Aquatic Animals, Others — Production 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 — Production is currently reported for 112 countries. The highest value is 1,235 1000 t in China; the lowest is 0 1000 t in Micronesia (Federated States of).
The median across all reporting countries is 0 1000 t, and the mean is 24.71 1000 t.
Over the past decade 14 countries rose and 16 fell. The largest increase was in Nicaragua (up 500.0%), and the largest decrease in Belize (down 100.0%).
Aquatic Animals, Others — Production: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 1,235 1000 t | 2023 | up 18.3% | rising |
| 2 | China, mainland | 1,232 1000 t | 2023 | up 18.6% | rising |
| 3 | Indonesia | 49 1000 t | 2023 | down 5.8% | volatile |
| 4 | Mexico | 40 1000 t | 2023 | up 42.9% | rising |
| 5 | Chile | 36 1000 t | 2023 | up 12.5% | rising |
| 6 | Republic of Korea | 29 1000 t | 2023 | up 26.1% | rising |
| 7 | Russian Federation | 26 1000 t | 2023 | up 100.0% | rising |
| 8 | Malaysia | 25 1000 t | 2023 | up 108.3% | rising |
| 9 | Canada | 16 1000 t | 2023 | up 23.1% | rising |
| 10 | Viet Nam | 15 1000 t | 2023 | up 275.0% | volatile |
| 11 | Thailand | 11 1000 t | 2023 | down 91.7% | volatile |
| 12 | Ecuador | 6 1000 t | 2023 | — | volatile |
| 12 | Iceland | 6 1000 t | 2023 | up 200.0% | rising |
| 12 | Nicaragua | 6 1000 t | 2023 | up 500.0% | volatile |
| 15 | India | 5 1000 t | 2023 | down 70.6% | volatile |
| 16 | Sri Lanka | 4 1000 t | 2023 | unchanged | flat |
| 17 | Pakistan | 3 1000 t | 2023 | up 200.0% | rising |
| 17 | China, Taiwan Province of | 3 1000 t | 2023 | down 40.0% | falling |
| 19 | Honduras | 2 1000 t | 2023 | up 100.0% | rising |
| 19 | Madagascar | 2 1000 t | 2023 | down 33.3% | rising |
| 19 | Myanmar | 2 1000 t | 2023 | down 60.0% | volatile |
| 19 | Melanesia | 2 1000 t | 2023 | up 100.0% | rising |
| 19 | Australia and New Zealand | 2 1000 t | 2023 | down 60.0% | volatile |
| 24 | Australia | 1 1000 t | 2023 | down 75.0% | volatile |
| 24 | Spain | 1 1000 t | 2023 | unchanged | flat |
| 24 | New Zealand | 1 1000 t | 2023 | unchanged | flat |
| 24 | Panama | 1 1000 t | 2023 | — | volatile |
| 24 | Peru | 1 1000 t | 2023 | unchanged | volatile |
| 24 | Philippines | 1 1000 t | 2023 | unchanged | flat |
| 24 | Papua New Guinea | 1 1000 t | 2023 | — | volatile |
| 24 | Samoa | 1 1000 t | 2023 | unchanged | flat |
| 24 | Polynesia | 1 1000 t | 2023 | unchanged | flat |
| 24 | Türkiye | 1 1000 t | 2023 | unchanged | rising |
| 34 | Albania | 0 1000 t | 2023 | — | flat |
| 34 | United Arab Emirates | 0 1000 t | 2023 | — | flat |
| 34 | Argentina | 0 1000 t | 2023 | — | flat |
| 34 | Belgium | 0 1000 t | 2023 | — | flat |
| 34 | Bangladesh | 0 1000 t | 2023 | — | flat |
| 34 | Bulgaria | 0 1000 t | 2018 | — | flat |
| 34 | Bahrain | 0 1000 t | 2023 | — | flat |
| 34 | Bahamas | 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 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 34 | Cuba | 0 1000 t | 2019 | — | flat |
| 34 | Germany | 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 | Egypt | 0 1000 t | 2018 | — | flat |
| 34 | Estonia | 0 1000 t | 2023 | — | flat |
| 34 | Finland | 0 1000 t | 2023 | — | flat |
| 34 | Fiji | 0 1000 t | 2023 | — | volatile |
| 34 | France | 0 1000 t | 2023 | — | flat |
| 34 | Gabon | 0 1000 t | 2023 | — | flat |
| 34 | Greece | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Grenada | 0 1000 t | 2023 | — | flat |
| 34 | Guyana | 0 1000 t | 2023 | — | flat |
| 34 | Croatia | 0 1000 t | 2023 | — | flat |
| 34 | Haiti | 0 1000 t | 2023 | — | volatile |
| 34 | Ireland | 0 1000 t | 2023 | — | volatile |
| 34 | Italy | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Jamaica | 0 1000 t | 2023 | — | flat |
| 34 | Kenya | 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 | Liberia | 0 1000 t | 2023 | — | flat |
| 34 | Lithuania | 0 1000 t | 2023 | — | flat |
| 34 | Latvia | 0 1000 t | 2023 | — | flat |
| 34 | Maldives | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Malta | 0 1000 t | 2023 | — | flat |
| 34 | Mongolia | 0 1000 t | 2023 | — | flat |
| 34 | Mozambique | 0 1000 t | 2023 | — | volatile |
| 34 | Mauritania | 0 1000 t | 2018 | — | flat |
| 34 | Mauritius | 0 1000 t | 2023 | — | flat |
| 34 | Namibia | 0 1000 t | 2023 | — | flat |
| 34 | New Caledonia | 0 1000 t | 2023 | — | volatile |
| 34 | Norway | 0 1000 t | 2023 | — | flat |
| 34 | Oman | 0 1000 t | 2023 | — | flat |
| 34 | Poland | 0 1000 t | 2023 | — | flat |
| 34 | Portugal | 0 1000 t | 2023 | — | volatile |
| 34 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 34 | Qatar | 0 1000 t | 2023 | — | flat |
| 34 | Romania | 0 1000 t | 2019 | — | flat |
| 34 | Saudi Arabia | 0 1000 t | 2017 | — | flat |
| 34 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 34 | El Salvador | 0 1000 t | 2023 | — | flat |
| 34 | Sweden | 0 1000 t | 2023 | — | flat |
| 34 | Seychelles | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Tonga | 0 1000 t | 2023 | — | flat |
| 34 | Tunisia | 0 1000 t | 2023 | — | flat |
| 34 | Ukraine | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Uruguay | 0 1000 t | 2020 | — | 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 | Micronesia | 0 1000 t | 2023 | — | flat |
| 34 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 34 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 34 | Caribbean | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | China, Hong Kong SAR | 0 1000 t | 2019 | — | volatile |
| 34 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | volatile |
| 34 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 34 | Côte d'Ivoire | 0 1000 t | 2014 | — | flat |
| 34 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 34 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 34 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | flat |
| 34 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | flat |
| 34 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | flat |
| 34 | Micronesia (Federated States of) | 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 1,563 1000 t
- Asia 1,407 1000 t
- Eastern Asia 1,291 1000 t
- Americas 114 1000 t
- South-eastern Asia 103 1000 t
- Central America 49 1000 t
- South America 43 1000 t
- Europe 35 1000 t
- Eastern Europe 27 1000 t
- Northern America 21 1000 t
- Net Food Importing Developing Countries (NFIDCs) 15 1000 t
- Southern Asia 12 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.