Silk — 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
Silk — Import Quantity is currently reported for 106 countries. The highest value is 3,767 t in India; the lowest is 0 t in China, Macao SAR.
The median across all reporting countries is 2 t, and the mean is 137.06 t.
Over the past decade 17 countries rose and 43 fell. The largest increase was in Brazil (up 1,214.3%), and the largest decrease in Belize (down 100.0%).
Silk — Import Quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 3,767 t | 2013 | down 60.5% | volatile |
| 2 | China, mainland | 2,647 t | 2013 | down 41.4% | volatile |
| 2 | Viet Nam | 635 t | 2013 | up 31.2% | volatile |
| 3 | Italy | 1,602 t | 2013 | down 56.5% | falling |
| 3 | Iran (Islamic Republic of) | 219 t | 2013 | up 397.7% | volatile |
| 4 | Romania | 1,382 t | 2013 | up 161.7% | volatile |
| 5 | Japan | 766 t | 2013 | down 73.1% | volatile |
| 5 | Venezuela (Bolivarian Republic of) | 1 t | 2013 | — | volatile |
| 5 | United Republic of Tanzania | 1 t | 2013 | — | volatile |
| 6 | Germany | 605 t | 2013 | down 63.2% | volatile |
| 7 | USSR | 450 t | 1991 | down 55.2% | volatile |
| 7 | Bolivia (Plurinational State of) | 0 t | 2013 | — | volatile |
| 7 | Democratic People's Republic of Korea | 0 t | 2013 | — | volatile |
| 8 | Republic of Korea | 438 t | 2013 | down 74.3% | volatile |
| 9 | France | 287 t | 2013 | down 8.0% | falling |
| 10 | Thailand | 234 t | 2013 | down 64.2% | volatile |
| 11 | Bangladesh | 223 t | 2013 | up 19.3% | volatile |
| 12 | Nigeria | 182 t | 2013 | — | volatile |
| 13 | United Kingdom of Great Britain and Northern Ireland | 118 t | 2013 | down 24.8% | volatile |
| 14 | Netherlands (Kingdom of the) | 117 t | 2013 | up 1,200.0% | volatile |
| 15 | Myanmar | 99 t | 2013 | up 22.2% | volatile |
| 16 | Brazil | 92 t | 2013 | up 1,214.3% | volatile |
| 17 | T�rkiye | 88 t | 2013 | down 52.2% | volatile |
| 18 | United Arab Emirates | 70 t | 2013 | — | volatile |
| 19 | Bulgaria | 66 t | 2013 | up 34.7% | volatile |
| 20 | Tunisia | 54 t | 2013 | up 8.0% | volatile |
| 21 | Azerbaijan | 47 t | 2013 | down 88.2% | volatile |
| 22 | Peru | 39 t | 2013 | up 129.4% | volatile |
| 23 | Switzerland | 32 t | 2013 | down 84.7% | volatile |
| 24 | Philippines | 25 t | 2013 | up 400.0% | volatile |
| 25 | Pakistan | 24 t | 2013 | down 59.3% | volatile |
| 25 | Caribbean | 3 t | 2013 | — | volatile |
| 26 | Austria | 23 t | 2013 | up 9.5% | volatile |
| 27 | Zambia | 17 t | 2013 | — | volatile |
| 28 | Belgium-Luxembourg | 15 t | 1999 | down 78.6% | volatile |
| 29 | Czechia | 13 t | 2013 | — | volatile |
| 30 | Mexico | 12 t | 2013 | up 500.0% | volatile |
| 30 | Portugal | 12 t | 2013 | up 500.0% | volatile |
| 32 | Malaysia | 11 t | 2013 | down 31.2% | volatile |
| 32 | Nepal | 11 t | 2013 | down 95.0% | volatile |
| 32 | China, Taiwan Province of | 11 t | 2013 | down 21.4% | volatile |
| 35 | Canada | 9 t | 2013 | down 59.1% | volatile |
| 36 | Lithuania | 8 t | 2013 | — | volatile |
| 36 | Slovenia | 8 t | 2013 | up 166.7% | volatile |
| 38 | Australia and New Zealand | 6 t | 2013 | down 45.5% | volatile |
| 39 | Belgium | 5 t | 2013 | down 80.0% | volatile |
| 39 | Egypt | 5 t | 2013 | down 98.8% | volatile |
| 39 | Ethiopia | 5 t | 2013 | — | volatile |
| 39 | Cambodia | 5 t | 2013 | up 400.0% | volatile |
| 39 | New Zealand | 5 t | 2013 | up 66.7% | volatile |
| 44 | Spain | 4 t | 2013 | down 97.4% | volatile |
| 44 | Poland | 4 t | 2013 | unchanged | volatile |
