Oilcrops, Other — Feed 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
Oilcrops, Other — Feed is currently reported for 124 countries. The highest value is 398 1000 t in China; the lowest is 0 1000 t in Venezuela (Bolivarian Republic of).
The median across all reporting countries is 2 1000 t, and the mean is 28.49 1000 t.
Over the past decade 37 countries rose and 32 fell. The largest increase was in Bolivia (Plurinational State of) (up 7,100.0%), and the largest decrease in Denmark (down 100.0%).
Oilcrops, Other — Feed: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 398 1000 t | 2023 | up 92.3% | flat |
| 2 | Pakistan | 390 1000 t | 2023 | up 41.3% | rising |
| 3 | China, mainland | 355 1000 t | 2023 | up 91.9% | falling |
| 4 | Vietnam | 272 1000 t | 2023 | — | volatile |
| 4 | Viet Nam | 272 1000 t | 2023 | — | volatile |
| 6 | India | 240 1000 t | 2023 | up 96.7% | falling |
| 7 | Russia | 235 1000 t | 2023 | up 111.7% | volatile |
| 7 | Russian Federation | 235 1000 t | 2023 | up 111.7% | volatile |
| 9 | Belgium | 142 1000 t | 2023 | up 82.1% | rising |
| 10 | Peru | 82 1000 t | 2023 | — | volatile |
| 11 | Bolivia (Plurinational State of) | 72 1000 t | 2023 | up 7,100.0% | volatile |
| 12 | Turkey | 65 1000 t | 2023 | up 22.6% | volatile |
| 12 | Türkiye | 65 1000 t | 2023 | up 22.6% | volatile |
| 14 | Kazakhstan | 44 1000 t | 2023 | down 70.7% | rising |
| 15 | China, Taiwan Province of | 43 1000 t | 2023 | up 95.5% | rising |
| 16 | Tajikistan | 42 1000 t | 2023 | up 2,000.0% | volatile |
| 17 | Niger | 41 1000 t | 2023 | up 51.9% | rising |
| 18 | Canada | 35 1000 t | 2023 | — | volatile |
| 19 | Ghana | 32 1000 t | 2023 | — | volatile |
| 19 | Ukraine | 32 1000 t | 2023 | up 28.0% | rising |
| 21 | Bulgaria | 29 1000 t | 2023 | up 2,800.0% | volatile |
| 22 | Serbia | 28 1000 t | 2023 | up 2,700.0% | volatile |
| 23 | Zimbabwe | 22 1000 t | 2023 | up 10.0% | rising |
| 24 | Malaysia | 19 1000 t | 2023 | down 71.2% | volatile |
| 24 | Uzbekistan | 19 1000 t | 2023 | up 533.3% | volatile |
| 26 | Democratic Republic of the Congo | 18 1000 t | 2023 | up 125.0% | volatile |
| 27 | Mexico | 17 1000 t | 2023 | down 22.7% | falling |
| 28 | Czechia | 16 1000 t | 2023 | — | volatile |
| 29 | Sweden | 15 1000 t | 2023 | up 15.4% | rising |
| 30 | United Republic of Tanzania | 14 1000 t | 2023 | up 16.7% | rising |
| 31 | France | 13 1000 t | 2023 | down 75.0% | falling |
| 31 | Australia and New Zealand | 13 1000 t | 2023 | up 62.5% | falling |
| 33 | Australia | 12 1000 t | 2023 | up 200.0% | volatile |
| 33 | Iceland | 12 1000 t | 2023 | up 100.0% | rising |
| 35 | Argentina | 11 1000 t | 2023 | up 175.0% | volatile |
| 35 | Chile | 11 1000 t | 2023 | up 1,000.0% | volatile |
| 37 | Azerbaijan | 10 1000 t | 2023 | up 25.0% | falling |
| 37 | Eswatini | 10 1000 t | 2023 | — | volatile |
| 39 | United Kingdom | 9 1000 t | 2023 | down 10.0% | flat |
| 39 | United Kingdom of Great Britain and Northern Ireland | 9 1000 t | 2023 | down 10.0% | flat |
| 41 | Kyrgyzstan | 8 1000 t | 2023 | down 38.5% | falling |
| 41 | Lithuania | 8 1000 t | 2023 | up 100.0% | rising |
| 41 | Romania | 8 1000 t | 2023 | up 700.0% | volatile |
| 44 | Afghanistan | 6 1000 t | 2023 | — | volatile |
| 44 | Cote d'Ivoire | 6 1000 t | 2023 | up 500.0% | volatile |
| 44 | Paraguay | 6 1000 t | 2023 | up 20.0% | rising |
| 44 | United States | 6 1000 t | 2023 | down 73.9% | volatile |
| 44 | Côte d'Ivoire | 6 1000 t | 2023 | up 500.0% | volatile |
| 49 | Spain | 5 1000 t | 2023 | down 37.5% | falling |
| 50 | Austria | 4 1000 t | 2023 | down 33.3% | volatile |
| 50 | Switzerland | 4 1000 t | 2023 | down 33.3% | falling |
| 50 | Dominican Republic | 4 1000 t | 2023 | — | volatile |
| 50 | Guyana | 4 1000 t | 2023 | — | volatile |
| 50 | Namibia | 4 1000 t | 2023 | — | volatile |
| 50 | Thailand | 4 1000 t | 2023 | up 300.0% | volatile |
| 50 | Caribbean | 4 1000 t | 2023 | — | volatile |
| 57 | Germany | 3 1000 t | 2023 | — | volatile |
| 57 | Estonia | 3 1000 t | 2023 | up 200.0% | volatile |
| 57 | Madagascar | 3 1000 t | 2023 | up 50.0% | rising |
| 57 | Poland | 3 1000 t | 2023 | — | volatile |
| 57 | South Africa | 3 1000 t | 2023 | up 50.0% | rising |
| 62 | United Arab Emirates | 2 1000 t | 2023 | — | volatile |
| 62 | Belarus | 2 1000 t | 2023 | down 33.3% | falling |
