Oilcrops — Residuals 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...
Countries reporting
157
Highest
373 1000 t
Senegal
Lowest
-4,053 1000 t
Brazil
Median
-2 1000 t
Years covered
14
2010–2023
Data points
3,046
What the numbers show
Oilcrops — Residuals is currently reported for 157 countries. The highest value is 373 1000 t in Senegal; the lowest is -4,053 1000 t in Brazil.
The median across all reporting countries is -2 1000 t, and the mean is -88 1000 t.
Over the past decade 37 countries rose and 36 fell. The largest increase was in Syria (up 6,433.3%), and the largest decrease in Ecuador (down 37,700.0%).
Oilcrops — Residuals: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Senegal | 373 1000 t | 2023 | up 511.5% | volatile |
| 2 | Guinea | 296 1000 t | 2023 | — | volatile |
| 3 | Greece | 210 1000 t | 2023 | up 2.4% | volatile |
| 4 | Syria | 190 1000 t | 2023 | up 6,433.3% | volatile |
| 4 | Syrian Arab Republic | 190 1000 t | 2023 | up 6,433.3% | volatile |
| 6 | Vanuatu | 81 1000 t | 2023 | — | volatile |
| 7 | Uganda | 30 1000 t | 2023 | up 123.3% | volatile |
| 8 | Melanesia | 29 1000 t | 2023 | up 145.3% | volatile |
| 9 | Canada | 24 1000 t | 2023 | — | volatile |
| 10 | Hungary | 16 1000 t | 2023 | — | volatile |
| 11 | Polynesia | 14 1000 t | 2023 | — | volatile |
| 12 | French Polynesia | 13 1000 t | 2023 | — | volatile |
| 13 | Lithuania | 6 1000 t | 2023 | — | volatile |
| 14 | Peru | 3 1000 t | 2023 | up 250.0% | volatile |
| 15 | Poland | 2 1000 t | 2023 | up 122.2% | volatile |
| 16 | Algeria | 1 1000 t | 2023 | up 150.0% | volatile |
| 16 | Samoa | 1 1000 t | 2023 | — | volatile |
| 18 | Armenia | 0 1000 t | 2023 | — | volatile |
| 18 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 18 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | volatile |
| 18 | Switzerland | 0 1000 t | 2023 | — | volatile |
| 18 | Cameroon | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Colombia | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Djibouti | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Dominican Republic | 0 1000 t | 2023 | — | volatile |
| 18 | Gabon | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Guinea-Bissau | 0 1000 t | 2023 | — | volatile |
| 18 | Guyana | 0 1000 t | 2023 | — | volatile |
| 18 | Haiti | 0 1000 t | 2023 | — | volatile |
| 18 | Ireland | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Jamaica | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Kazakhstan | 0 1000 t | 2023 | — | volatile |
| 18 | Cambodia | 0 1000 t | 2023 | — | volatile |
| 18 | Kiribati | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | volatile |
| 18 | Kuwait | 0 1000 t | 2023 | up 100.0% | flat |
| 18 | Laos | 0 1000 t | 2023 | — | volatile |
| 18 | Maldives | 0 1000 t | 2023 | — | volatile |
| 18 | Marshall Islands | 0 1000 t | 2023 | — | volatile |
| 18 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 18 | Mongolia | 0 1000 t | 2023 | — | volatile |
| 18 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 18 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 18 | Oman | 0 1000 t | 2023 | — | volatile |
| 18 | Papua New Guinea | 0 1000 t | 2023 | — | volatile |
| 18 | Russia | 0 1000 t | 2023 | — | volatile |
| 18 | Rwanda | 0 1000 t | 2023 | — | volatile |
| 18 | Saudi Arabia | 0 1000 t | 2023 | — | volatile |
| 18 | Solomon Islands | 0 1000 t | 2023 | — | volatile |
| 18 | Sao Tome and Principe | 0 1000 t | 2023 | — | volatile |
| 18 | Sweden | 0 1000 t | 2023 | — | volatile |
| 18 | Tajikistan | 0 1000 t | 2023 | — | volatile |
| 18 | East Timor | 0 1000 t | 2023 | — | volatile |
| 18 | Tonga | 0 1000 t | 2023 | — | volatile |
