Soyabean Oil — 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
Soyabean Oil — Stock Variation is currently reported for 178 countries. The highest value is 235 1000 t in Russian Federation; the lowest is -278 1000 t in Brazil.
The median across all reporting countries is 0 1000 t, and the mean is 1.16 1000 t.
Over the past decade 40 countries rose and 39 fell. The largest increase was in Canada (up 20,800.0%), and the largest decrease in Angola (down 3,100.0%).
Soyabean Oil — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Russian Federation | 235 1000 t | 2023 | — | volatile |
| 2 | Canada | 207 1000 t | 2023 | up 20,800.0% | volatile |
| 3 | Spain | 153 1000 t | 2023 | up 161.2% | volatile |
| 4 | Democratic People's Republic of Korea | 60 1000 t | 2018 | up 350.0% | volatile |
| 5 | Algeria | 50 1000 t | 2023 | up 28.2% | volatile |
| 6 | Paraguay | 40 1000 t | 2023 | up 407.7% | volatile |
| 7 | Netherlands (Kingdom of the) | 26 1000 t | 2023 | up 159.1% | volatile |
| 8 | Peru | 25 1000 t | 2023 | — | volatile |
| 9 | Ecuador | 24 1000 t | 2023 | up 140.0% | volatile |
| 10 | Cuba | 14 1000 t | 2019 | — | volatile |
| 11 | Mauritania | 10 1000 t | 2023 | — | volatile |
| 12 | India | 7 1000 t | 2023 | down 63.2% | volatile |
| 13 | United Kingdom of Great Britain and Northern Ireland | 6 1000 t | 2023 | up 400.0% | volatile |
| 14 | Costa Rica | 5 1000 t | 2023 | — | volatile |
| 14 | Ghana | 5 1000 t | 2023 | up 600.0% | volatile |
| 16 | Belgium | 4 1000 t | 2023 | up 180.0% | volatile |
| 16 | Ukraine | 4 1000 t | 2023 | down 20.0% | volatile |
| 18 | Bulgaria | 3 1000 t | 2023 | up 400.0% | volatile |
| 18 | France | 3 1000 t | 2023 | — | volatile |
| 18 | Kenya | 3 1000 t | 2023 | — | volatile |
| 21 | Belarus | 2 1000 t | 2023 | up 100.0% | volatile |
| 21 | Colombia | 2 1000 t | 2023 | — | volatile |
| 21 | Czechia | 2 1000 t | 2023 | — | volatile |
| 21 | Honduras | 2 1000 t | 2023 | — | volatile |
| 21 | Mexico | 2 1000 t | 2023 | up 102.3% | volatile |
| 21 | China, Macao SAR | 2 1000 t | 2023 | — | flat |
| 27 | Australia | 1 1000 t | 2023 | — | volatile |
| 27 | Botswana | 1 1000 t | 2023 | — | volatile |
| 27 | China | 1 1000 t | 2023 | up 101.2% | volatile |
| 27 | Germany | 1 1000 t | 2023 | up 102.5% | volatile |
| 27 | Fiji | 1 1000 t | 2023 | — | volatile |
| 27 | Trinidad and Tobago | 1 1000 t | 2023 | — | volatile |
| 27 | Melanesia | 1 1000 t | 2023 | unchanged | volatile |
| 27 | Democratic Republic of the Congo | 1 1000 t | 2023 | — | volatile |
| 27 | Australia and New Zealand | 1 1000 t | 2023 | down 50.0% | volatile |
| 27 | China, Taiwan Province of | 1 1000 t | 2023 | up 102.4% | volatile |
| 37 | Afghanistan | 0 1000 t | 2023 | down 100.0% | flat |
| 37 | Albania | 0 1000 t | 2023 | — | flat |
| 37 | Armenia | 0 1000 t | 2023 | — | flat |
| 37 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 37 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 37 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 37 | Bahrain | 0 1000 t | 2023 | — | flat |
| 37 | Bahamas | 0 1000 t | 2023 | — | volatile |
| 37 | Bosnia and Herzegovina | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Belize | 0 1000 t | 2023 | — | volatile |
| 37 | Barbados | 0 1000 t | 2023 | — | flat |
| 37 | Bhutan | 0 1000 t | 2023 | — | flat |
| 37 | Switzerland | 0 1000 t | 2023 | — | flat |
| 37 | Cameroon | 0 1000 t | 2023 | — | volatile |
| 37 | Congo | 0 1000 t | 2023 | — | volatile |
| 37 | Comoros | 0 1000 t | 2023 | — | flat |
| 37 | Cyprus | 0 1000 t | 2023 | — | volatile |
