Rape and Mustard Oil — 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
Rape and Mustard Oil — Food is currently reported for 145 countries. The highest value is 3,500 1000 t in India; the lowest is 0 1000 t in Micronesia (Federated States of).
The median across all reporting countries is 0 1000 t, and the mean is 86.64 1000 t.
Over the past decade 32 countries rose and 25 fell. The largest increase was in Philippines (up 2,400.0%), and the largest decrease in Afghanistan (down 100.0%).
Rape and Mustard Oil — Food: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 3,500 1000 t | 2023 | up 49.2% | rising |
| 2 | China | 2,242 1000 t | 2023 | up 17.3% | rising |
| 3 | China, mainland | 2,240 1000 t | 2023 | up 17.9% | rising |
| 4 | United Kingdom of Great Britain and Northern Ireland | 650 1000 t | 2023 | up 46.4% | rising |
| 5 | Canada | 585 1000 t | 2023 | up 47.4% | rising |
| 6 | Germany | 473 1000 t | 2023 | up 14.0% | rising |
| 7 | Pakistan | 350 1000 t | 2023 | up 337.5% | rising |
| 8 | Australia and New Zealand | 340 1000 t | 2023 | up 75.3% | rising |
| 9 | Australia | 326 1000 t | 2023 | up 77.2% | rising |
| 10 | Bangladesh | 226 1000 t | 2023 | up 96.5% | rising |
| 11 | France | 192 1000 t | 2023 | down 2.0% | flat |
| 12 | Republic of Korea | 152 1000 t | 2023 | up 55.1% | rising |
| 13 | Poland | 144 1000 t | 2023 | up 2.9% | flat |
| 14 | Czechia | 132 1000 t | 2023 | up 10.9% | rising |
| 15 | Mexico | 122 1000 t | 2023 | down 37.4% | falling |
| 16 | Iran (Islamic Republic of) | 117 1000 t | 2023 | up 46.2% | rising |
| 17 | Nepal | 88 1000 t | 2023 | up 35.4% | rising |
| 18 | Russian Federation | 83 1000 t | 2023 | up 1,560.0% | volatile |
| 19 | Austria | 76 1000 t | 2023 | down 3.8% | falling |
| 20 | United Arab Emirates | 60 1000 t | 2023 | up 1,900.0% | volatile |
| 21 | Switzerland | 52 1000 t | 2023 | up 44.4% | rising |
| 21 | Israel | 52 1000 t | 2023 | down 10.3% | flat |
| 23 | Slovakia | 48 1000 t | 2023 | up 140.0% | rising |
| 24 | Hungary | 33 1000 t | 2023 | up 37.5% | rising |
| 25 | Kazakhstan | 29 1000 t | 2023 | up 20.8% | falling |
| 26 | Chile | 26 1000 t | 2023 | down 13.3% | rising |
| 27 | Philippines | 25 1000 t | 2023 | up 2,400.0% | volatile |
| 27 | Sweden | 25 1000 t | 2023 | up 25.0% | rising |
| 29 | Malaysia | 21 1000 t | 2023 | up 40.0% | volatile |
| 30 | Ireland | 17 1000 t | 2023 | up 30.8% | rising |
| 31 | New Zealand | 14 1000 t | 2023 | up 55.6% | rising |
| 32 | Algeria | 12 1000 t | 2023 | up 200.0% | volatile |
| 33 | Latvia | 10 1000 t | 2023 | down 23.1% | rising |
| 34 | Belarus | 9 1000 t | 2023 | down 80.9% | falling |
| 34 | Tunisia | 9 1000 t | 2023 | — | volatile |
| 34 | Viet Nam | 9 1000 t | 2023 | up 200.0% | volatile |
| 37 | Saudi Arabia | 8 1000 t | 2023 | up 166.7% | volatile |
| 38 | Ethiopia | 7 1000 t | 2023 | down 73.1% | volatile |
| 38 | Tajikistan | 7 1000 t | 2023 | — | volatile |
| 40 | Italy | 6 1000 t | 2023 | down 45.5% | falling |
| 40 | Ukraine | 6 1000 t | 2023 | down 40.0% | volatile |
| 42 | Spain | 5 1000 t | 2023 | unchanged | flat |
| 43 | Dominican Republic | 4 1000 t | 2023 | unchanged | rising |
| 43 | Estonia | 4 1000 t | 2023 | up 33.3% | rising |
| 46 | Argentina | 3 1000 t | 2023 | up 50.0% | rising |
| 46 | Kenya | 3 1000 t | 2023 | — | volatile |
| 48 | Colombia | 2 1000 t | 2023 | down 71.4% | rising |
| 48 | Mongolia | 2 1000 t | 2023 | up 100.0% | volatile |
| 48 | Qatar | 2 1000 t | 2023 | — | rising |
| 48 | China, Macao SAR | 2 1000 t | 2023 | down 50.0% | falling |
| 52 | Bahrain | 1 1000 t | 2023 | — | flat |
| 52 | Cyprus | 1 1000 t | 2023 | unchanged | falling |
| 52 | Fiji | 1 1000 t | 2023 | unchanged | rising |
| 52 | Jordan | 1 1000 t | 2023 | — | volatile |
| 52 | Lebanon | 1 1000 t | 2023 | down 50.0% | falling |
| 52 | Morocco | 1 1000 t | 2023 | down 83.3% | volatile |
| 52 | Malta | 1 1000 t | 2023 | — | volatile |
| 52 | Mauritius | 1 1000 t | 2023 | — | volatile |
| 52 | Nigeria | 1 1000 t | 2023 | — | volatile |
| 52 | Panama | 1 1000 t | 2023 | down 50.0% | falling |
| 52 | Uzbekistan | 1 1000 t | 2023 | unchanged | volatile |
| 52 | Melanesia | 1 1000 t | 2023 | down 50.0% | rising |
| 52 | Republic of Moldova | 1 1000 t | 2023 | down 50.0% | volatile |
| 65 | Afghanistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 65 | Angola | 0 1000 t | 2023 | down 100.0% | volatile |
| 65 | Albania | 0 1000 t | 2023 | — | flat |
| 65 | Armenia | 0 1000 t | 2023 | — | flat |
