Soft-Fibres, Other — 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
Soft-Fibres, Other — Import Quantity is currently reported for 146 countries. The highest value is 140,737 t in China, mainland; the lowest is 0 t in China, Macao SAR.
The median across all reporting countries is 11.5 t, and the mean is 3,380 t.
Over the past decade 28 countries rose and 60 fell. The largest increase was in Australia and New Zealand (up 13,550.0%), and the largest decrease in Viet Nam (down 100.0%).
Soft-Fibres, Other — Import Quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China, mainland | 140,737 t | 2013 | up 34.5% | volatile |
| 2 | Belgium-Luxembourg | 121,275 t | 1999 | down 6.5% | falling |
| 3 | Belgium | 105,754 t | 2013 | down 30.1% | falling |
| 3 | Iran (Islamic Republic of) | 55 t | 2013 | — | volatile |
| 4 | France | 18,064 t | 2013 | down 57.6% | flat |
| 5 | Netherlands (Kingdom of the) | 13,508 t | 2013 | up 186.4% | volatile |
| 5 | Republic of Moldova | 7 t | 2013 | up 600.0% | volatile |
| 6 | Spain | 10,115 t | 2013 | down 42.6% | rising |
| 6 | Melanesia | 6 t | 2013 | — | volatile |
| 7 | Lithuania | 9,834 t | 2013 | down 42.7% | volatile |
| 7 | Venezuela (Bolivarian Republic of) | 4 t | 2013 | — | volatile |
| 8 | Czechia | 9,467 t | 2013 | down 5.9% | rising |
| 8 | Bolivia (Plurinational State of) | 3 t | 2013 | up 200.0% | volatile |
| 9 | USSR | 8,400 t | 1991 | — | volatile |
| 9 | United Republic of Tanzania | 1 t | 2013 | — | volatile |
| 10 | Russian Federation | 7,720 t | 2013 | down 16.5% | volatile |
| 10 | Polynesia | 0 t | 2013 | — | volatile |
| 10 | Viet Nam | 0 t | 2013 | down 100.0% | volatile |
| 11 | Germany | 7,491 t | 2013 | down 32.3% | volatile |
| 12 | India | 7,038 t | 2013 | up 173.7% | volatile |
| 13 | Japan | 6,972 t | 2013 | down 52.0% | falling |
| 14 | Poland | 6,470 t | 2013 | down 23.7% | falling |
| 15 | Tunisia | 2,377 t | 2013 | up 55.8% | volatile |
| 16 | T�rkiye | 2,216 t | 2013 | up 47.5% | volatile |
| 17 | Czechoslovakia | 2,150 t | 1992 | down 73.1% | falling |
| 18 | Italy | 1,996 t | 2013 | down 87.9% | falling |
| 19 | Hungary | 1,387 t | 2013 | down 28.4% | volatile |
| 20 | Romania | 1,068 t | 2013 | down 36.3% | volatile |
| 21 | Yugoslav SFR | 1,000 t | 1991 | down 68.7% | volatile |
| 22 | Egypt | 802 t | 2013 | up 854.8% | volatile |
| 23 | Slovenia | 764 t | 2013 | up 58.5% | volatile |
| 24 | Brazil | 743 t | 2013 | up 13.3% | volatile |
| 25 | Latvia | 638 t | 2013 | down 65.1% | volatile |
| 26 | Switzerland | 548 t | 2013 | up 17.1% | volatile |
| 27 | Canada | 466 t | 2013 | down 58.9% | volatile |
| 27 | Caribbean | 12 t | 2013 | up 300.0% | volatile |
| 28 | South Africa | 310 t | 2013 | down 64.8% | volatile |
| 29 | China, Taiwan Province of | 305 t | 2013 | down 82.6% | volatile |
| 30 | Denmark | 304 t | 2013 | up 44.8% | volatile |
| 31 | Australia and New Zealand | 273 t | 2013 | up 13,550.0% | volatile |
| 32 | Australia | 258 t | 2013 | up 12,800.0% | volatile |
| 33 | Belarus | 234 t | 2013 | down 93.7% | volatile |
| 34 | United Kingdom of Great Britain and Northern Ireland | 213 t | 2013 | down 93.4% | volatile |
