Aquatic Plants — 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 Plants — Production is currently reported for 51 countries. The highest value is 21,790 1000 t in China; the lowest is 0 1000 t in Senegal.
The median across all reporting countries is 6 1000 t, and the mean is 1,133 1000 t.
Over the past decade 16 countries rose and 21 fell. The largest increase was in Russian Federation (up 416.7%), and the largest decrease in Israel (down 100.0%).
Aquatic Plants — Production: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 21,790 1000 t | 2023 | up 45.5% | rising |
| 2 | China, mainland | 21,789 1000 t | 2023 | up 45.5% | rising |
| 3 | Indonesia | 9,148 1000 t | 2023 | down 1.8% | rising |
| 4 | Republic of Korea | 1,853 1000 t | 2023 | up 62.5% | rising |
| 5 | Philippines | 1,344 1000 t | 2023 | down 13.8% | falling |
| 6 | Democratic People's Republic of Korea | 603 1000 t | 2018 | up 35.5% | rising |
| 7 | Chile | 428 1000 t | 2023 | down 19.2% | flat |
| 8 | Malaysia | 179 1000 t | 2023 | down 33.5% | falling |
| 9 | Norway | 163 1000 t | 2023 | up 5.8% | rising |
| 10 | United Republic of Tanzania | 106 1000 t | 2023 | down 10.2% | falling |
| 11 | France | 52 1000 t | 2023 | down 24.6% | rising |
| 12 | Peru | 49 1000 t | 2023 | up 58.1% | rising |
| 13 | India | 39 1000 t | 2023 | up 44.4% | rising |
| 14 | Russian Federation | 31 1000 t | 2023 | up 416.7% | volatile |
| 14 | Russia | 31 1000 t | 2023 | up 416.7% | volatile |
| 16 | Ireland | 30 1000 t | 2023 | unchanged | flat |
| 17 | Morocco | 21 1000 t | 2023 | down 4.5% | rising |
| 18 | Iceland | 18 1000 t | 2023 | up 5.9% | flat |
| 19 | Viet Nam | 13 1000 t | 2023 | down 13.3% | falling |
| 19 | Vietnam | 13 1000 t | 2023 | down 13.3% | falling |
| 19 | Canada | 13 1000 t | 2023 | down 18.8% | falling |
| 22 | Madagascar | 12 1000 t | 2023 | up 200.0% | volatile |
| 23 | Melanesia | 10 1000 t | 2023 | down 33.3% | falling |
| 24 | South Africa | 9 1000 t | 2023 | down 35.7% | falling |
| 25 | Mexico | 7 1000 t | 2023 | down 30.0% | rising |
| 26 | Solomon Islands | 6 1000 t | 2023 | down 50.0% | falling |
| 27 | Venezuela (Bolivarian Republic of) | 5 1000 t | 2023 | — | volatile |
| 28 | Kiribati | 4 1000 t | 2023 | up 100.0% | falling |
| 28 | Papua New Guinea | 4 1000 t | 2023 | up 33.3% | rising |
| 28 | Micronesia | 4 1000 t | 2023 | up 100.0% | falling |
| 31 | Spain | 3 1000 t | 2023 | up 200.0% | volatile |
| 31 | United States | 3 1000 t | 2023 | down 25.0% | volatile |
| 33 | Portugal | 2 1000 t | 2023 | up 100.0% | volatile |
| 33 | China, Taiwan Province of | 2 1000 t | 2023 | down 50.0% | volatile |
| 33 | Australia | 2 1000 t | 2023 | unchanged | flat |
| 33 | Australia and New Zealand | 2 1000 t | 2023 | down 33.3% | falling |
| 37 | Brazil | 1 1000 t | 2023 | unchanged | flat |
| 37 | Italy | 1 1000 t | 2023 | unchanged | flat |
| 37 | New Zealand | 1 1000 t | 2023 | unchanged | volatile |
| 37 | Kenya | 1 1000 t | 2023 | — | volatile |
| 37 | Cambodia | 1 1000 t | 2023 | — | volatile |
| 37 | Timor-Leste | 1 1000 t | 2023 | unchanged | rising |
| 37 | East Timor | 1 1000 t | 2023 | unchanged | rising |
| 44 | Fiji | 0 1000 t | 2023 | — | volatile |
| 44 | Israel | 0 1000 t | 2023 | down 100.0% | volatile |
| 44 | Denmark | 0 1000 t | 2023 | down 100.0% | volatile |
| 44 | Myanmar | 0 1000 t | 2023 | down 100.0% | volatile |
| 44 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 44 | Estonia | 0 1000 t | 2023 | — | volatile |
| 44 | Ukraine | 0 1000 t | 2023 | — | volatile |
| 44 | Senegal | 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 36,354 1000 t
- Asia 35,383 1000 t
- Eastern Asia 24,659 1000 t
- South-Eastern Asia 10,686 1000 t
- Low Income Food Deficit Countries (LIFDCs) 722 1000 t
- Americas 507 1000 t
- South America 483 1000 t
- Europe 299 1000 t
- Northern Europe 210 1000 t
- Net Food Importing Developing Countries (NFIDCs) 206 1000 t
- Africa 149 1000 t
- Least Developed Countries (LDCs) 130 1000 t
- Eastern Africa 119 1000 t
- European Union (27) 87 1000 t
- Western Europe 52 1000 t
- Southern Asia 39 1000 t
- Eastern Europe 31 1000 t
- Northern Africa 21 1000 t
- Northern America 16 1000 t
- Oceania 16 1000 t
- Small island developing States (SIDS) 15 1000 t
- Southern Africa 9 1000 t
- Central America 7 1000 t
- Southern Europe 6 1000 t
- United States of America 3 1000 t
- Western Asia 0 1000 t
- Western Africa 0 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.