Aquatic Animals, Others — Domestic supply 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
Aquatic Animals, Others — Domestic supply quantity is currently reported for 154 countries. The highest value is 1,400 1000 t in China (People’s Republic of); the lowest is 0 1000 t in Netherlands (Kingdom of the).
The median across all reporting countries is 0 1000 t, and the mean is 19.49 1000 t.
Over the past decade 10 countries rose and 15 fell. The largest increase was in Russian Federation (up 1,200.0%), and the largest decrease in Belgium (down 100.0%).
Aquatic Animals, Others — Domestic supply quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China (People’s Republic of) | 1,400 1000 t | 2023 | up 48.1% | rising |
| 2 | China, mainland | 1,382 1000 t | 2023 | up 48.8% | rising |
| 3 | Republic of Korea | 38 1000 t | 2023 | up 11.8% | falling |
| 4 | Chile | 32 1000 t | 2023 | up 33.3% | rising |
| 5 | Indonesia | 29 1000 t | 2023 | up 262.5% | volatile |
| 6 | Saudi Arabia | 21 1000 t | 2023 | — | volatile |
| 7 | Malaysia | 15 1000 t | 2023 | up 87.5% | rising |
| 8 | Russian Federation | 13 1000 t | 2023 | up 1,200.0% | volatile |
| 9 | Mexico | 12 1000 t | 2023 | down 50.0% | volatile |
| 10 | Canada | 9 1000 t | 2023 | up 28.6% | rising |
| 10 | China, Taiwan Province of | 9 1000 t | 2023 | down 25.0% | falling |
| 12 | China, Hong Kong SAR | 8 1000 t | 2023 | up 166.7% | rising |
| 13 | Nicaragua | 4 1000 t | 2023 | — | volatile |
| 14 | Sri Lanka | 3 1000 t | 2023 | unchanged | volatile |
| 14 | Thailand | 3 1000 t | 2023 | down 97.5% | volatile |
| 14 | Australia and New Zealand | 3 1000 t | 2023 | down 57.1% | volatile |
| 17 | Australia | 2 1000 t | 2023 | down 66.7% | volatile |
| 17 | Myanmar | 2 1000 t | 2023 | down 60.0% | volatile |
| 17 | Pakistan | 2 1000 t | 2023 | up 100.0% | rising |
| 20 | Bulgaria | 1 1000 t | 2023 | — | volatile |
| 20 | Switzerland | 1 1000 t | 2023 | — | volatile |
| 20 | Germany | 1 1000 t | 2023 | — | volatile |
| 20 | Spain | 1 1000 t | 2023 | down 50.0% | volatile |
| 20 | France | 1 1000 t | 2023 | down 75.0% | volatile |
| 20 | Iceland | 1 1000 t | 2023 | unchanged | falling |
| 20 | Italy | 1 1000 t | 2023 | unchanged | falling |
| 20 | Madagascar | 1 1000 t | 2023 | down 66.7% | volatile |
| 20 | New Zealand | 1 1000 t | 2023 | unchanged | flat |
| 20 | Peru | 1 1000 t | 2023 | — | volatile |
| 20 | Philippines | 1 1000 t | 2023 | unchanged | volatile |
| 20 | Samoa | 1 1000 t | 2023 | unchanged | flat |
| 20 | United Kingdom of Great Britain and Northern Ireland | 1 1000 t | 2023 | unchanged | volatile |
| 20 | China, Macao SAR | 1 1000 t | 2023 | — | volatile |
| 34 | Angola | 0 1000 t | 2023 | — | flat |
| 34 | Albania | 0 1000 t | 2023 | — | flat |
| 34 | United Arab Emirates | 0 1000 t | 2023 | — | flat |
| 34 | Argentina | 0 1000 t | 2023 | — | flat |
| 34 | Armenia | 0 1000 t | 2023 | — | flat |
| 34 | Austria | 0 1000 t | 2023 | — | volatile |
| 34 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 34 | Belgium | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 34 | Bangladesh | 0 1000 t | 2023 | — | flat |
| 34 | Bahrain | 0 1000 t | 2023 | — | flat |
| 34 | Bahamas | 0 1000 t | 2023 | — | flat |
| 34 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 34 | Belarus | 0 1000 t | 2023 | — | flat |
| 34 | Belize | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Brazil | 0 1000 t | 2023 | — | volatile |
| 34 | Barbados | 0 1000 t | 2023 | — | flat |
| 34 | Botswana | 0 1000 t | 2023 | — | flat |
| 34 | Cameroon | 0 1000 t | 2023 | — | flat |
| 34 | Congo | 0 1000 t | 2023 | — | flat |
| 34 | Colombia | 0 1000 t | 2023 | — | flat |
| 34 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 34 | Cuba | 0 1000 t | 2019 | — | flat |
| 34 | Cyprus | 0 1000 t | 2023 | — | flat |
| 34 | Czechia | 0 1000 t | 2023 | — | volatile |
| 34 | Djibouti | 0 1000 t | 2023 | — | flat |
| 34 | Denmark | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 34 | Algeria | 0 1000 t | 2023 | — | flat |
| 34 | Ecuador | 0 1000 t | 2023 | — | volatile |
| 34 | Egypt | 0 1000 t | 2023 | — | flat |
| 34 | Estonia | 0 1000 t | 2023 | — | volatile |
| 34 | Ethiopia | 0 1000 t | 2023 | — | flat |
| 34 | Finland | 0 1000 t | 2023 | — | flat |
| 34 | Fiji | 0 1000 t | 2023 | — | flat |
| 34 | Gabon | 0 1000 t | 2023 | — | flat |
| 34 | Georgia | 0 1000 t | 2023 | — | flat |
| 34 | Ghana | 0 1000 t | 2023 | — | flat |
| 34 | Guinea | 0 1000 t | 2023 | — | flat |
