Treenuts — 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
Treenuts — Stock Variation is currently reported for 182 countries. The highest value is 196 1000 t in India; the lowest is -108 1000 t in Côte d'Ivoire.
The median across all reporting countries is 0 1000 t, and the mean is 3.56 1000 t.
The gap between the highest and lowest reporting country is a factor of about 2.
Over the past decade 36 countries rose and 29 fell. The largest increase was in Viet Nam (up 7,750.0%), and the largest decrease in Belgium (down 1,200.0%).
Treenuts — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 196 1000 t | 2023 | up 444.4% | volatile |
| 2 | Viet Nam | 153 1000 t | 2023 | up 7,750.0% | volatile |
| 3 | China, mainland | 47 1000 t | 2023 | up 4,800.0% | volatile |
| 4 | China | 46 1000 t | 2023 | up 557.1% | volatile |
| 5 | Zimbabwe | 35 1000 t | 2023 | — | volatile |
| 6 | Myanmar | 34 1000 t | 2023 | up 3,500.0% | volatile |
| 6 | Türkiye | 34 1000 t | 2023 | up 270.0% | volatile |
| 8 | Indonesia | 33 1000 t | 2023 | up 83.3% | volatile |
| 9 | Canada | 28 1000 t | 2023 | down 20.0% | volatile |
| 10 | Sweden | 17 1000 t | 2023 | — | volatile |
| 11 | Iran (Islamic Republic of) | 14 1000 t | 2023 | up 108.7% | volatile |
| 12 | Kazakhstan | 12 1000 t | 2023 | unchanged | volatile |
| 13 | Australia | 11 1000 t | 2023 | up 161.1% | volatile |
| 13 | Switzerland | 11 1000 t | 2023 | — | volatile |
| 13 | Romania | 11 1000 t | 2023 | up 1,000.0% | volatile |
| 13 | Australia and New Zealand | 11 1000 t | 2023 | up 144.0% | volatile |
| 13 | Democratic People's Republic of Korea | 11 1000 t | 2018 | — | volatile |
| 18 | Saudi Arabia | 9 1000 t | 2023 | down 50.0% | volatile |
| 19 | Algeria | 8 1000 t | 2023 | up 700.0% | volatile |
| 19 | Finland | 8 1000 t | 2023 | up 700.0% | volatile |
| 21 | Russian Federation | 7 1000 t | 2023 | — | volatile |
| 22 | Morocco | 6 1000 t | 2023 | up 200.0% | volatile |
| 23 | Spain | 5 1000 t | 2023 | up 106.0% | volatile |
| 23 | Kyrgyzstan | 5 1000 t | 2023 | — | volatile |
| 23 | Madagascar | 5 1000 t | 2023 | up 400.0% | volatile |
| 23 | Portugal | 5 1000 t | 2023 | up 66.7% | volatile |
| 23 | Thailand | 5 1000 t | 2023 | down 16.7% | volatile |
| 23 | Republic of Korea | 5 1000 t | 2023 | down 86.8% | volatile |
| 29 | Afghanistan | 4 1000 t | 2023 | — | volatile |
| 29 | Lebanon | 4 1000 t | 2023 | — | volatile |
| 31 | Germany | 3 1000 t | 2023 | — | volatile |
| 31 | Greece | 3 1000 t | 2023 | — | volatile |
| 33 | Estonia | 2 1000 t | 2023 | — | volatile |
| 33 | Ethiopia | 2 1000 t | 2023 | down 71.4% | volatile |
| 33 | Kuwait | 2 1000 t | 2023 | — | volatile |
| 33 | Libya | 2 1000 t | 2023 | down 75.0% | volatile |
| 33 | Mongolia | 2 1000 t | 2023 | up 100.0% | volatile |
| 33 | Uzbekistan | 2 1000 t | 2023 | — | volatile |
| 33 | China, Taiwan Province of | 2 1000 t | 2023 | down 71.4% | volatile |
| 33 | Netherlands (Kingdom of the) | 2 1000 t | 2023 | up 102.2% | volatile |
| 41 | Antigua and Barbuda | 1 1000 t | 2023 | — | volatile |
| 41 | Azerbaijan | 1 1000 t | 2023 | — | volatile |
| 41 | Bosnia and Herzegovina | 1 1000 t | 2023 | up 133.3% | volatile |
| 41 | Belarus | 1 1000 t | 2023 | — | volatile |
| 41 | Czechia | 1 1000 t | 2023 | up 200.0% | volatile |
| 41 | Georgia | 1 1000 t | 2023 | down 75.0% | volatile |
| 41 | Guatemala | 1 1000 t | 2023 | unchanged | volatile |
| 41 | Croatia | 1 1000 t | 2023 | — | volatile |
| 41 | Hungary | 1 1000 t | 2023 | — | volatile |
| 41 | Iraq | 1 1000 t | 2023 | unchanged | volatile |
| 41 | Italy | 1 1000 t | 2023 | — | volatile |
| 41 | Latvia | 1 1000 t | 2023 | — | volatile |
| 41 | Malaysia | 1 1000 t | 2023 | — | volatile |
