Rape and Mustard Oil — 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
Rape and Mustard Oil — Import quantity is currently reported for 123 countries. The highest value is 3,004 1000 t in United States; the lowest is 0 1000 t in Côte d'Ivoire.
The median across all reporting countries is 3 1000 t, and the mean is 108.83 1000 t.
Over the past decade 40 countries rose and 36 fell. The largest increase was in Russia (up 12,000.0%), and the largest decrease in Afghanistan (down 100.0%).
Rape and Mustard Oil — Import quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | United States | 3,004 1000 t | 2023 | up 136.2% | rising |
| 2 | China | 2,429 1000 t | 2023 | up 51.5% | rising |
| 3 | China, mainland | 2,359 1000 t | 2023 | up 54.5% | rising |
| 4 | Netherlands (Kingdom of the) | 1,055 1000 t | 2023 | up 81.3% | rising |
| 5 | Belgium | 642 1000 t | 2023 | up 88.8% | rising |
| 6 | Norway | 455 1000 t | 2023 | up 43.5% | rising |
| 7 | Germany | 446 1000 t | 2023 | up 139.8% | flat |
| 8 | Poland | 197 1000 t | 2023 | up 137.3% | rising |
| 8 | Sweden | 197 1000 t | 2023 | up 20.1% | rising |
| 10 | Mexico | 176 1000 t | 2023 | up 266.7% | volatile |
| 11 | Spain | 160 1000 t | 2023 | up 300.0% | volatile |
| 12 | Republic of Korea | 152 1000 t | 2023 | up 130.3% | rising |
| 13 | France | 142 1000 t | 2023 | down 47.2% | falling |
| 14 | United Kingdom | 140 1000 t | 2023 | up 12.0% | rising |
| 14 | United Kingdom of Great Britain and Northern Ireland | 140 1000 t | 2023 | up 12.0% | rising |
| 16 | Austria | 137 1000 t | 2023 | down 1.4% | falling |
| 16 | Latvia | 137 1000 t | 2023 | up 110.8% | volatile |
| 18 | Russia | 121 1000 t | 2023 | up 12,000.0% | volatile |
| 18 | Russian Federation | 121 1000 t | 2023 | up 12,000.0% | volatile |
| 20 | Chile | 105 1000 t | 2023 | up 133.3% | rising |
| 21 | Australia and New Zealand | 87 1000 t | 2023 | up 55.4% | rising |
| 22 | Israel | 76 1000 t | 2023 | up 111.1% | rising |
| 23 | Lithuania | 73 1000 t | 2023 | down 19.8% | rising |
| 24 | New Zealand | 72 1000 t | 2023 | up 89.5% | rising |
| 25 | Malaysia | 66 1000 t | 2023 | up 26.9% | rising |
| 26 | Denmark | 56 1000 t | 2023 | down 1.8% | rising |
| 27 | Hungary | 55 1000 t | 2023 | up 27.9% | rising |
| 28 | Ireland | 40 1000 t | 2023 | up 2.6% | rising |
| 29 | Slovakia | 35 1000 t | 2023 | down 47.8% | falling |
| 29 | China, Hong Kong SAR | 35 1000 t | 2023 | down 31.4% | falling |
| 31 | China, Taiwan Province of | 33 1000 t | 2023 | up 57.1% | rising |
| 32 | Czechia | 32 1000 t | 2023 | down 64.0% | volatile |
| 33 | Switzerland | 26 1000 t | 2023 | up 225.0% | rising |
| 34 | Philippines | 25 1000 t | 2023 | — | volatile |
| 34 | Portugal | 25 1000 t | 2023 | down 60.9% | falling |
| 36 | Italy | 24 1000 t | 2023 | down 80.8% | volatile |
| 37 | Finland | 23 1000 t | 2023 | up 360.0% | volatile |
| 38 | Canada | 22 1000 t | 2023 | down 72.8% | volatile |
| 39 | Pakistan | 21 1000 t | 2023 | — | volatile |
| 40 | Greece | 17 1000 t | 2023 | up 142.9% | volatile |
| 41 | Australia | 15 1000 t | 2023 | down 16.7% | falling |
| 41 | Brazil | 15 1000 t | 2023 | up 36.4% | rising |
| 41 | Turkey | 15 1000 t | 2023 | — | volatile |
| 41 | Türkiye | 15 1000 t | 2023 | — | volatile |
| 45 | Estonia | 12 1000 t | 2023 | up 9.1% | rising |
| 46 | Vietnam | 10 1000 t | 2023 | up 233.3% | volatile |
| 46 | Viet Nam | 10 1000 t | 2023 | up 233.3% | volatile |
| 48 | Indonesia | 9 1000 t | 2023 | up 80.0% | rising |
| 48 | Tunisia | 9 1000 t | 2023 | — | volatile |
| 50 | Saudi Arabia | 8 1000 t | 2023 | up 166.7% | volatile |
| 50 | Slovenia | 8 1000 t | 2023 | down 27.3% | falling |
| 52 | United Arab Emirates | 7 1000 t | 2023 | up 250.0% | volatile |
| 52 | Algeria | 7 1000 t | 2023 | — | volatile |
| 52 | Croatia | 7 1000 t | 2023 | down 75.0% | volatile |
| 52 | India | 7 1000 t | 2023 | down 82.1% | volatile |
| 52 | Tajikistan | 7 1000 t | 2023 | — | volatile |
| 57 | Romania | 6 1000 t | 2023 | down 73.9% | falling |
| 58 | Colombia | 5 1000 t | 2023 | down 61.5% | rising |
| 58 | Caribbean | 5 1000 t | 2023 | up 150.0% | volatile |
| 60 | Dominican Republic | 4 1000 t | 2023 | unchanged | volatile |
| 60 | Iceland | 4 1000 t | 2023 | up 100.0% | rising |
| 62 | Kenya | 3 1000 t | 2023 | — | volatile |
| 62 | Thailand | 3 1000 t | 2023 | up 200.0% | volatile |
