Sugar Crops — 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
Sugar Crops — Export quantity is currently reported for 117 countries. The highest value is 345 1000 t in Germany; the lowest is 0 1000 t in China, Taiwan Province of.
The median across all reporting countries is 0 1000 t, and the mean is 10.79 1000 t.
Over the past decade 6 countries rose and 10 fell. The largest increase was in Germany (up 1,280.0%), and the largest decrease in Austria (down 100.0%).
Sugar Crops — Export quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Germany | 345 1000 t | 2023 | up 1,280.0% | volatile |
| 2 | Slovakia | 191 1000 t | 2023 | — | volatile |
| 3 | Myanmar | 190 1000 t | 2023 | up 175.4% | rising |
| 4 | Belgium | 178 1000 t | 2023 | up 394.4% | volatile |
| 5 | Latvia | 100 1000 t | 2023 | — | volatile |
| 6 | Poland | 95 1000 t | 2023 | — | volatile |
| 7 | Lao People's Democratic Republic | 84 1000 t | 2023 | up 265.2% | volatile |
| 8 | Slovenia | 11 1000 t | 2023 | — | volatile |
| 8 | Viet Nam | 11 1000 t | 2023 | — | volatile |
| 10 | Malaysia | 8 1000 t | 2023 | down 20.0% | volatile |
| 11 | France | 6 1000 t | 2023 | up 500.0% | volatile |
| 12 | China | 5 1000 t | 2023 | unchanged | rising |
| 12 | Denmark | 5 1000 t | 2023 | — | volatile |
| 12 | Hungary | 5 1000 t | 2023 | down 97.2% | volatile |
| 12 | China, mainland | 5 1000 t | 2023 | unchanged | rising |
| 16 | Lebanon | 4 1000 t | 2023 | — | volatile |
| 17 | Netherlands (Kingdom of the) | 3 1000 t | 2023 | down 98.6% | volatile |
| 18 | Cyprus | 2 1000 t | 2023 | down 50.0% | falling |
| 18 | Morocco | 2 1000 t | 2023 | — | volatile |
| 18 | Türkiye | 2 1000 t | 2023 | — | volatile |
| 18 | United Kingdom of Great Britain and Northern Ireland | 2 1000 t | 2023 | up 100.0% | volatile |
| 22 | Angola | 1 1000 t | 2023 | — | volatile |
| 22 | Brazil | 1 1000 t | 2023 | — | volatile |
| 22 | Costa Rica | 1 1000 t | 2023 | — | volatile |
| 22 | Czechia | 1 1000 t | 2023 | — | volatile |
| 22 | Algeria | 1 1000 t | 2023 | unchanged | volatile |
| 22 | Spain | 1 1000 t | 2023 | unchanged | volatile |
| 22 | India | 1 1000 t | 2023 | — | volatile |
| 22 | Pakistan | 1 1000 t | 2023 | — | volatile |
| 22 | Uganda | 1 1000 t | 2023 | — | volatile |
| 31 | Afghanistan | 0 1000 t | 2023 | — | flat |
| 31 | Albania | 0 1000 t | 2019 | — | flat |
| 31 | United Arab Emirates | 0 1000 t | 2023 | — | flat |
| 31 | Australia | 0 1000 t | 2023 | — | flat |
| 31 | Austria | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 31 | Bangladesh | 0 1000 t | 2023 | — | flat |
| 31 | Bulgaria | 0 1000 t | 2023 | — | flat |
| 31 | Belarus | 0 1000 t | 2023 | — | flat |
| 31 | Barbados | 0 1000 t | 2021 | — | flat |
| 31 | Botswana | 0 1000 t | 2023 | — | flat |
| 31 | Canada | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Switzerland | 0 1000 t | 2023 | — | flat |
| 31 | Chile | 0 1000 t | 2023 | — | flat |
| 31 | Cameroon | 0 1000 t | 2023 | — | flat |
| 31 | Colombia | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 31 | Ecuador | 0 1000 t | 2022 | — | flat |
| 31 | Egypt | 0 1000 t | 2023 | — | volatile |
| 31 | Estonia | 0 1000 t | 2022 | — | flat |
| 31 | Ethiopia | 0 1000 t | 2021 | — | flat |
| 31 | Fiji | 0 1000 t | 2023 | — | flat |
| 31 | Ghana | 0 1000 t | 2023 | — | flat |
| 31 | Greece | 0 1000 t | 2022 | — | flat |
| 31 | Guatemala | 0 1000 t | 2022 | — | flat |
| 31 | Guyana | 0 1000 t | 2021 | — | flat |
| 31 | Honduras | 0 1000 t | 2022 | — | flat |
