Rape and Mustardseed — Export 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 Mustardseed — Export Quantity is currently reported for 126 countries. The highest value is 7.13 million t in Canada; the lowest is 0 t in China, Macao SAR.
The median across all reporting countries is 199.62 t, and the mean is 203,718 t.
Over the past decade 62 countries rose and 29 fell. The largest increase was in Kazakhstan (up 3,913,070.0%), and the largest decrease in Melanesia (down 100.0%).
Rape and Mustardseed — Export Quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Canada | 7.13 million t | 2013 | up 110.2% | volatile |
| 2 | Australia and New Zealand | 3.80 million t | 2013 | up 506.2% | volatile |
| 3 | Australia | 3.80 million t | 2013 | up 506.6% | volatile |
| 3 | Republic of Moldova | 45,108 t | 2013 | up 37,102.3% | volatile |
| 4 | Ukraine | 2.36 million t | 2013 | up 3,531.6% | volatile |
| 4 | United Republic of Tanzania | 496 t | 2013 | — | volatile |
| 5 | France | 1.36 million t | 2013 | down 22.2% | volatile |
| 5 | Iran (Islamic Republic of) | 1 t | 2013 | down 76.5% | volatile |
| 6 | Netherlands (Kingdom of the) | 1.14 million t | 2013 | up 1,761.6% | volatile |
| 6 | Melanesia | 0 t | 2013 | down 100.0% | volatile |
| 6 | Bolivia (Plurinational State of) | 0 t | 2013 | down 100.0% | volatile |
| 6 | Venezuela (Bolivarian Republic of) | 0 t | 2013 | down 100.0% | volatile |
| 7 | Poland | 768,732 t | 2013 | up 9,046.7% | volatile |
| 8 | Belgium | 753,285 t | 2013 | up 1,104.7% | volatile |
| 9 | Czechia | 526,456 t | 2013 | up 615.2% | volatile |
| 10 | Romania | 478,035 t | 2013 | up 7,525.7% | volatile |
| 11 | United Kingdom of Great Britain and Northern Ireland | 435,365 t | 2013 | up 58.6% | volatile |
| 12 | Hungary | 425,498 t | 2013 | up 519.8% | volatile |
| 13 | Slovakia | 384,947 t | 2013 | up 4,592.5% | volatile |
| 14 | Lithuania | 370,243 t | 2013 | up 255.7% | volatile |
| 15 | Bulgaria | 336,897 t | 2013 | up 5,290.6% | volatile |
| 16 | Latvia | 236,487 t | 2013 | up 1,874.5% | volatile |
| 17 | Germany | 163,349 t | 2013 | down 60.6% | volatile |
| 18 | Belgium-Luxembourg | 160,487 t | 1999 | up 2,229.4% | volatile |
| 19 | Denmark | 138,587 t | 2013 | up 145.9% | volatile |
| 20 | Russian Federation | 136,266 t | 2013 | up 98.1% | rising |
| 21 | Argentina | 129,200 t | 2013 | up 15,415.8% | volatile |
| 22 | Kazakhstan | 97,829 t | 2013 | up 3,913,070.0% | volatile |
| 23 | Austria | 85,257 t | 2013 | up 37.2% | volatile |
| 24 | Estonia | 60,244 t | 2013 | up 170.9% | volatile |
| 25 | Sweden | 39,191 t | 2013 | up 689.7% | volatile |
| 26 | India | 35,787 t | 2013 | down 33.5% | volatile |
| 27 | USSR | 29,800 t | 1991 | — | volatile |
| 27 | Caribbean | 243.75 t | 2013 | up 52.3% | volatile |
| 28 | Serbia | 24,853 t | 2013 | up 526.5% | volatile |
| 29 | Paraguay | 23,562 t | 2013 | up 945.3% | volatile |
| 30 | Spain | 20,672 t | 2013 | up 2,129.4% | volatile |
