Rape and Mustard 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
Rape and Mustard Cake — Import Quantity is currently reported for 107 countries. The highest value is 1.11 million t in Netherlands (Kingdom of the); the lowest is 0 t in C�te d'Ivoire.
The median across all reporting countries is 2,569 t, and the mean is 65,766 t.
Over the past decade 44 countries rose and 12 fell. The largest increase was in New Zealand (up 1,066,700.0%), and the largest decrease in Albania (down 100.0%).
Rape and Mustard Cake — Import Quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Netherlands (Kingdom of the) | 1.11 million t | 2013 | up 183.3% | volatile |
| 2 | Spain | 826,966 t | 2013 | up 4,290.6% | volatile |
| 3 | France | 585,442 t | 2013 | up 103.1% | volatile |
| 4 | Germany | 527,574 t | 2013 | up 114.7% | volatile |
| 5 | Republic of Korea | 439,557 t | 2013 | up 66.7% | volatile |
| 6 | Thailand | 377,179 t | 2013 | up 172.9% | volatile |
| 7 | Denmark | 326,965 t | 2013 | up 111.5% | volatile |
| 8 | Ireland | 288,739 t | 2013 | up 156.3% | volatile |
| 9 | United Kingdom of Great Britain and Northern Ireland | 272,178 t | 2013 | up 89.0% | volatile |
| 10 | Finland | 220,289 t | 2013 | up 154.1% | volatile |
| 11 | Indonesia | 152,446 t | 2013 | up 169.8% | volatile |
| 12 | Democratic People's Republic of Korea | 130,000 t | 2013 | up 396.4% | volatile |
| 13 | China, mainland | 125,879 t | 2013 | up 780.3% | volatile |
| 14 | Norway | 124,325 t | 2013 | up 128.2% | volatile |
| 15 | Sweden | 113,012 t | 2013 | up 54.2% | volatile |
| 16 | Belgium | 105,666 t | 2013 | up 0.7% | rising |
| 17 | Italy | 101,742 t | 2013 | up 121.4% | volatile |
| 18 | Belgium-Luxembourg | 94,364 t | 1999 | up 479.3% | volatile |
| 19 | Austria | 75,226 t | 2013 | up 101.4% | volatile |
| 20 | Portugal | 72,178 t | 2013 | — | volatile |
| 21 | Japan | 68,451 t | 2013 | up 246.0% | volatile |
| 22 | Mexico | 65,372 t | 2013 | up 451.2% | volatile |
| 23 | Switzerland | 64,195 t | 2013 | up 649.5% | volatile |
| 24 | China, Taiwan Province of | 63,717 t | 2013 | down 34.6% | volatile |
| 25 | Saudi Arabia | 63,149 t | 2013 | — | volatile |
| 26 | Poland | 60,816 t | 2013 | up 2,252.7% | volatile |
| 27 | Morocco | 53,421 t | 2013 | — | volatile |
| 28 | Czechia | 49,344 t | 2013 | up 35.3% | volatile |
| 29 | Lithuania | 40,850 t | 2013 | up 709.6% | volatile |
| 30 | T�rkiye | 39,771 t | 2013 | — | volatile |
| 31 | Israel | 35,303 t | 2013 | up 783.2% | volatile |
| 32 | Hungary | 35,000 t | 2013 | — | volatile |
| 33 | Latvia | 34,405 t | 2013 | up 68,710.0% | volatile |
| 34 | Estonia | 33,881 t | 2013 | up 852.5% | volatile |
| 35 | Iran (Islamic Republic of) | 29,064 t | 2013 | — | volatile |
| 36 | Malaysia | 29,009 t | 2013 | up 444.1% | volatile |
| 37 | New Zealand | 21,336 t | 2013 | up 1,066,700.0% | volatile |
| 37 | Australia and New Zealand | 21,336 t | 2013 | up 1,066,700.0% | volatile |
| 39 | Slovenia | 20,203 t | 2013 | up 350.2% | volatile |
| 40 | Pakistan | 18,394 t | 2013 | — | volatile |
| 41 | Czechoslovakia | 15,200 t | 1992 | — | volatile |
| 42 | Croatia | 14,558 t | 2013 | up 35,407.3% | volatile |
| 43 | Slovakia | 12,533 t | 2013 | up 549.4% | volatile |
| 44 | Luxembourg | 12,219 t | 2013 | up 189.7% | rising |
| 45 | Canada | 11,566 t | 2013 | up 10.3% | volatile |
| 46 | United Arab Emirates | 9,000 t | 2013 | up 1,692.8% | volatile |
| 47 | USSR | 7,000 t | 1991 | down 53.3% | volatile |