| 37 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 37 | Estonia | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Ethiopia | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Gabon | 0 1000 t | 2023 | — | flat |
| 37 | Georgia | 0 1000 t | 2023 | — | volatile |
| 37 | Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Gambia | 0 1000 t | 2023 | — | flat |
| 37 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 37 | Grenada | 0 1000 t | 2023 | — | flat |
| 37 | Guyana | 0 1000 t | 2023 | — | volatile |
| 37 | Croatia | 0 1000 t | 2023 | — | volatile |
| 37 | Haiti | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Hungary | 0 1000 t | 2023 | — | volatile |
| 37 | Indonesia | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Iceland | 0 1000 t | 2023 | — | flat |
| 37 | Jamaica | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Jordan | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 37 | Cambodia | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Kiribati | 0 1000 t | 2023 | — | flat |
| 37 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 37 | Kuwait | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Lebanon | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Liberia | 0 1000 t | 2023 | — | flat |
| 37 | Libya | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 37 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 37 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 37 | Latvia | 0 1000 t | 2023 | — | volatile |
| 37 | Maldives | 0 1000 t | 2023 | — | volatile |
| 37 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 37 | Malta | 0 1000 t | 2023 | — | flat |
| 37 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 37 | Montenegro | 0 1000 t | 2023 | — | flat |
| 37 | Malawi | 0 1000 t | 2023 | — | volatile |
| 37 | Namibia | 0 1000 t | 2023 | — | volatile |
| 37 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 37 | Niger | 0 1000 t | 2023 | — | flat |
| 37 | Nigeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Nicaragua | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Nauru | 0 1000 t | 2023 | — | flat |
| 37 | New Zealand | 0 1000 t | 2023 | down 100.0% | flat |
| 37 | Philippines | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Papua New Guinea | 0 1000 t | 2023 | down 100.0% | flat |
| 37 | Poland | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 37 | Qatar | 0 1000 t | 2023 | — | flat |
| 37 | Rwanda | 0 1000 t | 2023 | — | flat |
| 37 | Saudi Arabia | 0 1000 t | 2023 | — | volatile |
| 37 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 37 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 37 | El Salvador | 0 1000 t | 2023 | — | flat |
| 37 | Serbia | 0 1000 t | 2023 | down 100.0% | flat |
| 37 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 37 | Suriname | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Slovenia | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Eswatini | 0 1000 t | 2023 | — | volatile |
| 37 | Seychelles | 0 1000 t | 2023 | — | flat |
| 37 | Tajikistan | 0 1000 t | 2023 | down 100.0% | flat |
| 37 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 37 | Tonga | 0 1000 t | 2023 | — | flat |
| 37 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 37 | Uganda | 0 1000 t | 2023 | — | flat |
| 37 | Uruguay | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Uzbekistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 37 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 37 | Samoa | 0 1000 t | 2023 | — | flat |
| 37 | Yemen | 0 1000 t | 2023 | — | flat |
| 37 | Zambia | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Zimbabwe | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Micronesia | 0 1000 t | 2023 | — | flat |