| 18 | Uzbekistan | 0 1000 t | 2023 | — | volatile |
| 18 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Zimbabwe | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Micronesia | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Timor-Leste | 0 1000 t | 2023 | — | volatile |
| 18 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 18 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 18 | Republic of Korea | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Russian Federation | 0 1000 t | 2023 | — | volatile |
| 18 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | volatile |
| 18 | China, Taiwan Province of | 0 1000 t | 2023 | up 100.0% | volatile |
| 103 | Botswana | -1 1000 t | 2023 | down 200.0% | volatile |
| 103 | Denmark | -1 1000 t | 2023 | down 102.0% | volatile |
| 103 | Finland | -1 1000 t | 2023 | — | volatile |
| 103 | Luxembourg | -1 1000 t | 2023 | — | volatile |
| 103 | New Zealand | -1 1000 t | 2023 | — | volatile |
| 103 | Thailand | -1 1000 t | 2023 | — | volatile |
| 103 | Turkmenistan | -1 1000 t | 2023 | — | volatile |
| 110 | Belize | -2 1000 t | 2023 | — | volatile |
| 110 | Germany | -2 1000 t | 2023 | down 100.0% | volatile |
| 110 | Gambia | -2 1000 t | 2023 | — | volatile |
| 110 | Kenya | -2 1000 t | 2023 | up 94.3% | volatile |
| 110 | Nigeria | -2 1000 t | 2023 | — | volatile |
| 110 | Pakistan | -2 1000 t | 2023 | — | volatile |
| 110 | Panama | -2 1000 t | 2023 | down 300.0% | volatile |
| 110 | Philippines | -2 1000 t | 2023 | up 99.9% | volatile |
| 110 | El Salvador | -2 1000 t | 2023 | — | volatile |
| 110 | Trinidad and Tobago | -2 1000 t | 2023 | — | volatile |
| 110 | Caribbean | -2 1000 t | 2023 | up 87.5% | volatile |
| 110 | Venezuela (Bolivarian Republic of) | -2 1000 t | 2023 | up 50.0% | volatile |
| 122 | United Arab Emirates | -3 1000 t | 2023 | — | volatile |
| 122 | Argentina | -3 1000 t | 2023 | down 102.1% | volatile |
| 122 | Malawi | -3 1000 t | 2023 | — | volatile |
| 122 | Slovenia | -3 1000 t | 2023 | — | volatile |
| 122 | Vietnam | -3 1000 t | 2023 | — | volatile |
| 122 | Iran (Islamic Republic of) | -3 1000 t | 2023 | — | volatile |
| 122 | Viet Nam | -3 1000 t | 2023 | — | volatile |
| 129 | China | -4 1000 t | 2023 | up 98.5% | volatile |
| 129 | Cyprus | -4 1000 t | 2023 | down 500.0% | volatile |
| 129 | Latvia | -4 1000 t | 2023 | — | volatile |
| 129 | Norway | -4 1000 t | 2023 | up 42.9% | volatile |
| 129 | China, mainland | -4 1000 t | 2023 | unchanged | volatile |
| 134 | Afghanistan | -5 1000 t | 2023 | — | volatile |
| 134 | Estonia | -5 1000 t | 2023 | — | volatile |
| 134 | Morocco | -5 1000 t | 2023 | down 105.3% | volatile |
| 137 | Ghana | -7 1000 t | 2023 | up 95.2% | volatile |
| 137 | Jordan | -7 1000 t | 2023 | up 65.0% | volatile |
| 137 | Mexico | -7 1000 t | 2023 | down 150.0% | volatile |
| 140 | Turkey | -8 1000 t | 2023 | — | volatile |
| 140 | Türkiye | -8 1000 t | 2023 | — | volatile |
| 142 | Austria | -9 1000 t | 2023 | down 156.2% | volatile |
| 142 | Croatia | -9 1000 t | 2023 | down 350.0% | volatile |
| 144 | Costa Rica | -10 1000 t | 2023 | — | volatile |
| 144 | Democratic People's Republic of Korea | -10 1000 t | 2018 | — | volatile |
| 146 | Ethiopia | -11 1000 t | 2023 | down 1,000.0% | volatile |
| 146 | Zambia | -11 1000 t | 2023 | — | volatile |
| 148 | Myanmar | -13 1000 t | 2023 | — | volatile |
| 149 | Georgia | -15 1000 t | 2023 | — | volatile |
| 150 | Chile | -16 1000 t | 2023 | down 45.5% | volatile |
| 151 | Indonesia | -17 1000 t | 2023 | down 100.1% | volatile |
| 152 | Egypt | -22 1000 t | 2023 | up 77.3% | volatile |
| 152 | Guatemala | -22 1000 t | 2023 | down 1,000.0% | volatile |