| 31 | Czechoslovakia | 20,300 t | 1992 | — | volatile |
| 32 | Mongolia | 19,294 t | 2013 | up 4,759.9% | volatile |
| 33 | Croatia | 19,050 t | 2013 | up 21.3% | volatile |
| 34 | Yugoslav SFR | 17,617 t | 1991 | up 79,078.5% | volatile |
| 35 | Ireland | 16,298 t | 2013 | up 48,191.1% | volatile |
| 36 | Luxembourg | 14,134 t | 2013 | up 139.4% | volatile |
| 37 | Slovenia | 12,961 t | 2013 | up 133.7% | volatile |
| 38 | Pakistan | 11,862 t | 2013 | up 931.4% | volatile |
| 39 | Chile | 10,351 t | 2013 | up 37,200.9% | volatile |
| 40 | North Macedonia | 4,411 t | 2013 | up 509.6% | volatile |
| 41 | Italy | 2,730 t | 2013 | up 42.6% | volatile |
| 42 | South Africa | 2,528 t | 2013 | up 2,617.6% | volatile |
| 43 | Guatemala | 2,299 t | 2013 | up 28.9% | volatile |
| 44 | New Zealand | 2,036 t | 2013 | up 181.6% | volatile |
| 45 | Senegal | 1,937 t | 2013 | up 2,770.0% | volatile |
| 46 | China, mainland | 1,669 t | 2013 | down 44.4% | volatile |
| 47 | Belarus | 978 t | 2013 | up 638.1% | volatile |
| 48 | Brazil | 749.63 t | 2013 | up 118.4% | volatile |
| 49 | Switzerland | 735.25 t | 2013 | down 3.3% | volatile |
| 50 | Serbia and Montenegro | 643.75 t | 2005 | — | volatile |
| 51 | Costa Rica | 640 t | 2013 | up 284.4% | volatile |
| 52 | Finland | 578.75 t | 2013 | up 172.0% | volatile |
| 53 | China, Hong Kong SAR | 562.5 t | 2013 | up 31.2% | volatile |
| 54 | Ethiopia | 458.25 t | 2013 | up 63.1% | volatile |
| 55 | United Arab Emirates | 404.75 t | 2013 | up 235.2% | volatile |
| 56 | El Salvador | 301.25 t | 2013 | down 44.8% | volatile |
| 57 | Malaysia | 261.63 t | 2013 | up 165.8% | volatile |
| 58 | Trinidad and Tobago | 243.75 t | 2013 | up 52.3% | volatile |
| 59 | Portugal | 230 t | 2013 | up 271.0% | volatile |
| 60 | Thailand | 220 t | 2013 | down 1.1% | volatile |
| 61 | China, Taiwan Province of | 179.25 t | 2013 | up 796.2% | volatile |
| 62 | Mexico | 156.25 t | 2013 | up 209.4% | volatile |
| 63 | Japan | 151.75 t | 2013 | down 89.2% | volatile |
| 64 | Republic of Korea | 150.5 t | 2013 | down 45.4% | volatile |
| 65 | Morocco | 132.5 t | 2013 | up 55.9% | volatile |
| 66 | Greece | 110 t | 2013 | up 378.3% | volatile |
| 67 | T�rkiye | 109.18 t | 2013 | up 133.2% | volatile |
| 68 | Egypt | 80.5 t | 2013 | down 36.6% | volatile |
| 69 | Norway | 76.09 t | 2013 | down 32.9% | volatile |
| 70 | Indonesia | 44 t | 2013 | down 84.6% | volatile |
| 71 | Georgia | 41 t | 2013 | up 228.0% | volatile |
| 72 | C�te d'Ivoire | 32.5 t | 2013 | — | volatile |
| 73 | Ecuador | 32.25 t | 2013 | — | volatile |
| 74 | Uganda | 30 t | 2013 | — | volatile |
| 75 | Lebanon | 26.5 t | 2013 | up 152.4% | volatile |
| 76 | Philippines | 22.5 t | 2013 | up 1,700.0% | volatile |
| 77 | Uruguay | 15 t | 2013 | up 1,100.0% | volatile |
| 78 | Colombia | 10 t | 2013 | down 71.0% | volatile |
| 79 | Peru | 8.75 t | 2013 | down 53.3% | volatile |
