Millet and products — 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
Millet and products — Export quantity is currently reported for 111 countries. The highest value is 103 1000 t in India; 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 3.77 1000 t.
Over the past decade 12 countries rose and 11 fell. The largest increase was in Türkiye (up 1,900.0%), and the largest decrease in Spain (down 100.0%).
Millet and products — Export quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 103 1000 t | 2023 | up 24.1% | falling |
| 2 | Russian Federation | 77 1000 t | 2023 | up 97.4% | rising |
| 3 | Ukraine | 69 1000 t | 2023 | up 72.5% | volatile |
| 4 | Uzbekistan | 33 1000 t | 2023 | — | volatile |
| 5 | France | 23 1000 t | 2023 | up 9.5% | rising |
| 6 | Türkiye | 20 1000 t | 2023 | up 1,900.0% | volatile |
| 7 | Poland | 17 1000 t | 2023 | up 112.5% | volatile |
| 8 | United Republic of Tanzania | 8 1000 t | 2023 | — | volatile |
| 9 | Canada | 6 1000 t | 2023 | up 20.0% | volatile |
| 9 | China | 6 1000 t | 2023 | down 53.8% | volatile |
| 9 | Kazakhstan | 6 1000 t | 2023 | up 500.0% | volatile |
| 9 | China, mainland | 6 1000 t | 2023 | down 53.8% | volatile |
| 13 | Germany | 5 1000 t | 2023 | down 16.7% | rising |
| 14 | Austria | 4 1000 t | 2023 | down 50.0% | falling |
| 14 | Netherlands (Kingdom of the) | 4 1000 t | 2023 | unchanged | rising |
| 16 | Argentina | 3 1000 t | 2023 | down 50.0% | volatile |
| 16 | Pakistan | 3 1000 t | 2023 | — | volatile |
| 16 | Yemen | 3 1000 t | 2023 | up 50.0% | volatile |
| 19 | Burkina Faso | 2 1000 t | 2021 | up 100.0% | volatile |
| 19 | Bulgaria | 2 1000 t | 2023 | up 100.0% | volatile |
| 19 | Czechia | 2 1000 t | 2023 | unchanged | rising |
| 19 | Senegal | 2 1000 t | 2023 | — | volatile |
| 19 | Uganda | 2 1000 t | 2023 | up 100.0% | volatile |
| 24 | Angola | 1 1000 t | 2023 | — | volatile |
| 24 | United Arab Emirates | 1 1000 t | 2023 | — | volatile |
| 24 | Australia | 1 1000 t | 2023 | down 66.7% | volatile |
| 24 | Belgium | 1 1000 t | 2023 | down 75.0% | falling |
| 24 | Egypt | 1 1000 t | 2023 | — | volatile |
| 24 | Ethiopia | 1 1000 t | 2023 | — | volatile |
| 24 | Hungary | 1 1000 t | 2023 | down 50.0% | volatile |
| 24 | Italy | 1 1000 t | 2023 | — | volatile |
| 24 | Niger | 1 1000 t | 2023 | — | volatile |
| 24 | Nigeria | 1 1000 t | 2023 | — | volatile |
| 24 | Slovakia | 1 1000 t | 2023 | unchanged | volatile |
| 24 | Iran (Islamic Republic of) | 1 1000 t | 2023 | — | volatile |
| 24 | Australia and New Zealand | 1 1000 t | 2023 | down 66.7% | volatile |
| 37 | Afghanistan | 0 1000 t | 2023 | — | volatile |
| 37 | Bangladesh | 0 1000 t | 2021 | — | flat |
| 37 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 37 | Belarus | 0 1000 t | 2023 | — | volatile |
| 37 | Brazil | 0 1000 t | 2023 | — | volatile |
| 37 | Botswana | 0 1000 t | 2023 | — | flat |
| 37 | Switzerland | 0 1000 t | 2023 | — | flat |
| 37 | Chile | 0 1000 t | 2023 | — | flat |
| 37 | Cameroon | 0 1000 t | 2023 | — | volatile |
| 37 | Colombia | 0 1000 t | 2023 | — | flat |
| 37 | Djibouti | 0 1000 t | 2020 | — | flat |
| 37 | Denmark | 0 1000 t | 2023 | — | flat |
| 37 | Spain | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Estonia | 0 1000 t | 2023 | — | volatile |
| 37 | Finland | 0 1000 t | 2023 | — | volatile |
| 37 | Fiji | 0 1000 t | 2022 | — | flat |
