Millet and products — Stock Variation 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 — Stock Variation is currently reported for 159 countries. The highest value is 280 1000 t in Senegal; the lowest is -50 1000 t in Ethiopia.
The median across all reporting countries is 0 1000 t, and the mean is 2.53 1000 t.
The gap between the highest and lowest reporting country is a factor of about 6.
Over the past decade 13 countries rose and 9 fell. The largest increase was in Senegal (up 450.0%), and the largest decrease in Ethiopia (down 2,400.0%).
Millet and products — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Senegal | 280 1000 t | 2023 | up 450.0% | volatile |
| 2 | Niger | 120 1000 t | 2023 | up 133.8% | volatile |
| 3 | India | 56 1000 t | 2023 | up 214.3% | volatile |
| 4 | Zimbabwe | 30 1000 t | 2023 | — | volatile |
| 5 | Uzbekistan | 16 1000 t | 2023 | — | volatile |
| 6 | Argentina | 4 1000 t | 2023 | — | volatile |
| 6 | Democratic People's Republic of Korea | 4 1000 t | 2018 | up 100.0% | volatile |
| 8 | United Republic of Tanzania | 2 1000 t | 2023 | down 33.3% | rising |
| 9 | Bangladesh | 1 1000 t | 2023 | unchanged | volatile |
| 9 | Congo | 1 1000 t | 2023 | — | volatile |
| 9 | Germany | 1 1000 t | 2023 | down 75.0% | volatile |
| 9 | Myanmar | 1 1000 t | 2023 | up 120.0% | volatile |
| 13 | Afghanistan | 0 1000 t | 2023 | — | flat |
| 13 | Angola | 0 1000 t | 2023 | — | flat |
| 13 | Albania | 0 1000 t | 2023 | — | flat |
| 13 | United Arab Emirates | 0 1000 t | 2023 | — | flat |
| 13 | Armenia | 0 1000 t | 2023 | — | flat |
| 13 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 13 | Australia | 0 1000 t | 2023 | — | flat |
| 13 | Austria | 0 1000 t | 2023 | — | volatile |
| 13 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 13 | Belgium | 0 1000 t | 2023 | — | flat |
| 13 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 13 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 13 | Bahrain | 0 1000 t | 2023 | — | flat |
| 13 | Bahamas | 0 1000 t | 2023 | — | flat |
| 13 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 13 | Belarus | 0 1000 t | 2023 | — | flat |
| 13 | Belize | 0 1000 t | 2023 | — | flat |
| 13 | Brazil | 0 1000 t | 2023 | — | flat |
| 13 | Barbados | 0 1000 t | 2023 | — | flat |
| 13 | Bhutan | 0 1000 t | 2023 | — | flat |
| 13 | Botswana | 0 1000 t | 2023 | — | flat |
| 13 | Canada | 0 1000 t | 2023 | — | flat |
| 13 | Switzerland | 0 1000 t | 2023 | — | flat |
| 13 | Chile | 0 1000 t | 2023 | — | flat |
| 13 | Cameroon | 0 1000 t | 2023 | — | flat |
| 13 | Colombia | 0 1000 t | 2023 | — | flat |
| 13 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 13 | Cuba | 0 1000 t | 2019 | — | flat |
| 13 | Cyprus | 0 1000 t | 2023 | — | flat |
| 13 | Czechia | 0 1000 t | 2023 | — | flat |
| 13 | Denmark | 0 1000 t | 2023 | up 100.0% | flat |
| 13 | Algeria | 0 1000 t | 2023 | — | flat |
| 13 | Ecuador | 0 1000 t | 2023 | — | flat |
| 13 | Egypt | 0 1000 t | 2023 | — | volatile |
| 13 | Spain | 0 1000 t | 2023 | — | volatile |
| 13 | Estonia | 0 1000 t | 2023 | — | flat |
| 13 | Finland | 0 1000 t | 2023 | — | flat |
| 13 | Fiji | 0 1000 t | 2023 | — | flat |
| 13 | France | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Gabon | 0 1000 t | 2023 | — | flat |
| 13 | Georgia | 0 1000 t | 2023 | — | flat |
| 13 | Ghana | 0 1000 t | 2023 | — | flat |
| 13 | Gambia | 0 1000 t | 2023 | up 100.0% | flat |
| 13 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 13 | Greece | 0 1000 t | 2023 | — | flat |
| 13 | Guatemala | 0 1000 t | 2023 | — | flat |
| 13 | Guyana | 0 1000 t | 2023 | — | flat |
| 13 | Honduras | 0 1000 t | 2023 | — | flat |
| 13 | Croatia | 0 1000 t | 2023 | — | flat |
| 13 | Hungary | 0 1000 t | 2023 | — | volatile |
| 13 | Indonesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 13 | Ireland | 0 1000 t | 2023 | — | flat |
| 13 | Iraq | 0 1000 t | 2023 | — | volatile |
| 13 | Iceland | 0 1000 t | 2023 | — | flat |
| 13 | Israel | 0 1000 t | 2023 | — | flat |
| 13 | Italy | 0 1000 t | 2023 | — | flat |
| 13 | Jamaica | 0 1000 t | 2023 | — | flat |
| 13 | Jordan | 0 1000 t | 2023 | — | volatile |
| 13 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 13 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 13 | Cambodia | 0 1000 t | 2023 | — | flat |
| 13 | Kuwait | 0 1000 t | 2023 | — | flat |
| 13 | Lebanon | 0 1000 t | 2023 | — | flat |
| 13 | Libya | 0 1000 t | 2023 | — | flat |
| 13 | Saint Lucia | 0 1000 t | 2021 | — | flat |
| 13 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 13 | Lithuania | 0 1000 t | 2023 | — | flat |
