Sunflowerseed 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
Sunflowerseed Oil — Stock Variation is currently reported for 176 countries. The highest value is 400 1000 t in India; the lowest is -200 1000 t in Ethiopia.
The median across all reporting countries is 0 1000 t, and the mean is 4.4 1000 t.
The gap between the highest and lowest reporting country is a factor of about 2.
Over the past decade 38 countries rose and 27 fell. The largest increase was in Jordan (up 900.0%), and the largest decrease in Czechia (down 600.0%).
Sunflowerseed Oil — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 400 1000 t | 2023 | up 107.3% | volatile |
| 2 | Djibouti | 272 1000 t | 2023 | — | volatile |
| 3 | Spain | 124 1000 t | 2023 | — | volatile |
| 4 | Hungary | 95 1000 t | 2023 | up 174.8% | volatile |
| 5 | Russian Federation | 90 1000 t | 2023 | — | volatile |
| 6 | Egypt | 80 1000 t | 2023 | down 27.9% | volatile |
| 6 | Türkiye | 80 1000 t | 2023 | up 627.3% | volatile |
| 8 | Saudi Arabia | 51 1000 t | 2023 | — | volatile |
| 9 | Uzbekistan | 24 1000 t | 2023 | up 41.2% | volatile |
| 10 | Ukraine | 22 1000 t | 2023 | up 155.0% | volatile |
| 11 | Mexico | 20 1000 t | 2023 | — | volatile |
| 12 | Belgium | 19 1000 t | 2023 | — | volatile |
| 13 | Libya | 18 1000 t | 2023 | — | volatile |
| 14 | Azerbaijan | 15 1000 t | 2023 | — | volatile |
| 15 | Germany | 10 1000 t | 2023 | up 66.7% | volatile |
| 15 | Greece | 10 1000 t | 2023 | up 200.0% | volatile |
| 17 | Tajikistan | 9 1000 t | 2023 | up 550.0% | volatile |
| 18 | Jordan | 8 1000 t | 2023 | up 900.0% | volatile |
| 18 | United Republic of Tanzania | 8 1000 t | 2023 | down 79.5% | volatile |
| 20 | Slovenia | 7 1000 t | 2023 | up 600.0% | volatile |
| 20 | Sweden | 7 1000 t | 2023 | up 40.0% | rising |
| 22 | Georgia | 6 1000 t | 2023 | — | volatile |
| 22 | United Kingdom of Great Britain and Northern Ireland | 6 1000 t | 2023 | — | volatile |
| 24 | Mauritius | 5 1000 t | 2023 | — | volatile |
| 24 | Pakistan | 5 1000 t | 2023 | up 350.0% | volatile |
| 26 | Thailand | 4 1000 t | 2023 | unchanged | volatile |
| 27 | Afghanistan | 3 1000 t | 2023 | up 118.8% | volatile |
| 27 | Ireland | 3 1000 t | 2023 | — | volatile |
| 27 | Oman | 3 1000 t | 2023 | unchanged | flat |
| 27 | Bolivia (Plurinational State of) | 3 1000 t | 2023 | up 110.7% | volatile |
| 31 | Bulgaria | 2 1000 t | 2023 | up 106.2% | volatile |
| 31 | Botswana | 2 1000 t | 2023 | — | volatile |
| 31 | Chile | 2 1000 t | 2023 | down 66.7% | volatile |
| 31 | Denmark | 2 1000 t | 2023 | unchanged | volatile |
| 31 | Guinea | 2 1000 t | 2023 | — | volatile |
| 31 | Indonesia | 2 1000 t | 2023 | up 300.0% | volatile |
| 31 | Latvia | 2 1000 t | 2023 | down 66.7% | volatile |
| 31 | Maldives | 2 1000 t | 2023 | — | volatile |
| 31 | Viet Nam | 2 1000 t | 2023 | — | volatile |
| 40 | Armenia | 1 1000 t | 2023 | — | volatile |
| 40 | Cyprus | 1 1000 t | 2023 | — | flat |
| 40 | Guyana | 1 1000 t | 2023 | — | volatile |
| 40 | French Polynesia | 1 1000 t | 2023 | — | volatile |
| 40 | Democratic Republic of the Congo | 1 1000 t | 2023 | up 200.0% | volatile |
| 40 | Democratic People's Republic of Korea | 1 1000 t | 2018 | — | volatile |
| 46 | Angola | 0 1000 t | 2023 | — | volatile |
| 46 | Albania | 0 1000 t | 2023 | — | volatile |
| 46 | Argentina | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 46 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 46 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 46 | Bahrain | 0 1000 t | 2023 | — | volatile |