| 34 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 34 | Greece | 0 1000 t | 2023 | — | flat |
| 34 | Grenada | 0 1000 t | 2023 | — | flat |
| 34 | Guatemala | 0 1000 t | 2023 | — | flat |
| 34 | Guyana | 0 1000 t | 2023 | — | flat |
| 34 | Honduras | 0 1000 t | 2023 | — | volatile |
| 34 | Croatia | 0 1000 t | 2023 | — | flat |
| 34 | Haiti | 0 1000 t | 2023 | — | flat |
| 34 | Hungary | 0 1000 t | 2023 | — | flat |
| 34 | India | 0 1000 t | 2023 | — | flat |
| 34 | Ireland | 0 1000 t | 2023 | — | flat |
| 34 | Iraq | 0 1000 t | 2023 | — | flat |
| 34 | Israel | 0 1000 t | 2023 | — | flat |
| 34 | Jamaica | 0 1000 t | 2023 | — | flat |
| 34 | Jordan | 0 1000 t | 2023 | — | flat |
| 34 | Kazakhstan | 0 1000 t | 2023 | — | flat |
| 34 | Kenya | 0 1000 t | 2023 | — | flat |
| 34 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 34 | Cambodia | 0 1000 t | 2023 | — | flat |
| 34 | Kiribati | 0 1000 t | 2023 | — | flat |
| 34 | Kuwait | 0 1000 t | 2023 | — | flat |
| 34 | Lebanon | 0 1000 t | 2023 | — | flat |
| 34 | Liberia | 0 1000 t | 2023 | — | flat |
| 34 | Libya | 0 1000 t | 2023 | — | flat |
| 34 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 34 | Lesotho | 0 1000 t | 2023 | — | flat |
| 34 | Lithuania | 0 1000 t | 2023 | — | flat |
| 34 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 34 | Latvia | 0 1000 t | 2023 | — | flat |
| 34 | Morocco | 0 1000 t | 2023 | — | flat |
| 34 | Maldives | 0 1000 t | 2023 | — | flat |
| 34 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 34 | North Macedonia | 0 1000 t | 2020 | — | flat |
| 34 | Malta | 0 1000 t | 2023 | — | flat |
| 34 | Montenegro | 0 1000 t | 2023 | — | flat |
| 34 | Mongolia | 0 1000 t | 2023 | — | flat |
| 34 | Mozambique | 0 1000 t | 2023 | — | flat |
| 34 | Mauritania | 0 1000 t | 2018 | — | flat |
| 34 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 34 | Malawi | 0 1000 t | 2020 | — | flat |
| 34 | Namibia | 0 1000 t | 2023 | — | flat |
| 34 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 34 | Niger | 0 1000 t | 2020 | — | flat |
| 34 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 34 | Norway | 0 1000 t | 2023 | — | flat |
| 34 | Nepal | 0 1000 t | 2020 | — | flat |
| 34 | Oman | 0 1000 t | 2023 | — | flat |
| 34 | Panama | 0 1000 t | 2023 | — | volatile |
| 34 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 34 | Poland | 0 1000 t | 2023 | — | flat |
| 34 | Portugal | 0 1000 t | 2023 | — | flat |
| 34 | Paraguay | 0 1000 t | 2020 | — | flat |
| 34 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 34 | Qatar | 0 1000 t | 2023 | — | flat |
| 34 | Romania | 0 1000 t | 2023 | — | flat |
| 34 | Rwanda | 0 1000 t | 2023 | — | flat |
| 34 | Senegal | 0 1000 t | 2023 | — | flat |
| 34 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 34 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 34 | El Salvador | 0 1000 t | 2023 | — | flat |
| 34 | Serbia | 0 1000 t | 2023 | — | volatile |
| 34 | Slovak Republic | 0 1000 t | 2023 | — | flat |
| 34 | Slovenia | 0 1000 t | 2023 | — | flat |
| 34 | Sweden | 0 1000 t | 2023 | — | flat |
| 34 | Eswatini | 0 1000 t | 2018 | — | flat |
| 34 | Seychelles | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Tajikistan | 0 1000 t | 2018 | — | flat |
| 34 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 34 | Tonga | 0 1000 t | 2023 | — | flat |
| 34 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 34 | Tunisia | 0 1000 t | 2023 | — | flat |
| 34 | Uganda | 0 1000 t | 2020 | — | flat |
| 34 | Ukraine | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Uruguay | 0 1000 t | 2020 | — | flat |
| 34 | Uzbekistan | 0 1000 t | 2023 | — | flat |
| 34 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 34 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 34 | Yemen | 0 1000 t | 2023 | — | flat |
| 34 | South Africa | 0 1000 t | 2023 | — | flat |
| 34 | Zambia | 0 1000 t | 2023 | — | flat |
| 34 | Zimbabwe | 0 1000 t | 2020 | — | flat |
| 34 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | down 100.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 1,672 1000 t
- Americas 76 1000 t
- Northern America 25 1000 t
- United States of America 16 1000 t
- Net Food Importing Developing Countries (NFIDCs) 11 1000 t
- European Union (27) 7 1000 t
- Low Income Food Deficit Countries (LIFDCs) 7 1000 t
- Western Europe 3 1000 t
- Northern Europe 3 1000 t
- Land Locked Developing Countries (LLDCs) 1 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.