| 62 | Brazil | 2 1000 t | 2023 | down 50.0% | volatile |
| 62 | Cameroon | 2 1000 t | 2023 | up 100.0% | falling |
| 62 | Iraq | 2 1000 t | 2023 | — | volatile |
| 62 | Mozambique | 2 1000 t | 2023 | down 33.3% | volatile |
| 62 | Philippines | 2 1000 t | 2023 | down 86.7% | volatile |
| 62 | Slovakia | 2 1000 t | 2023 | — | volatile |
| 62 | Slovenia | 2 1000 t | 2023 | — | volatile |
| 62 | Iran (Islamic Republic of) | 2 1000 t | 2023 | down 86.7% | volatile |
| 62 | Netherlands (Kingdom of the) | 2 1000 t | 2023 | down 50.0% | volatile |
| 73 | Congo | 1 1000 t | 2023 | — | volatile |
| 73 | Colombia | 1 1000 t | 2023 | — | volatile |
| 73 | Egypt | 1 1000 t | 2023 | — | volatile |
| 73 | Ethiopia | 1 1000 t | 2023 | down 66.7% | rising |
| 73 | Finland | 1 1000 t | 2023 | — | volatile |
| 73 | Gambia | 1 1000 t | 2023 | unchanged | volatile |
| 73 | Hungary | 1 1000 t | 2023 | unchanged | volatile |
| 73 | Ireland | 1 1000 t | 2023 | down 66.7% | falling |
| 73 | Jordan | 1 1000 t | 2023 | unchanged | volatile |
| 73 | New Zealand | 1 1000 t | 2023 | down 80.0% | volatile |
| 83 | Angola | 0 1000 t | 2023 | — | volatile |
| 83 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 83 | Belize | 0 1000 t | 2023 | — | volatile |
| 83 | Cyprus | 0 1000 t | 2023 | — | volatile |
| 83 | Denmark | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Algeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Georgia | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Greece | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Croatia | 0 1000 t | 2023 | — | volatile |
| 83 | Haiti | 0 1000 t | 2023 | — | volatile |
| 83 | Indonesia | 0 1000 t | 2023 | — | volatile |
| 83 | Italy | 0 1000 t | 2023 | — | volatile |
| 83 | Kenya | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Kuwait | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Lebanon | 0 1000 t | 2023 | — | volatile |
| 83 | Liberia | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 83 | Lesotho | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Latvia | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 83 | Malta | 0 1000 t | 2023 | — | volatile |
| 83 | Montenegro | 0 1000 t | 2023 | — | volatile |
| 83 | Mauritania | 0 1000 t | 2023 | — | volatile |
| 83 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 83 | Nepal | 0 1000 t | 2023 | — | volatile |
| 83 | Oman | 0 1000 t | 2023 | — | volatile |
| 83 | Panama | 0 1000 t | 2023 | — | volatile |
| 83 | Papua New Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Portugal | 0 1000 t | 2023 | — | volatile |
| 83 | French Polynesia | 0 1000 t | 2023 | — | volatile |
| 83 | Rwanda | 0 1000 t | 2023 | — | volatile |
| 83 | Senegal | 0 1000 t | 2023 | — | volatile |
| 83 | Sierra Leone | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Syria | 0 1000 t | 2023 | — | volatile |
| 83 | Trinidad and Tobago | 0 1000 t | 2023 | — | volatile |
| 83 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 83 | Yemen | 0 1000 t | 2023 | — | volatile |
| 83 | Melanesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 83 | Polynesia | 0 1000 t | 2023 | — | volatile |
| 83 | Republic of Korea | 0 1000 t | 2023 | — | volatile |
| 83 | Syrian Arab Republic | 0 1000 t | 2023 | — | volatile |
| 83 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2022 | — | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 2,587 1000 t
- Asia 1,529 1000 t
- Southern Asia 637 1000 t
- Net Food Importing Developing Countries (NFIDCs) 636 1000 t
- Europe 581 1000 t
- Eastern Asia 400 1000 t
- Land Locked Developing Countries (LLDCs) 331 1000 t
- Eastern Europe 328 1000 t
- South-Eastern Asia 298 1000 t
- European Union (27) 258 1000 t
- Americas 250 1000 t
- Low Income Food Deficit Countries (LIFDCs) 233 1000 t
- Africa 214 1000 t
- South America 188 1000 t
- Western Europe 168 1000 t
- Least Developed Countries (LDCs) 140 1000 t
- Central Asia 114 1000 t
- Western Africa 114 1000 t
- Western Asia 81 1000 t
- Northern Europe 49 1000 t
- Northern America 41 1000 t
- Eastern Africa 41 1000 t
- Middle Africa 40 1000 t
- Southern Europe 35 1000 t
- Southern Africa 17 1000 t
- Central America 17 1000 t
- Oceania 13 1000 t
- Small island developing States (SIDS) 9 1000 t
- United States of America 6 1000 t
- Northern Africa 1 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.