| 46 | Bahamas | 0 1000 t | 2023 | — | flat |
| 46 | Belize | 0 1000 t | 2023 | — | flat |
| 46 | Brazil | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Barbados | 0 1000 t | 2023 | — | volatile |
| 46 | Bhutan | 0 1000 t | 2023 | — | flat |
| 46 | Canada | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | China | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Cameroon | 0 1000 t | 2023 | — | flat |
| 46 | Congo | 0 1000 t | 2023 | — | volatile |
| 46 | Colombia | 0 1000 t | 2023 | — | volatile |
| 46 | Comoros | 0 1000 t | 2023 | — | flat |
| 46 | Cuba | 0 1000 t | 2019 | — | flat |
| 46 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 46 | Algeria | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Ecuador | 0 1000 t | 2023 | — | volatile |
| 46 | Estonia | 0 1000 t | 2023 | — | volatile |
| 46 | Finland | 0 1000 t | 2023 | — | volatile |
| 46 | Fiji | 0 1000 t | 2023 | — | flat |
| 46 | Gabon | 0 1000 t | 2023 | — | flat |
| 46 | Ghana | 0 1000 t | 2023 | — | volatile |
| 46 | Gambia | 0 1000 t | 2023 | — | flat |
| 46 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 46 | Grenada | 0 1000 t | 2023 | — | flat |
| 46 | Honduras | 0 1000 t | 2023 | — | flat |
| 46 | Haiti | 0 1000 t | 2023 | — | flat |
| 46 | Iceland | 0 1000 t | 2023 | — | flat |
| 46 | Jamaica | 0 1000 t | 2023 | — | flat |
| 46 | Kenya | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Kyrgyzstan | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Cambodia | 0 1000 t | 2023 | — | flat |
| 46 | Kiribati | 0 1000 t | 2023 | — | flat |
| 46 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 46 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 46 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 46 | Lesotho | 0 1000 t | 2023 | — | volatile |
| 46 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 46 | Morocco | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Madagascar | 0 1000 t | 2023 | — | flat |
| 46 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 46 | Malta | 0 1000 t | 2023 | — | flat |
| 46 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 46 | Mongolia | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Mozambique | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Mauritania | 0 1000 t | 2023 | — | flat |
| 46 | Malawi | 0 1000 t | 2023 | — | volatile |
| 46 | Namibia | 0 1000 t | 2023 | — | volatile |
| 46 | Niger | 0 1000 t | 2023 | — | flat |
| 46 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 46 | Nicaragua | 0 1000 t | 2023 | — | flat |
| 46 | Norway | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Nepal | 0 1000 t | 2023 | — | volatile |
| 46 | Nauru | 0 1000 t | 2023 | — | flat |
| 46 | New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Panama | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Peru | 0 1000 t | 2023 | — | volatile |
| 46 | Philippines | 0 1000 t | 2023 | — | flat |
| 46 | Papua New Guinea | 0 1000 t | 2023 | — | volatile |
| 46 | Poland | 0 1000 t | 2023 | — | volatile |
| 46 | Paraguay | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Rwanda | 0 1000 t | 2023 | — | flat |
| 46 | Senegal | 0 1000 t | 2023 | — | volatile |
| 46 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 46 | El Salvador | 0 1000 t | 2023 | up 100.0% | flat |
| 46 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 46 | Suriname | 0 1000 t | 2023 | — | volatile |
| 46 | Eswatini | 0 1000 t | 2023 | down 100.0% | flat |
| 46 | Seychelles | 0 1000 t | 2023 | — | volatile |
| 46 | Turkmenistan | 0 1000 t | 2023 | — | volatile |
| 46 | Tonga | 0 1000 t | 2023 | — | flat |