| 37 | Cabo Verde | 0 1000 t | 2023 | — | volatile |
| 37 | Polynesia | 0 1000 t | 2023 | — | flat |
| 37 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 37 | Syrian Arab Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 37 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | volatile |
| 37 | China, mainland | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Côte d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 37 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 37 | United Republic of Tanzania | 0 1000 t | 2023 | up 100.0% | volatile |
| 37 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
| 137 | Austria | -1 1000 t | 2023 | up 66.7% | volatile |
| 137 | Finland | -1 1000 t | 2023 | down 150.0% | volatile |
| 137 | Guatemala | -1 1000 t | 2023 | down 150.0% | volatile |
| 137 | Mongolia | -1 1000 t | 2023 | down 200.0% | flat |
| 137 | Romania | -1 1000 t | 2023 | up 80.0% | volatile |
| 137 | Slovakia | -1 1000 t | 2023 | up 66.7% | volatile |
| 143 | United Arab Emirates | -2 1000 t | 2023 | up 75.0% | volatile |
| 143 | Israel | -2 1000 t | 2023 | down 200.0% | volatile |
| 143 | Morocco | -2 1000 t | 2023 | up 85.7% | volatile |
| 143 | Madagascar | -2 1000 t | 2023 | — | volatile |
| 143 | Malaysia | -2 1000 t | 2023 | down 125.0% | volatile |
| 143 | Norway | -2 1000 t | 2023 | down 125.0% | volatile |
| 143 | Oman | -2 1000 t | 2023 | down 300.0% | volatile |
| 143 | Senegal | -2 1000 t | 2023 | up 90.9% | volatile |
| 143 | Sweden | -2 1000 t | 2023 | — | flat |
| 143 | China, Hong Kong SAR | -2 1000 t | 2023 | — | volatile |
| 153 | Greece | -3 1000 t | 2023 | — | volatile |
| 153 | Mauritius | -3 1000 t | 2023 | unchanged | volatile |
| 153 | Panama | -3 1000 t | 2023 | — | volatile |
| 153 | Türkiye | -3 1000 t | 2023 | up 96.4% | volatile |
| 157 | Bangladesh | -4 1000 t | 2023 | — | volatile |
| 157 | Dominican Republic | -4 1000 t | 2023 | unchanged | volatile |
| 159 | Chile | -5 1000 t | 2023 | up 28.6% | volatile |
| 159 | Ireland | -5 1000 t | 2023 | — | volatile |
| 161 | Republic of Korea | -6 1000 t | 2023 | up 25.0% | volatile |
| 162 | Denmark | -8 1000 t | 2023 | — | volatile |
| 163 | Iraq | -9 1000 t | 2023 | down 50.0% | volatile |
| 163 | Lithuania | -9 1000 t | 2023 | — | volatile |
| 165 | Italy | -10 1000 t | 2023 | up 92.3% | volatile |
| 165 | Portugal | -10 1000 t | 2023 | down 171.4% | volatile |
| 165 | Viet Nam | -10 1000 t | 2023 | down 130.3% | volatile |
| 168 | Nepal | -11 1000 t | 2023 | down 129.7% | volatile |
| 169 | Tunisia | -14 1000 t | 2023 | down 275.0% | volatile |
| 170 | Egypt | -18 1000 t | 2023 | down 131.6% | volatile |
| 170 | Bolivia (Plurinational State of) | -18 1000 t | 2023 | down 550.0% | volatile |
| 172 | Pakistan | -22 1000 t | 2023 | — | volatile |
| 173 | Mozambique | -23 1000 t | 2023 | — | volatile |
| 175 | Iran (Islamic Republic of) | -35 1000 t | 2023 | down 131.8% | volatile |
| 176 | Thailand | -40 1000 t | 2023 | down 566.7% | volatile |
| 177 | Angola | -60 1000 t | 2023 | down 3,100.0% | volatile |
| 178 | Argentina | -63 1000 t | 2023 | down 157.8% | volatile |
| 179 | Brazil | -278 1000 t | 2023 | down 717.8% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Northern America 1,371 1000 t
- World 1,269 1000 t
- United States of America 1,164 1000 t
- Americas 1,075 1000 t
- Europe 386 1000 t
- Eastern Europe 243 1000 t
- European Union (27) 141 1000 t
- Southern Europe 130 1000 t
- Western Europe 33 1000 t
- Northern Africa 16 1000 t
- Western Africa 14 1000 t
- Land Locked Developing Countries (LLDCs) 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.