Oranges, Mandarines — 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
Oranges, Mandarines — Stock Variation is currently reported for 150 countries. The highest value is 443 1000 t in Brazil; the lowest is -88 1000 t in South Africa.
The median across all reporting countries is 0 1000 t, and the mean is 4.34 1000 t.
The gap between the highest and lowest reporting country is a factor of about 5.
Over the past decade 33 countries rose and 59 fell. The largest increase was in Brazil (up 44,400.0%), and the largest decrease in South Africa (down 351.4%).
Oranges, Mandarines — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Brazil | 443 1000 t | 2023 | up 44,400.0% | volatile |
| 2 | Republic of Korea | 68 1000 t | 2023 | up 70.0% | volatile |
| 3 | Mexico | 30 1000 t | 2023 | down 3.2% | volatile |
| 4 | Czechia | 22 1000 t | 2023 | down 62.1% | volatile |
| 5 | China | 21 1000 t | 2023 | down 12.5% | volatile |
| 6 | Thailand | 19 1000 t | 2023 | up 171.4% | volatile |
| 7 | Bulgaria | 18 1000 t | 2023 | — | volatile |
| 8 | Portugal | 17 1000 t | 2023 | down 57.5% | volatile |
| 9 | China, mainland | 14 1000 t | 2023 | down 22.2% | volatile |
| 10 | United States | 13 1000 t | 2023 | down 99.7% | volatile |
| 11 | Greece | 9 1000 t | 2023 | down 70.0% | volatile |
| 12 | Caribbean | 8 1000 t | 2023 | up 300.0% | volatile |
| 12 | China, Taiwan Province of | 8 1000 t | 2023 | up 300.0% | volatile |
| 14 | Croatia | 7 1000 t | 2023 | — | volatile |
| 15 | New Zealand | 6 1000 t | 2023 | up 250.0% | volatile |
| 15 | Romania | 6 1000 t | 2023 | up 700.0% | volatile |
| 15 | Australia and New Zealand | 6 1000 t | 2023 | down 72.7% | volatile |
| 18 | Israel | 5 1000 t | 2023 | up 112.5% | volatile |
| 18 | Kuwait | 5 1000 t | 2023 | up 600.0% | volatile |
| 18 | Slovakia | 5 1000 t | 2023 | up 150.0% | volatile |
| 18 | Slovenia | 5 1000 t | 2023 | up 150.0% | volatile |
| 18 | Trinidad and Tobago | 5 1000 t | 2023 | down 16.7% | volatile |
| 18 | Ukraine | 5 1000 t | 2023 | down 54.5% | volatile |
| 24 | Bangladesh | 4 1000 t | 2023 | up 300.0% | volatile |
| 24 | Egypt | 4 1000 t | 2023 | — | volatile |
| 24 | Finland | 4 1000 t | 2023 | down 71.4% | volatile |
| 27 | Austria | 3 1000 t | 2023 | down 88.0% | volatile |
| 27 | Bahamas | 3 1000 t | 2023 | up 250.0% | volatile |
| 29 | Ghana | 2 1000 t | 2023 | — | volatile |
| 29 | Nigeria | 2 1000 t | 2023 | — | volatile |
| 31 | Bahrain | 1 1000 t | 2023 | — | volatile |
| 31 | Chile | 1 1000 t | 2023 | up 116.7% | volatile |
| 31 | Honduras | 1 1000 t | 2023 | unchanged | volatile |
| 31 | Jordan | 1 1000 t | 2023 | down 66.7% | volatile |
| 31 | Libya | 1 1000 t | 2023 | down 90.0% | volatile |
| 31 | Norway | 1 1000 t | 2023 | down 96.9% | volatile |
| 31 | Uzbekistan | 1 1000 t | 2023 | — | volatile |
| 31 | Democratic Republic of the Congo | 1 1000 t | 2023 | unchanged | volatile |
| 39 | Angola | 0 1000 t | 2023 | — | volatile |
| 39 | Albania | 0 1000 t | 2023 | — | volatile |
| 39 | Argentina | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 39 | Australia | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Azerbaijan | 0 1000 t | 2023 | down 100.0% | flat |
| 39 | Belgium | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Burkina Faso | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Bosnia and Herzegovina | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Belize | 0 1000 t | 2023 | — | volatile |
| 39 | Barbados | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Bhutan | 0 1000 t | 2023 | — | volatile |
| 39 | Botswana | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Canada | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Congo | 0 1000 t | 2023 | — | volatile |
| 39 | Colombia | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 39 | Cuba | 0 1000 t | 2019 | down 100.0% | volatile |
| 39 | Cyprus | 0 1000 t | 2023 | — | volatile |
| 39 | Germany | 0 1000 t | 2023 | — | volatile |
| 39 | Denmark | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Algeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Spain | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Estonia | 0 1000 t | 2023 | — | volatile |
| 39 | Ethiopia | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Fiji | 0 1000 t | 2023 | — | volatile |
| 39 | France | 0 1000 t | 2023 | — | volatile |
| 39 | Gabon | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | United Kingdom | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Georgia | 0 1000 t | 2023 | — | volatile |
| 39 | Guinea | 0 1000 t | 2023 | — | volatile |
| 39 | Gambia | 0 1000 t | 2023 | — | volatile |
| 39 | Guatemala | 0 1000 t | 2023 | — | volatile |
| 39 | Guyana | 0 1000 t | 2023 | — | volatile |
| 39 | Hungary | 0 1000 t | 2023 | — | volatile |
| 39 | Indonesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | India | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Ireland | 0 1000 t | 2023 | — | volatile |