| 46 | Dominican Republic | 3 t | 2013 | — | volatile |
| 46 | Hungary | 3 t | 2013 | — | volatile |
| 46 | Oman | 3 t | 2013 | — | volatile |
| 46 | China, Hong Kong SAR | 3 t | 2013 | down 96.6% | volatile |
| 50 | Denmark | 2 t | 2013 | down 96.2% | volatile |
| 50 | Malta | 2 t | 2013 | down 96.6% | volatile |
| 50 | Saudi Arabia | 2 t | 2013 | down 75.0% | volatile |
| 50 | Uruguay | 2 t | 2013 | down 98.7% | volatile |
| 54 | Australia | 1 t | 2013 | down 87.5% | volatile |
| 54 | Bosnia and Herzegovina | 1 t | 2013 | unchanged | volatile |
| 54 | Indonesia | 1 t | 2013 | down 98.2% | volatile |
| 54 | Ireland | 1 t | 2013 | down 83.3% | volatile |
| 54 | Eswatini | 1 t | 2013 | down 93.3% | volatile |
| 54 | South Africa | 1 t | 2013 | down 97.1% | volatile |
| 60 | Albania | 0 t | 2013 | — | volatile |
| 60 | Argentina | 0 t | 2013 | — | volatile |
| 60 | Bahamas | 0 t | 2013 | — | volatile |
| 60 | Belize | 0 t | 2013 | down 100.0% | volatile |
| 60 | Botswana | 0 t | 2013 | down 100.0% | volatile |
| 60 | Chile | 0 t | 2013 | — | volatile |
| 60 | Colombia | 0 t | 2013 | — | volatile |
| 60 | Cyprus | 0 t | 2013 | — | volatile |
| 60 | Ecuador | 0 t | 2013 | — | volatile |
| 60 | Estonia | 0 t | 2013 | down 100.0% | volatile |
| 60 | Finland | 0 t | 2013 | — | volatile |
| 60 | Greece | 0 t | 2013 | down 100.0% | volatile |
| 60 | Guatemala | 0 t | 2013 | down 100.0% | volatile |
| 60 | Guyana | 0 t | 2013 | — | volatile |
| 60 | Honduras | 0 t | 2013 | — | volatile |
| 60 | Croatia | 0 t | 2013 | — | volatile |
| 60 | Iraq | 0 t | 2013 | — | volatile |
| 60 | Israel | 0 t | 2013 | — | volatile |
| 60 | Kazakhstan | 0 t | 2013 | — | volatile |
| 60 | Kyrgyzstan | 0 t | 2013 | — | volatile |
| 60 | Lebanon | 0 t | 2013 | — | volatile |
| 60 | Sri Lanka | 0 t | 2013 | — | volatile |
| 60 | Luxembourg | 0 t | 2013 | — | volatile |
| 60 | Morocco | 0 t | 2013 | — | volatile |
| 60 | Madagascar | 0 t | 2013 | — | volatile |
| 60 | North Macedonia | 0 t | 2013 | — | volatile |
| 60 | Mauritius | 0 t | 2013 | — | volatile |
| 60 | Malawi | 0 t | 2013 | — | volatile |
| 60 | Namibia | 0 t | 2013 | down 100.0% | volatile |
| 60 | Nicaragua | 0 t | 2013 | — | volatile |
| 60 | Norway | 0 t | 2013 | — | volatile |
| 60 | Paraguay | 0 t | 2013 | down 100.0% | volatile |
| 60 | El Salvador | 0 t | 2013 | down 100.0% | volatile |
| 60 | Sweden | 0 t | 2013 | — | volatile |
| 60 | Yemen | 0 t | 2013 | — | volatile |
| 60 | Russian Federation | 0 t | 2013 | — | volatile |
| 60 | Brunei Darussalam | 0 t | 2013 | down 100.0% | volatile |
| 60 | Ethiopia PDR | 0 t | 1992 | — | volatile |
| 60 | Yugoslav SFR | 0 t | 1991 | down 100.0% | volatile |
| 60 | 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 14,077 t
- Asia 9,329 t
- Europe 4,295 t
- Southern Asia 4,244 t
- Low Income Food Deficit Countries 4,213 t
- Land Locked Developing Countries 81 t
- European Union (27) 4,144 t
- Eastern Asia 3,865 t
- Southern Europe 1,629 t
- Eastern Europe 1,468 t
- Western Europe 1,069 t
- South-Eastern Asia 1,010 t
- Net Food Importing Developing Countries 488 t
- Least developed countries 361 t
- Africa 266 t
- Western Asia 210 t
- Western Africa 182 t
- Americas 181 t
- South America 134 t
- Northern Europe 129 t
- Northern Africa 59 t
- Northern America 32 t
- Eastern Africa 23 t
- United States of America 23 t
- Central America 12 t
- Oceania 6 t
- Small Island Developing States 3 t
- Southern Africa 2 t
- Central Asia 0 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.