Roots, Other — 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
Roots, Other — Export quantity is currently reported for 147 countries. The highest value is 92 1000 t in China; the lowest is 0 1000 t in United Kingdom of Great Britain and Northern Ireland.
The median across all reporting countries is 0 1000 t, and the mean is 3.56 1000 t.
Over the past decade 13 countries rose and 19 fell. The largest increase was in Honduras (up 2,533.3%), and the largest decrease in Brazil (down 100.0%).
Roots, Other — Export quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 92 1000 t | 2023 | down 25.8% | falling |
| 2 | China, mainland | 91 1000 t | 2023 | down 25.4% | falling |
| 3 | Honduras | 79 1000 t | 2023 | up 2,533.3% | volatile |
| 4 | Mexico | 54 1000 t | 2023 | up 17.4% | rising |
| 5 | Ecuador | 35 1000 t | 2023 | up 191.7% | rising |
| 6 | Indonesia | 31 1000 t | 2023 | up 63.2% | rising |
| 7 | Ghana | 21 1000 t | 2023 | up 90.9% | volatile |
| 8 | Costa Rica | 18 1000 t | 2023 | up 5.9% | falling |
| 9 | United Arab Emirates | 12 1000 t | 2023 | up 500.0% | volatile |
| 10 | Nicaragua | 9 1000 t | 2023 | down 25.0% | falling |
| 11 | Cameroon | 6 1000 t | 2023 | up 500.0% | volatile |
| 11 | Nigeria | 6 1000 t | 2023 | — | volatile |
| 13 | Spain | 5 1000 t | 2023 | up 150.0% | rising |
| 13 | Fiji | 5 1000 t | 2023 | down 44.4% | falling |
| 13 | Melanesia | 5 1000 t | 2023 | down 44.4% | falling |
| 13 | Côte d'Ivoire | 5 1000 t | 2023 | down 80.8% | volatile |
| 13 | Netherlands (Kingdom of the) | 5 1000 t | 2023 | up 150.0% | rising |
| 18 | Uganda | 4 1000 t | 2023 | — | volatile |
| 18 | Caribbean | 4 1000 t | 2023 | down 87.1% | volatile |
| 18 | Viet Nam | 4 1000 t | 2023 | down 60.0% | falling |
| 21 | France | 3 1000 t | 2023 | up 50.0% | rising |
| 21 | Myanmar | 3 1000 t | 2023 | — | volatile |
| 21 | Thailand | 3 1000 t | 2023 | down 40.0% | volatile |
| 24 | Belgium | 2 1000 t | 2023 | unchanged | flat |
| 24 | Bangladesh | 2 1000 t | 2023 | — | volatile |
| 24 | Egypt | 2 1000 t | 2023 | unchanged | falling |
| 24 | India | 2 1000 t | 2023 | unchanged | volatile |
| 24 | Madagascar | 2 1000 t | 2023 | up 100.0% | volatile |
| 24 | Malaysia | 2 1000 t | 2023 | unchanged | falling |
| 24 | Saint Vincent and the Grenadines | 2 1000 t | 2023 | down 50.0% | falling |
| 24 | Polynesia | 2 1000 t | 2023 | up 100.0% | volatile |
| 32 | Cyprus | 1 1000 t | 2023 | — | volatile |
| 32 | Dominican Republic | 1 1000 t | 2023 | unchanged | volatile |
| 32 | Ethiopia | 1 1000 t | 2023 | — | volatile |
| 32 | Jamaica | 1 1000 t | 2023 | down 96.0% | volatile |
| 32 | Tonga | 1 1000 t | 2023 | — | falling |
| 32 | Zambia | 1 1000 t | 2023 | — | volatile |
| 32 | China, Hong Kong SAR | 1 1000 t | 2023 | unchanged | falling |
| 32 | China, Taiwan Province of | 1 1000 t | 2023 | unchanged | rising |
| 40 | Afghanistan | 0 1000 t | 2022 | — | volatile |
| 40 | Angola | 0 1000 t | 2023 | — | volatile |
| 40 | Albania | 0 1000 t | 2023 | — | flat |
| 40 | Argentina | 0 1000 t | 2017 | — | flat |
| 40 | Armenia | 0 1000 t | 2023 | — | flat |
| 40 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 40 | Australia | 0 1000 t | 2023 | — | flat |
| 40 | Austria | 0 1000 t | 2023 | — | flat |
| 40 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 40 | Bulgaria | 0 1000 t | 2023 | — | flat |
| 40 | Bahrain | 0 1000 t | 2023 | — | flat |
| 40 | Belarus | 0 1000 t | 2022 | — | flat |
| 40 | Belize | 0 1000 t | 2023 | — | flat |
| 40 | Brazil | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Barbados | 0 1000 t | 2023 | — | flat |
| 40 | Botswana | 0 1000 t | 2016 | — | flat |
| 40 | Canada | 0 1000 t | 2023 | — | flat |
| 40 | Switzerland | 0 1000 t | 2023 | — | flat |
| 40 | Chile | 0 1000 t | 2023 | — | flat |
| 40 | Congo | 0 1000 t | 2023 | — | flat |
| 40 | Colombia | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Czechia | 0 1000 t | 2023 | — | flat |
| 40 | Germany | 0 1000 t | 2023 | — | flat |
| 40 | Denmark | 0 1000 t | 2023 | — | flat |
| 40 | Algeria | 0 1000 t | 2023 | — | flat |
| 40 | Estonia | 0 1000 t | 2023 | — | flat |
| 40 | Finland | 0 1000 t | 2023 | — | flat |
| 40 | Gabon | 0 1000 t | 2023 | — | flat |
| 40 | Guinea | 0 1000 t | 2023 | — | flat |
| 40 | Gambia | 0 1000 t | 2016 | — | flat |