| 65 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 65 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 65 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 65 | Bhutan | 0 1000 t | 2023 | — | flat |
| 65 | Botswana | 0 1000 t | 2023 | — | volatile |
| 65 | Cameroon | 0 1000 t | 2023 | — | flat |
| 65 | Congo | 0 1000 t | 2023 | — | flat |
| 65 | Comoros | 0 1000 t | 2023 | — | flat |
| 65 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 65 | Denmark | 0 1000 t | 2023 | — | flat |
| 65 | Ecuador | 0 1000 t | 2023 | — | flat |
| 65 | Finland | 0 1000 t | 2023 | — | flat |
| 65 | Gabon | 0 1000 t | 2023 | — | flat |
| 65 | Georgia | 0 1000 t | 2023 | — | flat |
| 65 | Ghana | 0 1000 t | 2023 | — | volatile |
| 65 | Guinea | 0 1000 t | 2023 | — | flat |
| 65 | Gambia | 0 1000 t | 2023 | — | flat |
| 65 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 65 | Grenada | 0 1000 t | 2023 | — | flat |
| 65 | Guatemala | 0 1000 t | 2023 | — | flat |
| 65 | Indonesia | 0 1000 t | 2023 | — | flat |
| 65 | Iraq | 0 1000 t | 2023 | — | volatile |
| 65 | Kyrgyzstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 65 | Cambodia | 0 1000 t | 2023 | — | flat |
| 65 | Kiribati | 0 1000 t | 2023 | — | flat |
| 65 | Liberia | 0 1000 t | 2023 | — | flat |
| 65 | Libya | 0 1000 t | 2023 | — | flat |
| 65 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 65 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 65 | Lesotho | 0 1000 t | 2023 | — | flat |
| 65 | Luxembourg | 0 1000 t | 2023 | down 100.0% | volatile |
| 65 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 65 | Maldives | 0 1000 t | 2023 | — | flat |
| 65 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 65 | Myanmar | 0 1000 t | 2023 | — | flat |
| 65 | Montenegro | 0 1000 t | 2023 | — | flat |
| 65 | Mozambique | 0 1000 t | 2023 | — | flat |
| 65 | Mauritania | 0 1000 t | 2023 | down 100.0% | volatile |
| 65 | Malawi | 0 1000 t | 2023 | — | flat |
| 65 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 65 | Niger | 0 1000 t | 2023 | — | flat |
| 65 | Nauru | 0 1000 t | 2023 | — | flat |
| 65 | Oman | 0 1000 t | 2023 | — | volatile |
| 65 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 65 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 65 | Rwanda | 0 1000 t | 2023 | — | flat |
| 65 | Senegal | 0 1000 t | 2023 | — | flat |
| 65 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 65 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 65 | El Salvador | 0 1000 t | 2023 | — | flat |
| 65 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 65 | Eswatini | 0 1000 t | 2023 | — | flat |
| 65 | Seychelles | 0 1000 t | 2023 | — | flat |
| 65 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 65 | Tonga | 0 1000 t | 2023 | — | flat |
| 65 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 65 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 65 | Uganda | 0 1000 t | 2023 | — | flat |
| 65 | Uruguay | 0 1000 t | 2023 | — | flat |
| 65 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 65 | Samoa | 0 1000 t | 2023 | — | flat |
| 65 | Yemen | 0 1000 t | 2023 | down 100.0% | volatile |
| 65 | Zambia | 0 1000 t | 2023 | — | flat |
| 65 | Zimbabwe | 0 1000 t | 2023 | — | flat |
| 65 | Micronesia | 0 1000 t | 2023 | — | flat |
| 65 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 65 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 65 | Polynesia | 0 1000 t | 2023 | — | flat |
| 65 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 65 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 65 | China, Hong Kong SAR | 0 1000 t | 2023 | down 100.0% | flat |
| 65 | Syrian Arab Republic | 0 1000 t | 2023 | — | volatile |
| 65 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 65 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 65 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 65 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 65 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | flat |
| 65 | Micronesia (Federated States of) | 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 11,577 1000 t
- Asia 7,541 1000 t
- Southern Asia 4,282 1000 t
- Eastern Asia 3,040 1000 t
- Europe 1,972 1000 t
- Americas 1,690 1000 t
- Northern America 1,532 1000 t
- European Union (27) 1,171 1000 t
- United States of America 947 1000 t
- Western Europe 793 1000 t
- Northern Europe 707 1000 t
- Net Food Importing Developing Countries (NFIDCs) 693 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.