| 31 | Croatia | 0 1000 t | 2020 | down 100.0% | volatile |
| 31 | Haiti | 0 1000 t | 2023 | — | flat |
| 31 | Indonesia | 0 1000 t | 2023 | — | volatile |
| 31 | Ireland | 0 1000 t | 2022 | — | flat |
| 31 | Israel | 0 1000 t | 2023 | — | flat |
| 31 | Italy | 0 1000 t | 2023 | — | flat |
| 31 | Jamaica | 0 1000 t | 2023 | — | flat |
| 31 | Kazakhstan | 0 1000 t | 2023 | — | volatile |
| 31 | Kenya | 0 1000 t | 2016 | — | flat |
| 31 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 31 | Cambodia | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Kuwait | 0 1000 t | 2023 | — | flat |
| 31 | Saint Lucia | 0 1000 t | 2020 | — | flat |
| 31 | Sri Lanka | 0 1000 t | 2019 | — | flat |
| 31 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 31 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 31 | Mexico | 0 1000 t | 2022 | down 100.0% | volatile |
| 31 | Malta | 0 1000 t | 2021 | — | flat |
| 31 | Mozambique | 0 1000 t | 2023 | — | flat |
| 31 | Mauritius | 0 1000 t | 2023 | — | flat |
| 31 | Malawi | 0 1000 t | 2022 | — | flat |
| 31 | Namibia | 0 1000 t | 2023 | — | flat |
| 31 | Niger | 0 1000 t | 2022 | — | flat |
| 31 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 31 | Nicaragua | 0 1000 t | 2022 | — | flat |
| 31 | Norway | 0 1000 t | 2022 | — | flat |
| 31 | Nepal | 0 1000 t | 2017 | — | flat |
| 31 | Oman | 0 1000 t | 2023 | — | flat |
| 31 | Peru | 0 1000 t | 2023 | — | flat |
| 31 | Philippines | 0 1000 t | 2019 | — | flat |
| 31 | Portugal | 0 1000 t | 2023 | — | flat |
| 31 | Paraguay | 0 1000 t | 2019 | — | flat |
| 31 | Romania | 0 1000 t | 2022 | — | flat |
| 31 | Rwanda | 0 1000 t | 2022 | — | flat |
| 31 | Saudi Arabia | 0 1000 t | 2023 | — | flat |
| 31 | Senegal | 0 1000 t | 2023 | — | flat |
| 31 | El Salvador | 0 1000 t | 2022 | — | flat |
| 31 | Serbia | 0 1000 t | 2023 | — | volatile |
| 31 | Sweden | 0 1000 t | 2023 | — | flat |
| 31 | Eswatini | 0 1000 t | 2019 | — | flat |
| 31 | Thailand | 0 1000 t | 2023 | — | volatile |
| 31 | Tunisia | 0 1000 t | 2023 | — | flat |
| 31 | Ukraine | 0 1000 t | 2023 | — | flat |
| 31 | Samoa | 0 1000 t | 2021 | — | flat |
| 31 | Yemen | 0 1000 t | 2022 | — | flat |
| 31 | Zambia | 0 1000 t | 2023 | — | flat |
| 31 | Zimbabwe | 0 1000 t | 2021 | — | flat |
| 31 | Melanesia | 0 1000 t | 2023 | — | flat |
| 31 | Polynesia | 0 1000 t | 2023 | — | flat |
| 31 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 31 | Caribbean | 0 1000 t | 2023 | — | flat |
| 31 | China, Hong Kong SAR | 0 1000 t | 2018 | — | flat |
| 31 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | flat |
| 31 | Republic of Korea | 0 1000 t | 2022 | — | flat |
| 31 | Russian Federation | 0 1000 t | 2023 | — | flat |
| 31 | Syrian Arab Republic | 0 1000 t | 2022 | — | flat |
| 31 | Australia and New Zealand | 0 1000 t | 2023 | — | flat |
| 31 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 31 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 31 | China, Taiwan Province of | 0 1000 t | 2019 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 1,261 1000 t
- European Union (27) 943 1000 t
- Europe 943 1000 t
- Western Europe 531 1000 t
- Asia 309 1000 t
- South-eastern Asia 294 1000 t
- Eastern Europe 292 1000 t
- Net Food Importing Developing Countries (NFIDCs) 279 1000 t
- Least Developed Countries (LDCs) 276 1000 t
- Northern Europe 107 1000 t
- Land Locked Developing Countries (LLDCs) 84 1000 t
- Southern Europe 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.