Sunflower seed — Food 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
Sunflower seed — Food is currently reported for 107 countries. The highest value is 90 1000 t in Uganda; the lowest is 0 1000 t in China, Macao SAR.
The median across all reporting countries is 0 1000 t, and the mean is 2.95 1000 t.
Over the past decade 13 countries rose and 12 fell. The largest increase was in Libya (up 400.0%), and the largest decrease in Jordan (down 100.0%).
Sunflower seed — Food: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Uganda | 90 1000 t | 2023 | up 52.5% | rising |
| 2 | Spain | 40 1000 t | 2023 | down 33.3% | falling |
| 3 | United Republic of Tanzania | 36 1000 t | 2023 | up 71.4% | rising |
| 4 | Myanmar | 21 1000 t | 2023 | down 38.2% | falling |
| 5 | Bulgaria | 13 1000 t | 2023 | down 7.1% | falling |
| 5 | Kazakhstan | 13 1000 t | 2023 | up 8.3% | volatile |
| 5 | Syrian Arab Republic | 13 1000 t | 2023 | up 225.0% | volatile |
| 8 | Saudi Arabia | 10 1000 t | 2023 | up 150.0% | volatile |
| 8 | Viet Nam | 10 1000 t | 2023 | — | volatile |
| 10 | Austria | 8 1000 t | 2023 | unchanged | rising |
| 11 | Iraq | 5 1000 t | 2023 | down 61.5% | volatile |
| 11 | Libya | 5 1000 t | 2023 | up 400.0% | volatile |
| 13 | Brazil | 4 1000 t | 2023 | down 50.0% | falling |
| 13 | China | 4 1000 t | 2023 | up 100.0% | rising |
| 15 | Philippines | 3 1000 t | 2023 | up 50.0% | volatile |
| 15 | Republic of Korea | 3 1000 t | 2023 | unchanged | flat |
| 15 | Republic of Moldova | 3 1000 t | 2023 | down 25.0% | falling |
| 15 | China, Taiwan Province of | 3 1000 t | 2023 | up 50.0% | rising |
| 19 | United Arab Emirates | 2 1000 t | 2023 | down 66.7% | volatile |
| 19 | Ecuador | 2 1000 t | 2023 | up 100.0% | rising |
| 19 | Kuwait | 2 1000 t | 2023 | unchanged | volatile |
| 19 | Mexico | 2 1000 t | 2023 | down 33.3% | volatile |
| 19 | New Zealand | 2 1000 t | 2023 | up 100.0% | rising |
| 19 | Paraguay | 2 1000 t | 2023 | down 71.4% | volatile |
| 19 | Slovenia | 2 1000 t | 2023 | up 100.0% | rising |
| 19 | Turkmenistan | 2 1000 t | 2023 | — | volatile |
| 19 | Australia and New Zealand | 2 1000 t | 2023 | up 100.0% | rising |
| 28 | Bahrain | 1 1000 t | 2023 | — | flat |
| 28 | Costa Rica | 1 1000 t | 2023 | unchanged | falling |
| 28 | Dominican Republic | 1 1000 t | 2023 | — | volatile |
| 28 | Guatemala | 1 1000 t | 2023 | unchanged | flat |
| 28 | Honduras | 1 1000 t | 2023 | — | volatile |
| 28 | Israel | 1 1000 t | 2023 | unchanged | falling |
| 28 | Oman | 1 1000 t | 2023 | unchanged | volatile |
| 28 | Qatar | 1 1000 t | 2023 | — | flat |
| 28 | El Salvador | 1 1000 t | 2023 | — | volatile |
| 28 | Trinidad and Tobago | 1 1000 t | 2023 | — | volatile |
| 28 | Ukraine | 1 1000 t | 2023 | — | falling |
| 28 | Zambia | 1 1000 t | 2023 | down 87.5% | volatile |
| 28 | Caribbean | 1 1000 t | 2023 | unchanged | volatile |
| 28 | Venezuela (Bolivarian Republic of) | 1 1000 t | 2023 | unchanged | volatile |
| 42 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 42 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 42 | Bangladesh | 0 1000 t | 2023 | — | flat |
| 42 | Bahamas | 0 1000 t | 2023 | — | flat |
| 42 | Belize | 0 1000 t | 2023 | — | flat |
| 42 | Barbados | 0 1000 t | 2023 | — | flat |
| 42 | Bhutan | 0 1000 t | 2023 | — | flat |
| 42 | Botswana | 0 1000 t | 2023 | — | volatile |
