Cephalopods — Export 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
Cephalopods — Export quantity is currently reported for 148 countries. The highest value is 777 1000 t in China; the lowest is 0 1000 t in China, Macao SAR.
The median across all reporting countries is 0 1000 t, and the mean is 24.01 1000 t.
Over the past decade 29 countries rose and 19 fell. The largest increase was in Ecuador (up 1,800.0%), and the largest decrease in Algeria (down 100.0%).
Cephalopods — Export quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 777 1000 t | 2023 | up 28.9% | rising |
| 2 | China, mainland | 730 1000 t | 2023 | up 39.3% | rising |
| 3 | Peru | 480 1000 t | 2023 | up 9.6% | rising |
| 4 | Spain | 239 1000 t | 2023 | up 77.0% | rising |
| 5 | Indonesia | 172 1000 t | 2023 | up 112.3% | rising |
| 6 | India | 152 1000 t | 2023 | up 90.0% | rising |
| 7 | Argentina | 121 1000 t | 2023 | down 6.9% | rising |
| 8 | Morocco | 117 1000 t | 2023 | up 18.2% | rising |
| 9 | Viet Nam | 92 1000 t | 2023 | down 9.8% | falling |
| 10 | Thailand | 54 1000 t | 2023 | down 26.0% | falling |
| 11 | Mauritania | 49 1000 t | 2023 | up 58.1% | rising |
| 12 | China, Taiwan Province of | 46 1000 t | 2023 | up 43.8% | volatile |
| 13 | Chile | 43 1000 t | 2023 | down 36.8% | falling |
| 14 | Malaysia | 41 1000 t | 2023 | up 28.1% | flat |
| 15 | New Zealand | 40 1000 t | 2023 | up 66.7% | rising |
| 15 | Australia and New Zealand | 40 1000 t | 2023 | up 60.0% | rising |
| 17 | Myanmar | 35 1000 t | 2023 | up 250.0% | volatile |
| 18 | Democratic People's Republic of Korea | 31 1000 t | 2017 | — | volatile |
| 19 | Portugal | 25 1000 t | 2023 | down 21.9% | rising |
| 20 | Republic of Korea | 24 1000 t | 2023 | down 68.8% | volatile |
| 21 | Russian Federation | 23 1000 t | 2023 | up 130.0% | volatile |
| 22 | Ecuador | 19 1000 t | 2023 | up 1,800.0% | volatile |
| 22 | France | 19 1000 t | 2023 | unchanged | falling |
| 24 | Senegal | 17 1000 t | 2023 | up 142.9% | rising |
| 25 | Netherlands (Kingdom of the) | 15 1000 t | 2023 | up 150.0% | rising |
| 26 | Oman | 14 1000 t | 2023 | up 100.0% | rising |
| 26 | United Kingdom of Great Britain and Northern Ireland | 14 1000 t | 2023 | up 40.0% | rising |
| 28 | Italy | 13 1000 t | 2023 | up 44.4% | rising |
| 28 | Philippines | 13 1000 t | 2023 | up 116.7% | rising |
| 30 | Yemen | 9 1000 t | 2023 | down 47.1% | falling |
| 31 | Belgium | 8 1000 t | 2023 | up 14.3% | rising |
| 31 | Greece | 8 1000 t | 2023 | up 100.0% | rising |
| 31 | Mexico | 8 1000 t | 2023 | down 65.2% | volatile |
| 31 | Tunisia | 8 1000 t | 2023 | up 33.3% | falling |
| 35 | Ghana | 6 1000 t | 2023 | — | volatile |
| 36 | Canada | 5 1000 t | 2023 | — | volatile |
| 36 | Uruguay | 5 1000 t | 2023 | up 400.0% | volatile |
| 38 | Namibia | 4 1000 t | 2023 | down 20.0% | rising |
| 39 | Germany | 3 1000 t | 2023 | down 40.0% | flat |
| 39 | Denmark | 3 1000 t | 2023 | unchanged | rising |
| 39 | Iran (Islamic Republic of) | 3 1000 t | 2023 | unchanged | rising |
| 42 | Belarus | 2 1000 t | 2023 | up 100.0% | volatile |
| 42 | Gambia | 2 1000 t | 2023 | — | volatile |
| 42 | Croatia | 2 1000 t | 2023 | up 100.0% | rising |
| 42 | Sri Lanka | 2 1000 t | 2023 | unchanged | rising |
| 42 | Madagascar | 2 1000 t | 2023 | up 100.0% | rising |
| 42 | China, Hong Kong SAR | 2 1000 t | 2023 | down 95.7% | volatile |
| 42 | Türkiye | 2 1000 t | 2023 | up 100.0% | rising |
| 49 | Albania | 1 1000 t | 2023 | unchanged | flat |
| 49 | United Arab Emirates | 1 1000 t | 2023 | down 93.8% | volatile |
| 49 | Bangladesh | 1 1000 t | 2023 | unchanged | rising |
| 49 | Bahrain | 1 1000 t | 2023 | — | flat |
| 49 | Brazil | 1 1000 t | 2023 | — | volatile |
| 49 | Guinea | 1 1000 t | 2023 | — | volatile |
| 49 | Ireland | 1 1000 t | 2023 | — | volatile |
| 49 | Iceland | 1 1000 t | 2023 | — | volatile |
| 49 | Kenya | 1 1000 t | 2023 | — | rising |
| 49 | Mozambique | 1 1000 t | 2023 | — | volatile |
| 49 | Pakistan | 1 1000 t | 2023 | down 50.0% | volatile |
| 49 | Saudi Arabia | 1 1000 t | 2023 | — | volatile |
| 49 | Slovenia | 1 1000 t | 2023 | — | volatile |
| 49 | Côte d'Ivoire | 1 1000 t | 2023 | — | volatile |
| 49 | United Republic of Tanzania | 1 1000 t | 2023 | unchanged | falling |
| 64 | Angola | 0 1000 t | 2023 | — | volatile |
| 64 | Armenia | 0 1000 t | 2017 | — | flat |
| 64 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 64 | Australia | 0 1000 t | 2023 | — | volatile |
