |
| 60 | Kuwait | 0 1000 t | 2023 | — | flat |
| 60 | Lebanon | 0 1000 t | 2023 | — | flat |
| 60 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 60 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 60 | Lesotho | 0 1000 t | 2020 | — | flat |
| 60 | Madagascar | 0 1000 t | 2023 | — | flat |
| 60 | Mexico | 0 1000 t | 2023 | — | volatile |
| 60 | North Macedonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | Malta | 0 1000 t | 2022 | — | flat |
| 60 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 60 | Montenegro | 0 1000 t | 2019 | — | flat |
| 60 | Mozambique | 0 1000 t | 2023 | — | volatile |
| 60 | Mauritius | 0 1000 t | 2023 | — | flat |
| 60 | Malawi | 0 1000 t | 2023 | — | flat |
| 60 | Malaysia | 0 1000 t | 2023 | — | flat |
| 60 | Namibia | 0 1000 t | 2023 | — | flat |
| 60 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 60 | Niger | 0 1000 t | 2018 | — | volatile |
| 60 | Nicaragua | 0 1000 t | 2022 | — | flat |
| 60 | Norway | 0 1000 t | 2023 | — | flat |
| 60 | Nepal | 0 1000 t | 2020 | — | flat |
| 60 | Oman | 0 1000 t | 2023 | — | volatile |
| 60 | Pakistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | Panama | 0 1000 t | 2023 | — | flat |
| 60 | Peru | 0 1000 t | 2023 | — | flat |
| 60 | Philippines | 0 1000 t | 2023 | — | flat |
| 60 | French Polynesia | 0 1000 t | 2020 | — | flat |
| 60 | Rwanda | 0 1000 t | 2022 | — | flat |
| 60 | Saudi Arabia | 0 1000 t | 2023 | — | flat |
| 60 | Suriname | 0 1000 t | 2017 | — | flat |
| 60 | Eswatini | 0 1000 t | 2020 | — | flat |
| 60 | Uganda | 0 1000 t | 2023 | — | flat |
| 60 | Uzbekistan | 0 1000 t | 2023 | — | flat |
| 60 | Zambia | 0 1000 t | 2023 | — | flat |
| 60 | Zimbabwe | 0 1000 t | 2023 | — | flat |
| 60 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 60 | Melanesia | 0 1000 t | 2023 | — | flat |
| 60 | Polynesia | 0 1000 t | 2021 | — | flat |
| 60 | Democratic Republic of the Congo | 0 1000 t | 2022 | — | flat |
| 60 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 60 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | flat |
| 60 | Syrian Arab Republic | 0 1000 t | 2023 | — | flat |
| 60 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 60 | Viet Nam | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 60 | United Republic of Tanzania | 0 1000 t | 2023 | — | volatile |
| 60 | China, Taiwan Province of | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | China, Macao SAR | 0 1000 t | 2014 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 27,150 1000 t
- Europe 13,212 1000 t
- European Union (27) 9,241 1000 t
- Eastern Europe 8,338 1000 t
- Americas 7,893 1000 t
- Northern America 7,493 1000 t
- Oceania 5,801 1000 t
- Western Europe 3,400 1000 t
- Northern Europe 1,227 1000 t
- Land Locked Developing Countries (LLDCs) 418 1000 t
- South America 390 1000 t
- United States of America 280 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.