| 42 | Cameroon | 0 1000 t | 2023 | — | flat |
| 42 | Cuba | 0 1000 t | 2019 | — | flat |
| 42 | Cyprus | 0 1000 t | 2023 | — | flat |
| 42 | Germany | 0 1000 t | 2023 | — | flat |
| 42 | Egypt | 0 1000 t | 2023 | — | flat |
| 42 | Ethiopia | 0 1000 t | 2023 | — | flat |
| 42 | Fiji | 0 1000 t | 2023 | — | flat |
| 42 | Gabon | 0 1000 t | 2023 | — | flat |
| 42 | Guinea | 0 1000 t | 2021 | — | flat |
| 42 | Gambia | 0 1000 t | 2023 | — | flat |
| 42 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 42 | Grenada | 0 1000 t | 2023 | — | flat |
| 42 | Guyana | 0 1000 t | 2023 | — | flat |
| 42 | Haiti | 0 1000 t | 2023 | — | flat |
| 42 | Ireland | 0 1000 t | 2023 | — | volatile |
| 42 | Iceland | 0 1000 t | 2023 | — | flat |
| 42 | Jamaica | 0 1000 t | 2023 | — | flat |
| 42 | Jordan | 0 1000 t | 2023 | down 100.0% | volatile |
| 42 | Cambodia | 0 1000 t | 2023 | — | flat |
| 42 | Saint Kitts and Nevis | 0 1000 t | 2018 | — | flat |
| 42 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 42 | Lesotho | 0 1000 t | 2023 | — | flat |
| 42 | Madagascar | 0 1000 t | 2023 | — | flat |
| 42 | Maldives | 0 1000 t | 2023 | — | flat |
| 42 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 42 | Malta | 0 1000 t | 2023 | — | flat |
| 42 | Montenegro | 0 1000 t | 2023 | — | flat |
| 42 | Mongolia | 0 1000 t | 2023 | — | flat |
| 42 | Mauritius | 0 1000 t | 2023 | — | flat |
| 42 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 42 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 42 | Nicaragua | 0 1000 t | 2023 | — | flat |
| 42 | Nepal | 0 1000 t | 2023 | — | volatile |
| 42 | Panama | 0 1000 t | 2023 | — | volatile |
| 42 | Peru | 0 1000 t | 2023 | — | volatile |
| 42 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 42 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 42 | Senegal | 0 1000 t | 2023 | — | flat |
| 42 | Serbia | 0 1000 t | 2023 | down 100.0% | falling |
| 42 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 42 | Suriname | 0 1000 t | 2023 | — | flat |
| 42 | Eswatini | 0 1000 t | 2023 | — | flat |
| 42 | Seychelles | 0 1000 t | 2023 | — | flat |
| 42 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 42 | Samoa | 0 1000 t | 2023 | — | flat |
| 42 | Yemen | 0 1000 t | 2023 | — | volatile |
| 42 | Zimbabwe | 0 1000 t | 2023 | — | flat |
| 42 | Micronesia | 0 1000 t | 2023 | — | flat |
| 42 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 42 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 42 | Melanesia | 0 1000 t | 2023 | — | flat |
| 42 | Polynesia | 0 1000 t | 2023 | — | flat |
| 42 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 42 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 42 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 42 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | volatile |
| 42 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | flat |
| 42 | China, Macao SAR | 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 542 1000 t
- Net Food Importing Developing Countries (NFIDCs) 203 1000 t
- Least Developed Countries (LDCs) 199 1000 t
- Americas 191 1000 t
- Low Income Food Deficit Countries (LIFDCs) 189 1000 t
- Africa 184 1000 t
- Eastern Africa 177 1000 t
- Northern America 176 1000 t
- United States of America 176 1000 t
- Land Locked Developing Countries (LLDCs) 162 1000 t
- Asia 93 1000 t
- 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.