| 48 | Romania | 3,865 t | 2013 | up 77,200.0% | volatile |
| 49 | India | 3,682 t | 2013 | up 986.1% | volatile |
| 50 | Philippines | 3,498 t | 2013 | down 6.3% | volatile |
| 51 | Oman | 3,173 t | 2013 | up 202.2% | volatile |
| 52 | Brazil | 3,000 t | 2013 | up 6.2% | volatile |
| 53 | Nepal | 2,973 t | 2013 | up 239.8% | volatile |
| 54 | Kuwait | 2,569 t | 2013 | — | volatile |
| 55 | Sri Lanka | 2,144 t | 2013 | — | volatile |
| 56 | Cyprus | 1,650 t | 2013 | — | volatile |
| 57 | Russian Federation | 1,520 t | 2013 | — | volatile |
| 58 | Egypt | 1,103 t | 2013 | — | volatile |
| 59 | Greece | 980 t | 2013 | — | volatile |
| 60 | Bulgaria | 852 t | 2013 | — | volatile |
| 61 | Uruguay | 682 t | 2013 | — | volatile |
| 62 | Bosnia and Herzegovina | 399 t | 2013 | — | volatile |
| 63 | New Caledonia | 325 t | 2013 | — | volatile |
| 63 | Melanesia | 325 t | 2013 | — | volatile |
| 65 | Lebanon | 316 t | 2013 | — | volatile |
| 66 | Yugoslav SFR | 300 t | 1991 | — | volatile |
| 67 | Jordan | 250 t | 2013 | — | volatile |
| 68 | Serbia | 218 t | 2013 | down 33.7% | volatile |
| 69 | Kenya | 170 t | 2013 | up 750.0% | volatile |
| 70 | Cabo Verde | 165 t | 2013 | — | volatile |
| 71 | Kyrgyzstan | 150 t | 2013 | — | volatile |
| 72 | Azerbaijan | 95 t | 2013 | — | volatile |
| 73 | Belarus | 79 t | 2013 | down 89.7% | volatile |
| 74 | Serbia and Montenegro | 74 t | 2005 | — | volatile |
| 75 | Kazakhstan | 70 t | 2013 | — | volatile |
| 76 | Eswatini | 63 t | 2013 | up 600.0% | volatile |
| 77 | Niger | 28 t | 2013 | — | volatile |
| 78 | Peru | 19 t | 2013 | — | volatile |
| 79 | Burkina Faso | 9 t | 2013 | — | volatile |
| 79 | Guinea | 9 t | 2013 | — | volatile |
| 81 | Senegal | 4 t | 2013 | — | volatile |
| 81 | United Republic of Tanzania | 4 t | 2013 | — | volatile |
| 83 | Albania | 0 t | 2013 | down 100.0% | volatile |
| 83 | Armenia | 0 t | 2013 | — | volatile |
| 83 | Australia | 0 t | 2013 | — | volatile |
| 83 | Botswana | 0 t | 2013 | down 100.0% | volatile |
| 83 | Chile | 0 t | 2013 | — | volatile |
| 83 | Algeria | 0 t | 2013 | down 100.0% | volatile |
| 83 | Guatemala | 0 t | 2013 | — | volatile |
| 83 | Iceland | 0 t | 2013 | — | volatile |
| 83 | North Macedonia | 0 t | 2013 | — | volatile |
| 83 | Mali | 0 t | 2013 | — | volatile |
| 83 | Malta | 0 t | 2013 | — | volatile |
| 83 | Mauritania | 0 t | 2013 | — | volatile |
| 83 | Malawi | 0 t | 2013 | — | volatile |
| 83 | Nicaragua | 0 t | 2013 | — | volatile |
| 83 | French Polynesia | 0 t | 2013 | down 100.0% | volatile |
| 83 | Rwanda | 0 t | 2013 | down 100.0% | volatile |
| 83 | Tunisia | 0 t | 2013 | — | volatile |
| 83 | Uganda | 0 t | 2013 | — | volatile |
| 83 | Ukraine | 0 t | 2013 | — | volatile |
| 83 | Zambia | 0 t | 2013 | — | volatile |
| 83 | Polynesia | 0 t | 2013 | down 100.0% | volatile |
| 83 | China, Hong Kong SAR | 0 t | 2013 | — | volatile |
| 83 | Venezuela (Bolivarian Republic of) | 0 t | 2013 | — | volatile |
| 83 | Brunei Darussalam | 0 t | 2013 | down 100.0% | volatile |
| 83 | C�te d'Ivoire | 0 t | 2013 | — | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 10.03 million t
- Europe 5.14 million t
- European Union (27) 4.68 million t
- Americas 3.22 million t
- Northern America 3.15 million t
- United States of America 3.14 million t
- Western Europe 2.48 million t
- Asia 1.60 million t
- Northern Europe 1.45 million t
- Southern Europe 1.04 million t
- Eastern Asia 827,604 t
- South-eastern Asia 562,132 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.