| 154 | United Kingdom | -24 1000 t | 2023 | — | volatile |
| 154 | Nicaragua | -24 1000 t | 2023 | up 40.0% | volatile |
| 154 | United Kingdom of Great Britain and Northern Ireland | -24 1000 t | 2023 | — | volatile |
| 157 | Libya | -26 1000 t | 2023 | down 388.9% | volatile |
| 158 | Slovakia | -31 1000 t | 2023 | — | volatile |
| 159 | Albania | -34 1000 t | 2023 | — | volatile |
| 159 | Australia | -34 1000 t | 2023 | down 477.8% | volatile |
| 159 | Australia and New Zealand | -34 1000 t | 2023 | down 477.8% | volatile |
| 162 | Tunisia | -40 1000 t | 2023 | down 207.7% | volatile |
| 163 | Czechia | -43 1000 t | 2023 | — | volatile |
| 164 | Cote d'Ivoire | -48 1000 t | 2023 | up 31.4% | volatile |
| 164 | Côte d'Ivoire | -48 1000 t | 2023 | up 31.4% | volatile |
| 166 | Madagascar | -51 1000 t | 2023 | — | volatile |
| 167 | Fiji | -52 1000 t | 2023 | up 18.8% | rising |
| 168 | Moldova | -54 1000 t | 2023 | — | volatile |
| 168 | Republic of Moldova | -54 1000 t | 2023 | — | volatile |
| 170 | Serbia | -59 1000 t | 2023 | — | volatile |
| 171 | Lebanon | -63 1000 t | 2023 | — | volatile |
| 172 | Azerbaijan | -67 1000 t | 2023 | down 415.4% | falling |
| 172 | Burkina Faso | -67 1000 t | 2023 | down 2,133.3% | volatile |
| 174 | Paraguay | -68 1000 t | 2023 | down 1,260.0% | volatile |
| 175 | Israel | -79 1000 t | 2023 | down 1,875.0% | volatile |
| 175 | United States | -79 1000 t | 2023 | up 75.7% | volatile |
| 177 | United Republic of Tanzania | -90 1000 t | 2023 | up 59.6% | volatile |
| 178 | Bolivia (Plurinational State of) | -94 1000 t | 2023 | down 46.9% | volatile |
| 179 | Belgium | -111 1000 t | 2023 | down 5,650.0% | volatile |
| 180 | Mozambique | -117 1000 t | 2023 | — | volatile |
| 181 | Netherlands (Kingdom of the) | -133 1000 t | 2023 | — | volatile |
| 182 | South Africa | -226 1000 t | 2023 | down 2,411.1% | volatile |
| 183 | Uruguay | -229 1000 t | 2023 | up 75.2% | volatile |
| 184 | India | -265 1000 t | 2023 | down 13,350.0% | volatile |
| 185 | Ecuador | -378 1000 t | 2023 | down 37,700.0% | volatile |
| 186 | Honduras | -395 1000 t | 2023 | — | volatile |
| 187 | Belarus | -396 1000 t | 2023 | down 19,700.0% | volatile |
| 188 | France | -401 1000 t | 2023 | up 0.2% | volatile |
| 189 | Portugal | -696 1000 t | 2023 | down 190.0% | volatile |
| 190 | Romania | -701 1000 t | 2023 | down 7,688.9% | volatile |
| 191 | Italy | -873 1000 t | 2023 | up 42.7% | rising |
| 192 | Ukraine | -2,351 1000 t | 2023 | down 1,104.7% | volatile |
| 193 | Spain | -2,394 1000 t | 2023 | up 16.1% | falling |
| 194 | Brazil | -4,053 1000 t | 2023 | down 8,523.4% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Low Income Food Deficit Countries (LIFDCs) 1,395 1000 t
- Least Developed Countries (LDCs) 1,206 1000 t
- Africa 846 1000 t
- Net Food Importing Developing Countries (NFIDCs) 682 1000 t
- Northern Africa 648 1000 t
- Western Africa 412 1000 t
- Middle Africa 254 1000 t
- Small island developing States (SIDS) 37 1000 t
- Oceania 8 1000 t
- Central Asia -1 1000 t
- Northern Europe -34 1000 t
- South-Eastern Asia -35 1000 t
- Northern America -55 1000 t
- Eastern Asia -55 1000 t
- Western Asia -55 1000 t
- United States of America -79 1000 t
- Land Locked Developing Countries (LLDCs) -92 1000 t
- Southern Africa -227 1000 t
- Eastern Africa -241 1000 t
- Southern Asia -274 1000 t
- Asia -421 1000 t
- Central America -464 1000 t
- Western Europe -657 1000 t
- Eastern Europe -3,560 1000 t
- Southern Europe -3,857 1000 t
- South America -4,839 1000 t
- European Union (27) -5,189 1000 t
- Americas -5,361 1000 t
- Europe -8,107 1000 t
- World -13,035 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.