Sorghum 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
Sorghum and products — Stock Variation is currently reported for 158 countries. The highest value is 105 1000 t in Brazil; the lowest is -258 1000 t in Australia and New Zealand.
The median across all reporting countries is 0 1000 t, and the mean is -4.34 1000 t.
Over the past decade 24 countries rose and 14 fell. The largest increase was in Saudi Arabia (up 950.0%), and the largest decrease in Australia (down 2,245.4%).
Sorghum and products — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Brazil | 105 1000 t | 2023 | — | volatile |
| 2 | China | 39 1000 t | 2023 | up 108.4% | volatile |
| 2 | China, mainland | 39 1000 t | 2023 | up 108.4% | volatile |
| 4 | Bolivia (Plurinational State of) | 38 1000 t | 2023 | up 192.7% | volatile |
| 5 | Saudi Arabia | 17 1000 t | 2023 | up 950.0% | volatile |
| 6 | Angola | 14 1000 t | 2023 | up 800.0% | volatile |
| 7 | Hungary | 9 1000 t | 2023 | — | volatile |
| 8 | Lesotho | 4 1000 t | 2023 | down 20.0% | volatile |
| 9 | Zimbabwe | 3 1000 t | 2023 | — | volatile |
| 9 | Republic of Moldova | 3 1000 t | 2023 | up 400.0% | volatile |
| 11 | Belize | 2 1000 t | 2023 | up 100.0% | volatile |
| 11 | Canada | 2 1000 t | 2023 | — | volatile |
| 11 | Egypt | 2 1000 t | 2023 | up 140.0% | volatile |
| 14 | Bulgaria | 1 1000 t | 2023 | up 200.0% | volatile |
| 14 | Democratic People's Republic of Korea | 1 1000 t | 2018 | — | volatile |
| 16 | Albania | 0 1000 t | 2023 | — | flat |
| 16 | United Arab Emirates | 0 1000 t | 2023 | — | flat |
| 16 | Armenia | 0 1000 t | 2020 | — | flat |
| 16 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 16 | Austria | 0 1000 t | 2023 | — | volatile |
| 16 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 16 | Belgium | 0 1000 t | 2023 | — | flat |
| 16 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 16 | Bahrain | 0 1000 t | 2023 | — | flat |
| 16 | Bahamas | 0 1000 t | 2023 | — | flat |
| 16 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 16 | Belarus | 0 1000 t | 2023 | — | flat |
| 16 | Barbados | 0 1000 t | 2023 | — | flat |
| 16 | Switzerland | 0 1000 t | 2023 | — | flat |
| 16 | Chile | 0 1000 t | 2023 | — | flat |
| 16 | Cameroon | 0 1000 t | 2023 | — | flat |
| 16 | Congo | 0 1000 t | 2023 | — | flat |
| 16 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 16 | Cuba | 0 1000 t | 2019 | — | flat |
| 16 | Cyprus | 0 1000 t | 2023 | — | flat |
| 16 | Czechia | 0 1000 t | 2023 | — | flat |
| 16 | Germany | 0 1000 t | 2023 | — | flat |
| 16 | Djibouti | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Denmark | 0 1000 t | 2023 | — | flat |
| 16 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 16 | Algeria | 0 1000 t | 2023 | — | flat |
| 16 | Ecuador | 0 1000 t | 2023 | — | flat |
| 16 | Estonia | 0 1000 t | 2023 | — | flat |
| 16 | Finland | 0 1000 t | 2023 | — | flat |
| 16 | Fiji | 0 1000 t | 2023 | — | flat |
| 16 | France | 0 1000 t | 2023 | — | volatile |
| 16 | Gabon | 0 1000 t | 2023 | — | flat |
| 16 | Georgia | 0 1000 t | 2023 | — | flat |
| 16 | Guinea | 0 1000 t | 2023 | — | volatile |
| 16 | Gambia | 0 1000 t | 2023 | — | flat |
| 16 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 16 | Greece | 0 1000 t | 2023 | — | flat |
| 16 | Guatemala | 0 1000 t | 2023 | — | flat |
| 16 | Honduras | 0 1000 t | 2023 | — | volatile |
| 16 | Croatia | 0 1000 t | 2023 | — | flat |
| 16 | Haiti | 0 1000 t | 2023 | — | flat |
| 16 | Indonesia | 0 1000 t | 2023 | — | flat |
| 16 | Ireland | 0 1000 t | 2023 | — | flat |
| 16 | Iraq | 0 1000 t | 2023 | — | flat |
| 16 | Iceland | 0 1000 t | 2023 | — | flat |
| 16 | Italy | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Jamaica | 0 1000 t | 2023 | — | flat |
| 16 | Jordan | 0 1000 t | 2023 | — | volatile |
| 16 | Kazakhstan | 0 1000 t | 2023 | — | volatile |
| 16 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 16 | Cambodia | 0 1000 t | 2023 | — | flat |
| 16 | Kuwait | 0 1000 t | 2023 | — | flat |
| 16 | Lebanon | 0 1000 t | 2023 | — | flat |
| 16 | Libya | 0 1000 t | 2023 | — | volatile |
| 16 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 16 | Lithuania | 0 1000 t | 2023 | — | flat |
| 16 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 16 | Latvia | 0 1000 t | 2023 | — | flat |
| 16 | Morocco | 0 1000 t | 2023 | — | volatile |
| 16 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 16 | Maldives | 0 1000 t | 2023 | — | flat |
| 16 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 16 | Malta | 0 1000 t | 2023 | — | flat |
| 16 | Montenegro | 0 1000 t | 2023 | — | flat |
| 16 | Mozambique | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Mauritania | 0 1000 t | 2023 | — | flat |