| 13 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 13 | Latvia | 0 1000 t | 2023 | — | flat |
| 13 | Morocco | 0 1000 t | 2023 | — | volatile |
| 13 | Madagascar | 0 1000 t | 2023 | — | flat |
| 13 | Maldives | 0 1000 t | 2023 | — | flat |
| 13 | Mexico | 0 1000 t | 2023 | — | flat |
| 13 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 13 | Malta | 0 1000 t | 2023 | — | flat |
| 13 | Montenegro | 0 1000 t | 2023 | — | flat |
| 13 | Mongolia | 0 1000 t | 2023 | — | flat |
| 13 | Mozambique | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Mauritania | 0 1000 t | 2023 | — | flat |
| 13 | Mauritius | 0 1000 t | 2023 | — | flat |
| 13 | Malawi | 0 1000 t | 2023 | — | volatile |
| 13 | Malaysia | 0 1000 t | 2023 | — | flat |
| 13 | Namibia | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 13 | Nigeria | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Nicaragua | 0 1000 t | 2023 | — | flat |
| 13 | Norway | 0 1000 t | 2023 | — | flat |
| 13 | Nepal | 0 1000 t | 2023 | — | volatile |
| 13 | New Zealand | 0 1000 t | 2023 | — | flat |
| 13 | Oman | 0 1000 t | 2023 | — | flat |
| 13 | Pakistan | 0 1000 t | 2023 | — | flat |
| 13 | Panama | 0 1000 t | 2023 | — | flat |
| 13 | Peru | 0 1000 t | 2023 | — | flat |
| 13 | Philippines | 0 1000 t | 2023 | — | flat |
| 13 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 13 | Portugal | 0 1000 t | 2023 | — | volatile |
| 13 | Paraguay | 0 1000 t | 2023 | — | flat |
| 13 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 13 | Qatar | 0 1000 t | 2023 | — | volatile |
| 13 | Romania | 0 1000 t | 2023 | — | volatile |
| 13 | Rwanda | 0 1000 t | 2023 | — | flat |
| 13 | Saudi Arabia | 0 1000 t | 2023 | — | volatile |
| 13 | Sierra Leone | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | El Salvador | 0 1000 t | 2023 | — | flat |
| 13 | Serbia | 0 1000 t | 2023 | — | flat |
| 13 | Suriname | 0 1000 t | 2020 | — | flat |
| 13 | Slovakia | 0 1000 t | 2023 | — | flat |
| 13 | Slovenia | 0 1000 t | 2023 | — | flat |
| 13 | Sweden | 0 1000 t | 2023 | — | flat |
| 13 | Eswatini | 0 1000 t | 2023 | — | flat |
| 13 | Thailand | 0 1000 t | 2023 | — | flat |
| 13 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 13 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 13 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 13 | Tunisia | 0 1000 t | 2023 | — | volatile |
| 13 | Uganda | 0 1000 t | 2023 | — | flat |
| 13 | Ukraine | 0 1000 t | 2023 | — | flat |
| 13 | Uruguay | 0 1000 t | 2023 | — | flat |
| 13 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 13 | Samoa | 0 1000 t | 2021 | — | flat |
| 13 | Yemen | 0 1000 t | 2023 | — | flat |
| 13 | Zambia | 0 1000 t | 2023 | — | flat |
| 13 | Melanesia | 0 1000 t | 2023 | — | flat |
| 13 | Polynesia | 0 1000 t | 2023 | — | flat |
| 13 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 13 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 13 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 13 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | volatile |
| 13 | Republic of Korea | 0 1000 t | 2023 | — | volatile |
| 13 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 13 | Russian Federation | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Syrian Arab Republic | 0 1000 t | 2023 | — | flat |
| 13 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 13 | Viet Nam | 0 1000 t | 2023 | — | flat |
| 13 | Türkiye | 0 1000 t | 2023 | — | volatile |
| 13 | Australia and New Zealand | 0 1000 t | 2023 | — | flat |
| 13 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 13 | China, Taiwan Province of | 0 1000 t | 2023 | — | flat |
| 13 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | flat |
| 13 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | flat |
| 13 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
| 155 | Guinea | -1 1000 t | 2023 | — | volatile |
| 156 | Poland | -6 1000 t | 2023 | down 100.0% | volatile |
| 157 | China | -12 1000 t | 2023 | down 180.0% | volatile |
| 157 | China, mainland | -12 1000 t | 2023 | down 185.7% | volatile |
| 159 | Kenya | -33 1000 t | 2023 | down 1,750.0% | volatile |
| 160 | Ethiopia | -50 1000 t | 2023 | down 2,400.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Western Africa 382 1000 t
- World 104 1000 t
- Land Locked Developing Countries (LLDCs) 93 1000 t
- Asia 70 1000 t
- Southern Asia 57 1000 t
- Low Income Food Deficit Countries (LIFDCs) 48 1000 t
- Least Developed Countries (LDCs) 26 1000 t
- Africa 24 1000 t
- Central Asia 16 1000 t
- Americas 15 1000 t
- Northern America 11 1000 t
- United States of America 11 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.