| 35 | United Arab Emirates | 195 t | 2013 | — | volatile |
| 36 | Portugal | 184 t | 2013 | up 27.8% | volatile |
| 37 | Thailand | 177 t | 2013 | up 45.1% | volatile |
| 38 | Greece | 154 t | 2013 | down 44.4% | volatile |
| 39 | Ethiopia PDR | 150 t | 1992 | — | volatile |
| 40 | Ukraine | 134 t | 2013 | — | volatile |
| 41 | Saudi Arabia | 122 t | 2013 | down 81.9% | volatile |
| 42 | Philippines | 90 t | 2013 | — | volatile |
| 43 | Malaysia | 87 t | 2013 | down 91.3% | volatile |
| 44 | Austria | 82 t | 2013 | down 98.2% | falling |
| 45 | Morocco | 78 t | 2013 | up 25.8% | volatile |
| 46 | Serbia and Montenegro | 70 t | 2005 | — | volatile |
| 47 | Pakistan | 68 t | 2013 | up 78.9% | volatile |
| 48 | C�te d'Ivoire | 67 t | 2013 | up 1,240.0% | volatile |
| 49 | Argentina | 62 t | 2013 | up 26.5% | volatile |
| 50 | Israel | 61 t | 2013 | up 60.5% | volatile |
| 50 | Kazakhstan | 61 t | 2013 | — | volatile |
| 52 | Chile | 56 t | 2013 | down 72.4% | volatile |
| 53 | Republic of Korea | 42 t | 2013 | down 93.9% | volatile |
| 54 | Congo | 38 t | 2013 | — | volatile |
| 55 | Indonesia | 36 t | 2013 | down 90.7% | volatile |
| 56 | Sweden | 30 t | 2013 | down 50.0% | volatile |
| 57 | Nigeria | 28 t | 2013 | — | volatile |
| 58 | Slovakia | 27 t | 2013 | down 97.4% | volatile |
| 59 | Botswana | 24 t | 2013 | down 33.3% | volatile |
| 59 | Ethiopia | 24 t | 2013 | up 100.0% | volatile |
| 59 | Jordan | 24 t | 2013 | down 33.3% | volatile |
| 62 | Estonia | 23 t | 2013 | down 99.1% | volatile |
| 62 | Lebanon | 23 t | 2013 | up 27.8% | volatile |
| 64 | Serbia | 22 t | 2013 | down 81.2% | volatile |
| 65 | Finland | 18 t | 2013 | down 96.5% | volatile |
| 66 | Bulgaria | 15 t | 2013 | down 93.1% | volatile |
| 66 | Norway | 15 t | 2013 | down 21.1% | volatile |
| 66 | New Zealand | 15 t | 2013 | — | volatile |
| 69 | Oman | 14 t | 2013 | unchanged | volatile |
| 70 | Ireland | 13 t | 2013 | down 27.8% | volatile |
| 71 | Jamaica | 12 t | 2013 | — | volatile |
| 72 | Algeria | 11 t | 2013 | down 47.6% | volatile |
| 72 | Gabon | 11 t | 2013 | — | volatile |
| 74 | Iceland | 9 t | 2013 | up 50.0% | volatile |
| 74 | Sri Lanka | 9 t | 2013 | up 125.0% | volatile |
| 74 | Nepal | 9 t | 2013 | down 97.7% | volatile |
| 77 | Bosnia and Herzegovina | 8 t | 2013 | down 27.3% | volatile |
| 77 | Peru | 8 t | 2013 | down 20.0% | volatile |
| 79 | Croatia | 7 t | 2013 | down 82.9% | volatile |
| 79 | Zambia | 7 t | 2013 | — | volatile |
| 81 | New Caledonia | 6 t | 2013 | — | volatile |
| 82 | Cameroon | 4 t | 2013 | up 100.0% | volatile |
| 83 | Albania | 3 t | 2013 | up 200.0% | volatile |
| 83 | Mexico | 3 t | 2013 | down 96.6% | volatile |
| 83 | North Macedonia | 3 t | 2013 | unchanged | volatile |
| 86 | Georgia | 2 t | 2013 | — | volatile |
| 86 | Kuwait | 2 t | 2013 | — | volatile |
| 86 | Luxembourg | 2 t | 2013 | down 60.0% | volatile |
| 86 | Niger | 2 t | 2013 | — | volatile |
| 86 | Rwanda | 2 t | 2013 | — | volatile |
| 86 | Senegal | 2 t | 2013 | down 60.0% | volatile |
| 86 | Uruguay | 2 t | 2013 | down 84.6% | volatile |