| 39 | Iceland | 0 1000 t | 2023 | — | flat |
| 39 | Italy | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Jamaica | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Kenya | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Kyrgyzstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | volatile |
| 39 | Lebanon | 0 1000 t | 2023 | — | volatile |
| 39 | Saint Lucia | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 39 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 39 | Luxembourg | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Latvia | 0 1000 t | 2023 | — | volatile |
| 39 | Morocco | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Maldives | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 39 | Malta | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 39 | Montenegro | 0 1000 t | 2023 | — | volatile |
| 39 | Mongolia | 0 1000 t | 2023 | down 100.0% | flat |
| 39 | Mozambique | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 39 | Malawi | 0 1000 t | 2023 | — | volatile |
| 39 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 39 | Namibia | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | New Caledonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Niger | 0 1000 t | 2023 | — | volatile |
| 39 | Nicaragua | 0 1000 t | 2023 | — | volatile |
| 39 | Nepal | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Oman | 0 1000 t | 2023 | — | flat |
| 39 | Pakistan | 0 1000 t | 2023 | — | volatile |
| 39 | Panama | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Philippines | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Papua New Guinea | 0 1000 t | 2023 | — | volatile |
| 39 | Poland | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Paraguay | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | French Polynesia | 0 1000 t | 2023 | down 100.0% | flat |
| 39 | Qatar | 0 1000 t | 2023 | — | volatile |
| 39 | Russia | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Saudi Arabia | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Senegal | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Sierra Leone | 0 1000 t | 2023 | — | volatile |
| 39 | Serbia | 0 1000 t | 2023 | — | volatile |
| 39 | Sao Tome and Principe | 0 1000 t | 2023 | — | volatile |
| 39 | Suriname | 0 1000 t | 2023 | — | volatile |
| 39 | Sweden | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Eswatini | 0 1000 t | 2023 | — | volatile |
| 39 | Syria | 0 1000 t | 2023 | — | volatile |
| 39 | Tunisia | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Turkey | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Uruguay | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | volatile |
| 39 | Yemen | 0 1000 t | 2023 | down 100.0% | flat |
| 39 | Zambia | 0 1000 t | 2023 | — | volatile |
| 39 | Zimbabwe | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Cabo Verde | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Melanesia | 0 1000 t | 2023 | down 100.0% | flat |
| 39 | Polynesia | 0 1000 t | 2023 | — | volatile |
| 39 | China, Hong Kong SAR | 0 1000 t | 2023 | down 100.0% | flat |
| 39 | Russian Federation | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | Syrian Arab Republic | 0 1000 t | 2023 | — | volatile |
| 39 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 39 | Türkiye | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 39 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | down 100.0% | volatile |
| 39 | China, Macao SAR | 0 1000 t | 2023 | down 100.0% | volatile |
| 178 | Cote d'Ivoire | -2 1000 t | 2023 | down 300.0% | flat |
| 178 | El Salvador | -2 1000 t | 2023 | down 166.7% | volatile |
| 178 | Côte d'Ivoire | -2 1000 t | 2023 | down 300.0% | flat |
| 181 | United Arab Emirates | -9 1000 t | 2023 | up 66.7% | volatile |
| 182 | Iran (Islamic Republic of) | -21 1000 t | 2023 | unchanged | volatile |
| 183 | South Africa | -88 1000 t | 2023 | down 351.4% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 638 1000 t
- Americas 494 1000 t
- South America 444 1000 t
- Asia 112 1000 t
- Eastern Asia 105 1000 t
- Europe 101 1000 t
- European Union (27) 96 1000 t
- Eastern Europe 56 1000 t
- Southern Europe 37 1000 t
- Central America 28 1000 t
- South-Eastern Asia 19 1000 t
- Net Food Importing Developing Countries (NFIDCs) 16 1000 t
- Northern America 13 1000 t
- United States of America 13 1000 t
- Small island developing States (SIDS) 9 1000 t
- Least Developed Countries (LDCs) 8 1000 t
- Oceania 6 1000 t
- Northern Africa 5 1000 t
- Low Income Food Deficit Countries (LIFDCs) 5 1000 t
- Northern Europe 4 1000 t
- Western Asia 4 1000 t
- Western Europe 3 1000 t
- Eastern Africa 3 1000 t
- Western Africa 2 1000 t
- Land Locked Developing Countries (LLDCs) 2 1000 t
- Central Asia 1 1000 t
- Middle Africa 1 1000 t
- Southern Asia -17 1000 t
- Africa -76 1000 t
- Southern Africa -87 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.