| 46 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 46 | Tunisia | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 46 | Uganda | 0 1000 t | 2023 | — | flat |
| 46 | Uruguay | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 46 | Samoa | 0 1000 t | 2023 | — | volatile |
| 46 | Yemen | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Zambia | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Zimbabwe | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Micronesia | 0 1000 t | 2023 | — | flat |
| 46 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 46 | Melanesia | 0 1000 t | 2023 | — | volatile |
| 46 | Polynesia | 0 1000 t | 2023 | — | volatile |
| 46 | Caribbean | 0 1000 t | 2023 | — | volatile |
| 46 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 46 | Republic of Korea | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | flat |
| 46 | China, mainland | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Côte d'Ivoire | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | China, Taiwan Province of | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
| 144 | France | -1 1000 t | 2023 | down 105.0% | volatile |
| 144 | Guatemala | -1 1000 t | 2023 | — | volatile |
| 144 | Kuwait | -1 1000 t | 2023 | — | volatile |
| 144 | Lithuania | -1 1000 t | 2023 | — | volatile |
| 144 | North Macedonia | -1 1000 t | 2023 | — | volatile |
| 144 | Montenegro | -1 1000 t | 2023 | — | volatile |
| 144 | New Caledonia | -1 1000 t | 2023 | — | volatile |
| 144 | Serbia | -1 1000 t | 2023 | up 96.8% | volatile |
| 152 | Switzerland | -2 1000 t | 2023 | — | volatile |
| 152 | Costa Rica | -2 1000 t | 2023 | down 100.0% | flat |
| 152 | Qatar | -2 1000 t | 2023 | — | volatile |
| 155 | Kazakhstan | -4 1000 t | 2023 | — | volatile |
| 155 | Portugal | -4 1000 t | 2023 | up 71.4% | volatile |
| 155 | Syrian Arab Republic | -4 1000 t | 2023 | — | volatile |
| 158 | Austria | -5 1000 t | 2023 | down 150.0% | volatile |
| 158 | Croatia | -5 1000 t | 2023 | down 200.0% | volatile |
| 158 | Slovakia | -5 1000 t | 2023 | up 16.7% | volatile |
| 161 | Republic of Moldova | -8 1000 t | 2023 | down 366.7% | volatile |
| 162 | Israel | -9 1000 t | 2023 | down 400.0% | volatile |
| 163 | United Arab Emirates | -10 1000 t | 2023 | down 150.0% | volatile |
| 163 | Czechia | -10 1000 t | 2023 | down 600.0% | volatile |
| 165 | Lebanon | -11 1000 t | 2023 | down 37.5% | volatile |
| 166 | Malaysia | -13 1000 t | 2023 | — | volatile |
| 167 | Belarus | -14 1000 t | 2023 | down 600.0% | volatile |
| 167 | Italy | -14 1000 t | 2023 | — | volatile |
| 169 | Bosnia and Herzegovina | -15 1000 t | 2023 | — | volatile |
| 170 | Australia | -20 1000 t | 2023 | down 322.2% | volatile |
| 170 | Australia and New Zealand | -20 1000 t | 2023 | down 322.2% | volatile |
| 172 | Iran (Islamic Republic of) | -45 1000 t | 2023 | up 47.1% | volatile |
| 173 | Iraq | -61 1000 t | 2023 | down 176.2% | volatile |
| 174 | Netherlands (Kingdom of the) | -65 1000 t | 2023 | — | volatile |
| 175 | Romania | -100 1000 t | 2023 | down 69.5% | volatile |
| 176 | Ethiopia | -200 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 789 1000 t
- Asia 455 1000 t
- Southern Asia 364 1000 t
- Africa 192 1000 t
- Net Food Importing Developing Countries (NFIDCs) 188 1000 t
- Europe 146 1000 t
- Northern Africa 99 1000 t
- Southern Europe 99 1000 t
- Least Developed Countries (LDCs) 87 1000 t
- Eastern Africa 85 1000 t
- European Union (27) 72 1000 t
- Eastern Europe 72 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.