| 16 | Malawi | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Malaysia | 0 1000 t | 2023 | — | flat |
| 16 | Namibia | 0 1000 t | 2023 | — | volatile |
| 16 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 16 | Nicaragua | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Norway | 0 1000 t | 2023 | — | flat |
| 16 | Nepal | 0 1000 t | 2023 | — | flat |
| 16 | New Zealand | 0 1000 t | 2023 | — | flat |
| 16 | Oman | 0 1000 t | 2023 | — | volatile |
| 16 | Pakistan | 0 1000 t | 2023 | — | flat |
| 16 | Panama | 0 1000 t | 2023 | — | volatile |
| 16 | Peru | 0 1000 t | 2023 | — | flat |
| 16 | Philippines | 0 1000 t | 2023 | — | flat |
| 16 | Papua New Guinea | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Poland | 0 1000 t | 2023 | — | flat |
| 16 | Portugal | 0 1000 t | 2023 | — | flat |
| 16 | Paraguay | 0 1000 t | 2023 | — | flat |
| 16 | French Polynesia | 0 1000 t | 2018 | — | flat |
| 16 | Qatar | 0 1000 t | 2023 | — | volatile |
| 16 | Romania | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Rwanda | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Senegal | 0 1000 t | 2023 | — | volatile |
| 16 | Solomon Islands | 0 1000 t | 2020 | — | flat |
| 16 | Sierra Leone | 0 1000 t | 2023 | — | volatile |
| 16 | El Salvador | 0 1000 t | 2023 | — | flat |
| 16 | Serbia | 0 1000 t | 2023 | — | flat |
| 16 | Slovakia | 0 1000 t | 2023 | — | flat |
| 16 | Slovenia | 0 1000 t | 2023 | — | flat |
| 16 | Sweden | 0 1000 t | 2023 | — | flat |
| 16 | Eswatini | 0 1000 t | 2023 | — | flat |
| 16 | Thailand | 0 1000 t | 2023 | down 100.0% | volatile |
| 16 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 16 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 16 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 16 | Tunisia | 0 1000 t | 2023 | — | flat |
| 16 | Uganda | 0 1000 t | 2023 | — | flat |
| 16 | Uzbekistan | 0 1000 t | 2023 | — | volatile |
| 16 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 16 | Samoa | 0 1000 t | 2020 | — | flat |
| 16 | Yemen | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Zambia | 0 1000 t | 2023 | — | flat |
| 16 | Micronesia | 0 1000 t | 2023 | — | flat |
| 16 | Melanesia | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Polynesia | 0 1000 t | 2020 | — | flat |
| 16 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 16 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 16 | Republic of Korea | 0 1000 t | 2023 | — | flat |
| 16 | Russian Federation | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Syrian Arab Republic | 0 1000 t | 2023 | — | flat |
| 16 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 16 | Viet Nam | 0 1000 t | 2023 | — | flat |
| 16 | Türkiye | 0 1000 t | 2023 | — | flat |
| 16 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 16 | China, Taiwan Province of | 0 1000 t | 2023 | up 100.0% | volatile |
| 16 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | flat |
| 16 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | flat |
| 16 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
| 140 | Colombia | -1 1000 t | 2023 | up 90.0% | volatile |
| 140 | Israel | -1 1000 t | 2023 | down 133.3% | volatile |
| 140 | Ukraine | -1 1000 t | 2023 | down 102.0% | volatile |
| 140 | Iran (Islamic Republic of) | -1 1000 t | 2023 | — | volatile |
| 144 | Uruguay | -2 1000 t | 2023 | up 50.0% | volatile |
| 145 | United Republic of Tanzania | -5 1000 t | 2023 | — | volatile |
| 146 | Ghana | -8 1000 t | 2023 | — | volatile |
| 147 | Myanmar | -9 1000 t | 2023 | down 125.0% | volatile |
| 148 | Botswana | -11 1000 t | 2023 | — | volatile |
| 149 | Spain | -19 1000 t | 2023 | — | volatile |
| 149 | Nigeria | -19 1000 t | 2023 | up 97.8% | volatile |
| 151 | Burkina Faso | -21 1000 t | 2023 | up 30.0% | volatile |
| 152 | Kenya | -27 1000 t | 2023 | down 640.0% | volatile |
| 153 | Ethiopia | -30 1000 t | 2023 | up 70.0% | volatile |
| 154 | Argentina | -40 1000 t | 2023 | up 57.0% | volatile |
| 155 | Mexico | -56 1000 t | 2023 | down 307.4% | volatile |
| 156 | Niger | -75 1000 t | 2023 | down 266.7% | volatile |
| 157 | India | -123 1000 t | 2023 | down 1,657.1% | volatile |
| 158 | Australia | -258 1000 t | 2023 | down 2,245.4% | volatile |
| 158 | Australia and New Zealand | -258 1000 t | 2023 | down 2,245.4% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Americas 121 1000 t
- South America 100 1000 t
- Northern America 76 1000 t
- United States of America 74 1000 t
- Eastern Asia 27 1000 t
- South Africa 23 1000 t
- Western Asia 17 1000 t
- Southern Africa 16 1000 t
- Eastern Europe 12 1000 t
- Small island developing States (SIDS) 1 1000 t
- Central Asia 0 1000 t
- Western Europe 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.