| 37 | Ghana | 0 1000 t | 2023 | — | flat |
| 37 | Guinea | 0 1000 t | 2023 | — | flat |
| 37 | Greece | 0 1000 t | 2023 | — | flat |
| 37 | Guatemala | 0 1000 t | 2023 | — | flat |
| 37 | Guyana | 0 1000 t | 2014 | — | flat |
| 37 | Honduras | 0 1000 t | 2020 | — | flat |
| 37 | Croatia | 0 1000 t | 2023 | — | flat |
| 37 | Haiti | 0 1000 t | 2023 | — | flat |
| 37 | Indonesia | 0 1000 t | 2023 | — | flat |
| 37 | Ireland | 0 1000 t | 2023 | — | flat |
| 37 | Kenya | 0 1000 t | 2023 | — | flat |
| 37 | Cambodia | 0 1000 t | 2016 | — | flat |
| 37 | Kuwait | 0 1000 t | 2017 | — | flat |
| 37 | Lebanon | 0 1000 t | 2023 | — | flat |
| 37 | Libya | 0 1000 t | 2018 | — | flat |
| 37 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 37 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 37 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 37 | Latvia | 0 1000 t | 2023 | — | flat |
| 37 | Morocco | 0 1000 t | 2023 | — | flat |
| 37 | Mexico | 0 1000 t | 2017 | — | flat |
| 37 | North Macedonia | 0 1000 t | 2022 | — | flat |
| 37 | Myanmar | 0 1000 t | 2022 | — | volatile |
| 37 | Mozambique | 0 1000 t | 2022 | — | flat |
| 37 | Mauritius | 0 1000 t | 2021 | — | flat |
| 37 | Malawi | 0 1000 t | 2023 | — | volatile |
| 37 | Malaysia | 0 1000 t | 2023 | — | flat |
| 37 | Namibia | 0 1000 t | 2023 | — | flat |
| 37 | Norway | 0 1000 t | 2023 | — | flat |
| 37 | Nepal | 0 1000 t | 2023 | — | flat |
| 37 | New Zealand | 0 1000 t | 2023 | — | flat |
| 37 | Oman | 0 1000 t | 2023 | — | flat |
| 37 | Philippines | 0 1000 t | 2023 | — | flat |
| 37 | Portugal | 0 1000 t | 2023 | — | flat |
| 37 | Romania | 0 1000 t | 2023 | — | volatile |
| 37 | Rwanda | 0 1000 t | 2023 | — | flat |
| 37 | Saudi Arabia | 0 1000 t | 2022 | — | flat |
| 37 | El Salvador | 0 1000 t | 2020 | — | flat |
| 37 | Serbia | 0 1000 t | 2023 | — | flat |
| 37 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 37 | Sweden | 0 1000 t | 2023 | — | flat |
| 37 | Eswatini | 0 1000 t | 2023 | — | flat |
| 37 | Thailand | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 37 | Tunisia | 0 1000 t | 2020 | — | flat |
| 37 | Uruguay | 0 1000 t | 2023 | — | flat |
| 37 | Zambia | 0 1000 t | 2023 | — | flat |
| 37 | Zimbabwe | 0 1000 t | 2023 | — | volatile |
| 37 | Melanesia | 0 1000 t | 2022 | — | flat |
| 37 | Caribbean | 0 1000 t | 2023 | — | flat |
| 37 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 37 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 37 | Republic of Korea | 0 1000 t | 2023 | — | flat |
| 37 | Republic of Moldova | 0 1000 t | 2023 | — | volatile |
| 37 | Syrian Arab Republic | 0 1000 t | 2022 | — | flat |
| 37 | Viet Nam | 0 1000 t | 2023 | — | volatile |
| 37 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 37 | China, Taiwan Province of | 0 1000 t | 2023 | — | flat |
| 37 | United Kingdom of Great Britain and Northern Ireland | 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 479 1000 t
- Europe 207 1000 t
- Asia 176 1000 t
- Eastern Europe 168 1000 t
- Southern Asia 108 1000 t
- Americas 75 1000 t
- Northern America 71 1000 t
- United States of America 65 1000 t
- European Union (27) 61 1000 t
- Low Income Food Deficit Countries (LIFDCs) 52 1000 t
- Land Locked Developing Countries (LLDCs) 45 1000 t
- Central Asia 39 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.