| 80 | Sri Lanka | 7.5 t | 2013 | up 76.5% | volatile |
| 81 | Myanmar | 5 t | 2013 | — | volatile |
| 82 | Israel | 4.18 t | 2013 | — | volatile |
| 83 | Tunisia | 2.5 t | 2013 | — | volatile |
| 84 | Honduras | 1.25 t | 2013 | — | volatile |
| 84 | Kenya | 1.25 t | 2013 | down 66.7% | volatile |
| 84 | Mauritius | 1.25 t | 2013 | — | volatile |
| 84 | Namibia | 1.25 t | 2013 | down 50.0% | volatile |
| 84 | Suriname | 1.25 t | 2013 | — | volatile |
| 89 | Albania | 0 t | 2013 | — | volatile |
| 89 | Azerbaijan | 0 t | 2013 | down 100.0% | volatile |
| 89 | Burkina Faso | 0 t | 2013 | — | volatile |
| 89 | Bangladesh | 0 t | 2013 | — | volatile |
| 89 | Bosnia and Herzegovina | 0 t | 2013 | — | volatile |
| 89 | Barbados | 0 t | 2013 | — | volatile |
| 89 | Botswana | 0 t | 2013 | down 100.0% | volatile |
| 89 | Central African Republic | 0 t | 2013 | — | volatile |
| 89 | Cameroon | 0 t | 2013 | down 100.0% | volatile |
| 89 | Cyprus | 0 t | 2013 | down 100.0% | volatile |
| 89 | Algeria | 0 t | 2013 | — | volatile |
| 89 | Fiji | 0 t | 2013 | down 100.0% | volatile |
| 89 | Guyana | 0 t | 2013 | — | volatile |
| 89 | Kyrgyzstan | 0 t | 2013 | — | volatile |
| 89 | Mali | 0 t | 2013 | — | volatile |
| 89 | Malta | 0 t | 2013 | — | volatile |
| 89 | Montenegro | 0 t | 2013 | — | volatile |
| 89 | Malawi | 0 t | 2013 | — | volatile |
| 89 | Niger | 0 t | 2013 | — | volatile |
| 89 | Nigeria | 0 t | 2013 | down 100.0% | volatile |
| 89 | Nicaragua | 0 t | 2013 | down 100.0% | volatile |
| 89 | Nepal | 0 t | 2013 | — | volatile |
| 89 | Oman | 0 t | 2013 | — | volatile |
| 89 | Panama | 0 t | 2013 | — | volatile |
| 89 | Saudi Arabia | 0 t | 2013 | down 100.0% | volatile |
| 89 | Eswatini | 0 t | 2013 | — | volatile |
| 89 | Zambia | 0 t | 2013 | — | volatile |
| 89 | Zimbabwe | 0 t | 2013 | down 100.0% | volatile |
| 89 | Sudan (former) | 0 t | 2011 | — | volatile |
| 89 | Ethiopia PDR | 0 t | 1992 | — | volatile |
| 89 | China, Macao SAR | 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 21.82 million t
- Land Locked Developing Countries 190,692 t
- Europe 10.37 million t
- Asia 168,632 t
- Americas 7.48 million t
- European Union (27) 7.35 million t
- Northern America 7.31 million t
- Eastern Europe 5.47 million t
- Middle Africa 0 t
- Oceania 3.80 million t
- Western Europe 3.52 million t
- Northern Europe 1.30 million t
- United States of America 176,787 t
- South America 163,930 t
- Central Asia 97,829 t
- Southern Europe 85,017 t
- Low Income Food Deficit Countries 50,604 t
- Southern Asia 47,657 t
- Net Food Importing Developing Countries 34,896 t
- Eastern Asia 22,007 t
- Africa 5,701 t
- Central America 3,398 t
- Least developed countries 2,926 t
- Southern Africa 2,529 t
- Western Africa 1,970 t
- Eastern Africa 986.75 t
- Western Asia 585.61 t
- South-Eastern Asia 553.13 t
- Small Island Developing States 246.25 t
- Northern Africa 215.5 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.