| 64 | Bulgaria | 2 1000 t | 2023 | down 81.8% | volatile |
| 64 | Bosnia and Herzegovina | 2 1000 t | 2023 | up 100.0% | volatile |
| 64 | Honduras | 2 1000 t | 2023 | unchanged | volatile |
| 64 | Nigeria | 2 1000 t | 2023 | — | volatile |
| 64 | Qatar | 2 1000 t | 2023 | — | rising |
| 64 | Serbia | 2 1000 t | 2023 | up 100.0% | volatile |
| 64 | China, Macao SAR | 2 1000 t | 2023 | down 50.0% | falling |
| 71 | Argentina | 1 1000 t | 2023 | down 50.0% | flat |
| 71 | Bahrain | 1 1000 t | 2023 | — | flat |
| 71 | Costa Rica | 1 1000 t | 2023 | — | volatile |
| 71 | Cyprus | 1 1000 t | 2023 | down 80.0% | volatile |
| 71 | Ecuador | 1 1000 t | 2023 | unchanged | falling |
| 71 | Egypt | 1 1000 t | 2023 | — | volatile |
| 71 | Ethiopia | 1 1000 t | 2023 | — | volatile |
| 71 | Fiji | 1 1000 t | 2023 | down 66.7% | rising |
| 71 | Guatemala | 1 1000 t | 2023 | unchanged | volatile |
| 71 | Jordan | 1 1000 t | 2023 | unchanged | volatile |
| 71 | Kazakhstan | 1 1000 t | 2023 | unchanged | volatile |
| 71 | Kuwait | 1 1000 t | 2023 | — | rising |
| 71 | Lebanon | 1 1000 t | 2023 | down 50.0% | falling |
| 71 | Morocco | 1 1000 t | 2023 | down 87.5% | volatile |
| 71 | Malta | 1 1000 t | 2023 | — | volatile |
| 71 | Mauritius | 1 1000 t | 2023 | unchanged | volatile |
| 71 | Oman | 1 1000 t | 2023 | unchanged | volatile |
| 71 | Panama | 1 1000 t | 2023 | down 50.0% | rising |
| 71 | El Salvador | 1 1000 t | 2023 | unchanged | rising |
| 71 | Trinidad and Tobago | 1 1000 t | 2023 | — | volatile |
| 71 | Ukraine | 1 1000 t | 2023 | unchanged | volatile |
| 71 | Uzbekistan | 1 1000 t | 2023 | — | volatile |
| 71 | Melanesia | 1 1000 t | 2023 | down 66.7% | rising |
| 94 | Afghanistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 94 | Angola | 0 1000 t | 2023 | down 100.0% | volatile |
| 94 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 94 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 94 | Bahamas | 0 1000 t | 2023 | — | volatile |
| 94 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 94 | Botswana | 0 1000 t | 2023 | — | volatile |
| 94 | Cote d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 94 | Cuba | 0 1000 t | 2019 | — | volatile |
| 94 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 94 | Ghana | 0 1000 t | 2023 | — | volatile |
| 94 | Haiti | 0 1000 t | 2023 | down 100.0% | volatile |
| 94 | Iraq | 0 1000 t | 2023 | — | volatile |
| 94 | Kyrgyzstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 94 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 94 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 94 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 94 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 94 | Mongolia | 0 1000 t | 2023 | down 100.0% | volatile |
| 94 | Mauritania | 0 1000 t | 2023 | down 100.0% | volatile |
| 94 | Nicaragua | 0 1000 t | 2023 | — | volatile |
| 94 | Nepal | 0 1000 t | 2023 | — | volatile |
| 94 | Peru | 0 1000 t | 2023 | — | volatile |
| 94 | Syria | 0 1000 t | 2019 | — | volatile |
| 94 | Yemen | 0 1000 t | 2023 | down 100.0% | volatile |
| 94 | South Africa | 0 1000 t | 2023 | down 100.0% | volatile |
| 94 | Iran (Islamic Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 94 | Syrian Arab Republic | 0 1000 t | 2019 | — | volatile |
| 94 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 94 | Côte d'Ivoire | 0 1000 t | 2023 | — | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 10,592 1000 t
- Europe 4,279 1000 t
- European Union (27) 3,530 1000 t
- Americas 3,342 1000 t
- Northern America 3,026 1000 t
- United States of America 3,004 1000 t
- Asia 2,859 1000 t
- Eastern Asia 2,594 1000 t
- Western Europe 2,448 1000 t
- Northern Europe 1,137 1000 t
- Eastern Europe 449 1000 t
- Southern Europe 245 1000 t
- Central America 182 1000 t
- South America 128 1000 t
- South-Eastern Asia 114 1000 t
- Western Asia 113 1000 t
- Oceania 88 1000 t
- Net Food Importing Developing Countries (NFIDCs) 47 1000 t
- Southern Asia 29 1000 t
- Africa 24 1000 t
- Northern Africa 17 1000 t
- Low Income Food Deficit Countries (LIFDCs) 13 1000 t
- Land Locked Developing Countries (LLDCs) 11 1000 t
- Central Asia 9 1000 t
- Small island developing States (SIDS) 8 1000 t
- Eastern Africa 5 1000 t
- Least Developed Countries (LDCs) 2 1000 t
- Western Africa 2 1000 t
- Southern Africa 0 1000 t
- Middle Africa 0 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.