| 64 | Austria | 0 1000 t | 2023 | — | flat |
| 64 | Bulgaria | 0 1000 t | 2023 | — | flat |
| 64 | Bahamas | 0 1000 t | 2023 | — | flat |
| 64 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 64 | Belize | 0 1000 t | 2023 | — | flat |
| 64 | Barbados | 0 1000 t | 2023 | — | flat |
| 64 | Botswana | 0 1000 t | 2023 | — | flat |
| 64 | Switzerland | 0 1000 t | 2023 | — | flat |
| 64 | Congo | 0 1000 t | 2020 | — | flat |
| 64 | Colombia | 0 1000 t | 2020 | — | flat |
| 64 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 64 | Cuba | 0 1000 t | 2018 | — | flat |
| 64 | Cyprus | 0 1000 t | 2023 | — | flat |
| 64 | Czechia | 0 1000 t | 2023 | — | flat |
| 64 | Djibouti | 0 1000 t | 2023 | — | flat |
| 64 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 64 | Algeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 64 | Egypt | 0 1000 t | 2023 | down 100.0% | volatile |
| 64 | Estonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 64 | Finland | 0 1000 t | 2023 | — | flat |
| 64 | Fiji | 0 1000 t | 2023 | — | flat |
| 64 | Gabon | 0 1000 t | 2018 | — | flat |
| 64 | Georgia | 0 1000 t | 2018 | — | flat |
| 64 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 64 | Guatemala | 0 1000 t | 2017 | — | flat |
| 64 | Guyana | 0 1000 t | 2023 | — | flat |
| 64 | Honduras | 0 1000 t | 2023 | — | flat |
| 64 | Haiti | 0 1000 t | 2023 | — | flat |
| 64 | Hungary | 0 1000 t | 2023 | — | flat |
| 64 | Jamaica | 0 1000 t | 2023 | — | flat |
| 64 | Jordan | 0 1000 t | 2017 | — | flat |
| 64 | Kazakhstan | 0 1000 t | 2023 | — | flat |
| 64 | Cambodia | 0 1000 t | 2023 | — | flat |
| 64 | Kiribati | 0 1000 t | 2023 | — | flat |
| 64 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 64 | Kuwait | 0 1000 t | 2023 | — | flat |
| 64 | Lebanon | 0 1000 t | 2023 | — | flat |
| 64 | Liberia | 0 1000 t | 2018 | — | flat |
| 64 | Libya | 0 1000 t | 2023 | — | flat |
| 64 | Lithuania | 0 1000 t | 2023 | — | flat |
| 64 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 64 | Latvia | 0 1000 t | 2023 | — | flat |
| 64 | Maldives | 0 1000 t | 2023 | — | flat |
| 64 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 64 | Malta | 0 1000 t | 2020 | — | flat |
| 64 | Montenegro | 0 1000 t | 2023 | — | flat |
| 64 | Mongolia | 0 1000 t | 2023 | — | flat |
| 64 | Mauritius | 0 1000 t | 2023 | — | flat |
| 64 | New Caledonia | 0 1000 t | 2019 | — | flat |
| 64 | Nigeria | 0 1000 t | 2018 | — | flat |
| 64 | Nicaragua | 0 1000 t | 2023 | — | flat |
| 64 | Norway | 0 1000 t | 2023 | — | flat |
| 64 | Panama | 0 1000 t | 2023 | — | volatile |
| 64 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 64 | Poland | 0 1000 t | 2023 | down 100.0% | volatile |
| 64 | French Polynesia | 0 1000 t | 2019 | — | flat |
| 64 | Qatar | 0 1000 t | 2023 | — | flat |
| 64 | Romania | 0 1000 t | 2023 | — | volatile |
| 64 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 64 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 64 | El Salvador | 0 1000 t | 2023 | — | flat |
| 64 | Serbia | 0 1000 t | 2023 | — | flat |
| 64 | Sao Tome and Principe | 0 1000 t | 2020 | — | flat |
| 64 | Suriname | 0 1000 t | 2018 | — | flat |
| 64 | Slovakia | 0 1000 t | 2023 | — | flat |
| 64 | Sweden | 0 1000 t | 2023 | — | flat |
| 64 | Seychelles | 0 1000 t | 2023 | — | flat |
| 64 | Tonga | 0 1000 t | 2023 | — | flat |
| 64 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 64 | Ukraine | 0 1000 t | 2023 | — | flat |
| 64 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 64 | Vanuatu | 0 1000 t | 2023 | down 100.0% | volatile |
| 64 | Samoa | 0 1000 t | 2023 | — | flat |
| 64 | Zambia | 0 1000 t | 2017 | — | flat |
| 64 | Micronesia | 0 1000 t | 2023 | — | flat |
| 64 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 64 | Melanesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 64 | Polynesia | 0 1000 t | 2023 | — | flat |
| 64 | Caribbean | 0 1000 t | 2023 | — | flat |
| 64 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 64 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 2,774 1000 t
- Asia 1,401 1000 t
- Eastern Asia 808 1000 t
- Americas 736 1000 t
- Net Food Importing Developing Countries (NFIDCs) 730 1000 t
- South America 668 1000 t
- South-eastern Asia 406 1000 t
- Europe 379 1000 t
- European Union (27) 337 1000 t
- Southern Europe 289 1000 t
- Africa 218 1000 t
- Southern Asia 159 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.