| 93 | Angola | 1 t | 2013 | — | volatile |
| 93 | Guatemala | 1 t | 2013 | — | volatile |
| 93 | Honduras | 1 t | 2013 | unchanged | volatile |
| 93 | Iraq | 1 t | 2013 | — | volatile |
| 93 | Madagascar | 1 t | 2013 | — | volatile |
| 93 | Mongolia | 1 t | 2013 | down 88.9% | volatile |
| 93 | Mozambique | 1 t | 2013 | — | volatile |
| 93 | Eswatini | 1 t | 2013 | down 83.3% | volatile |
| 101 | Azerbaijan | 0 t | 2013 | — | volatile |
| 101 | Benin | 0 t | 2013 | — | volatile |
| 101 | Bangladesh | 0 t | 2013 | — | volatile |
| 101 | Barbados | 0 t | 2013 | down 100.0% | volatile |
| 101 | Colombia | 0 t | 2013 | down 100.0% | volatile |
| 101 | Costa Rica | 0 t | 2013 | — | volatile |
| 101 | Cyprus | 0 t | 2013 | down 100.0% | volatile |
| 101 | Djibouti | 0 t | 2013 | — | volatile |
| 101 | Dominican Republic | 0 t | 2013 | — | volatile |
| 101 | Ecuador | 0 t | 2013 | — | volatile |
| 101 | Fiji | 0 t | 2013 | — | volatile |
| 101 | Ghana | 0 t | 2013 | down 100.0% | volatile |
| 101 | Gambia | 0 t | 2013 | down 100.0% | volatile |
| 101 | Grenada | 0 t | 2013 | — | volatile |
| 101 | Guyana | 0 t | 2013 | — | volatile |
| 101 | Haiti | 0 t | 2013 | — | volatile |
| 101 | Kenya | 0 t | 2013 | — | volatile |
| 101 | Kyrgyzstan | 0 t | 2013 | — | volatile |
| 101 | Malta | 0 t | 2013 | down 100.0% | volatile |
| 101 | Myanmar | 0 t | 2013 | — | volatile |
| 101 | Mauritania | 0 t | 2013 | — | volatile |
| 101 | Mauritius | 0 t | 2013 | — | volatile |
| 101 | Namibia | 0 t | 2013 | down 100.0% | volatile |
| 101 | Nicaragua | 0 t | 2013 | — | volatile |
| 101 | Panama | 0 t | 2013 | — | volatile |
| 101 | Paraguay | 0 t | 2013 | — | volatile |
| 101 | French Polynesia | 0 t | 2013 | — | volatile |
| 101 | El Salvador | 0 t | 2013 | down 100.0% | volatile |
| 101 | Suriname | 0 t | 2013 | — | volatile |
| 101 | Togo | 0 t | 2013 | — | volatile |
| 101 | Turkmenistan | 0 t | 2013 | — | volatile |
| 101 | Trinidad and Tobago | 0 t | 2013 | — | volatile |
| 101 | Uganda | 0 t | 2013 | — | volatile |
| 101 | Yemen | 0 t | 2013 | down 100.0% | volatile |
| 101 | Zimbabwe | 0 t | 2013 | — | volatile |
| 101 | China, Hong Kong SAR | 0 t | 2013 | down 100.0% | volatile |
| 101 | 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 376,430 t
- Asia 158,347 t
- Europe 196,331 t
- Land Locked Developing Countries 144 t
- European Union (27) 187,415 t
- Eastern Asia 148,057 t
- Middle Africa 54 t
- Western Europe 145,449 t
- Eastern Europe 26,529 t
- Americas 17,623 t
- Northern America 16,728 t
- United States of America 16,262 t
- Southern Europe 13,256 t
- Northern Europe 11,097 t
- Low Income Food Deficit Countries 7,305 t
- Southern Asia 7,179 t
- Africa 3,850 t
- Net Food Importing Developing Countries 3,595 t
- Northern Africa 3,326 t
- Western Asia 2,660 t
- South America 878 t
- South-Eastern Asia 390 t
- Southern Africa 335 t
- Oceania 279 t
- Least developed countries 108 t
- Western Africa 99 t
- Central Asia 61 t
- Eastern Africa 36 t
- Small Island Developing States 18 t
- Central America 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.