| 40 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 40 | Greece | 0 1000 t | 2023 | — | flat |
| 40 | Grenada | 0 1000 t | 2023 | — | flat |
| 40 | Guatemala | 0 1000 t | 2023 | — | flat |
| 40 | Guyana | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Croatia | 0 1000 t | 2023 | — | flat |
| 40 | Haiti | 0 1000 t | 2022 | — | flat |
| 40 | Hungary | 0 1000 t | 2023 | — | flat |
| 40 | Ireland | 0 1000 t | 2023 | — | flat |
| 40 | Israel | 0 1000 t | 2023 | — | flat |
| 40 | Italy | 0 1000 t | 2023 | — | volatile |
| 40 | Jordan | 0 1000 t | 2022 | — | flat |
| 40 | Kazakhstan | 0 1000 t | 2023 | — | flat |
| 40 | Kenya | 0 1000 t | 2023 | — | flat |
| 40 | Cambodia | 0 1000 t | 2023 | — | flat |
| 40 | Saint Kitts and Nevis | 0 1000 t | 2022 | — | flat |
| 40 | Kuwait | 0 1000 t | 2023 | — | flat |
| 40 | Lebanon | 0 1000 t | 2023 | — | flat |
| 40 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 40 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 40 | Lithuania | 0 1000 t | 2023 | — | flat |
| 40 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 40 | Latvia | 0 1000 t | 2022 | — | flat |
| 40 | Morocco | 0 1000 t | 2023 | — | flat |
| 40 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 40 | Mozambique | 0 1000 t | 2023 | — | flat |
| 40 | Mauritius | 0 1000 t | 2023 | — | flat |
| 40 | Malawi | 0 1000 t | 2023 | — | flat |
| 40 | Namibia | 0 1000 t | 2023 | — | flat |
| 40 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 40 | Niger | 0 1000 t | 2023 | — | volatile |
| 40 | Norway | 0 1000 t | 2023 | — | flat |
| 40 | New Zealand | 0 1000 t | 2023 | — | flat |
| 40 | Oman | 0 1000 t | 2023 | — | flat |
| 40 | Pakistan | 0 1000 t | 2023 | — | flat |
| 40 | Panama | 0 1000 t | 2023 | — | flat |
| 40 | Peru | 0 1000 t | 2023 | — | volatile |
| 40 | Philippines | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 40 | Poland | 0 1000 t | 2023 | — | flat |
| 40 | Portugal | 0 1000 t | 2023 | — | flat |
| 40 | Paraguay | 0 1000 t | 2023 | — | flat |
| 40 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 40 | Romania | 0 1000 t | 2023 | — | flat |
| 40 | Rwanda | 0 1000 t | 2023 | — | volatile |
| 40 | Saudi Arabia | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Senegal | 0 1000 t | 2023 | — | flat |
| 40 | Solomon Islands | 0 1000 t | 2018 | — | flat |
| 40 | Sierra Leone | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Serbia | 0 1000 t | 2023 | — | flat |
| 40 | Suriname | 0 1000 t | 2023 | — | volatile |
| 40 | Slovakia | 0 1000 t | 2023 | — | flat |
| 40 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 40 | Sweden | 0 1000 t | 2023 | — | flat |
| 40 | Eswatini | 0 1000 t | 2018 | — | flat |
| 40 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 40 | Tunisia | 0 1000 t | 2022 | — | flat |
| 40 | Ukraine | 0 1000 t | 2021 | — | flat |
| 40 | Uruguay | 0 1000 t | 2019 | — | flat |
| 40 | Uzbekistan | 0 1000 t | 2023 | — | flat |
| 40 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 40 | Samoa | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Yemen | 0 1000 t | 2023 | — | flat |
| 40 | Zimbabwe | 0 1000 t | 2014 | — | flat |
| 40 | Timor-Leste | 0 1000 t | 2023 | — | volatile |
| 40 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 40 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 40 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | flat |
| 40 | Republic of Korea | 0 1000 t | 2023 | — | flat |
| 40 | Republic of Moldova | 0 1000 t | 2018 | — | flat |
| 40 | Russian Federation | 0 1000 t | 2023 | — | volatile |
| 40 | Syrian Arab Republic | 0 1000 t | 2023 | — | flat |
| 40 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 40 | Türkiye | 0 1000 t | 2023 | — | flat |
| 40 | Australia and New Zealand | 0 1000 t | 2023 | — | flat |
| 40 | Lao People's Democratic Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 40 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 448 1000 t
- Americas 216 1000 t
- Central America 160 1000 t
- Asia 153 1000 t
- Net Food Importing Developing Countries (NFIDCs) 112 1000 t
- Eastern Asia 92 1000 t
- Africa 54 1000 t
- South-eastern Asia 44 1000 t
- Western Africa 37 1000 t
- South America 36 1000 t
- Low Income Food Deficit Countries (LIFDCs) 29 1000 t
- Least Developed Countries (LDCs) 19 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.