| 41 | Yemen | 1 1000 t | 2023 | — | volatile |
| 41 | Republic of Moldova | 1 1000 t | 2023 | — | volatile |
| 56 | Angola | 0 1000 t | 2023 | — | flat |
| 56 | Albania | 0 1000 t | 2023 | — | volatile |
| 56 | United Arab Emirates | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | Armenia | 0 1000 t | 2023 | — | volatile |
| 56 | Austria | 0 1000 t | 2023 | down 100.0% | flat |
| 56 | Bangladesh | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Bulgaria | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | Bahrain | 0 1000 t | 2023 | — | flat |
| 56 | Bahamas | 0 1000 t | 2023 | — | flat |
| 56 | Belize | 0 1000 t | 2023 | — | flat |
| 56 | Bhutan | 0 1000 t | 2023 | — | flat |
| 56 | Botswana | 0 1000 t | 2023 | — | flat |
| 56 | Cameroon | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Congo | 0 1000 t | 2023 | — | flat |
| 56 | Comoros | 0 1000 t | 2023 | — | flat |
| 56 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 56 | Cuba | 0 1000 t | 2019 | — | flat |
| 56 | Cyprus | 0 1000 t | 2023 | — | flat |
| 56 | Djibouti | 0 1000 t | 2023 | — | flat |
| 56 | Denmark | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 56 | Ecuador | 0 1000 t | 2023 | — | flat |
| 56 | Fiji | 0 1000 t | 2023 | — | flat |
| 56 | France | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | Gabon | 0 1000 t | 2023 | — | flat |
| 56 | Ghana | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | Gambia | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | Guinea-Bissau | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | Grenada | 0 1000 t | 2023 | — | flat |
| 56 | Guyana | 0 1000 t | 2023 | — | volatile |
| 56 | Honduras | 0 1000 t | 2023 | — | flat |
| 56 | Haiti | 0 1000 t | 2023 | — | flat |
| 56 | Ireland | 0 1000 t | 2023 | — | volatile |
| 56 | Iceland | 0 1000 t | 2023 | — | volatile |
| 56 | Israel | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Jamaica | 0 1000 t | 2023 | down 100.0% | flat |
| 56 | Jordan | 0 1000 t | 2023 | — | volatile |
| 56 | Kenya | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Cambodia | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Kiribati | 0 1000 t | 2023 | — | flat |
| 56 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 56 | Liberia | 0 1000 t | 2023 | — | flat |
| 56 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 56 | Sri Lanka | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | Lesotho | 0 1000 t | 2023 | — | flat |
| 56 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 56 | Luxembourg | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Maldives | 0 1000 t | 2023 | — | volatile |
| 56 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 56 | North Macedonia | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | Malta | 0 1000 t | 2023 | — | flat |
| 56 | Montenegro | 0 1000 t | 2023 | — | flat |
| 56 | Mauritania | 0 1000 t | 2023 | — | flat |
| 56 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 56 | Malawi | 0 1000 t | 2023 | — | volatile |
| 56 | Namibia | 0 1000 t | 2023 | — | volatile |
| 56 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 56 | Niger | 0 1000 t | 2023 | — | flat |
| 56 | Nigeria | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | Nicaragua | 0 1000 t | 2023 | — | volatile |
| 56 | Norway | 0 1000 t | 2023 | — | volatile |
| 56 | Nepal | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Nauru | 0 1000 t | 2023 | — | flat |
| 56 | New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | Oman | 0 1000 t | 2023 | — | volatile |
| 56 | Panama | 0 1000 t | 2023 | — | volatile |
| 56 | Peru | 0 1000 t | 2023 | — | volatile |
| 56 | Philippines | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 56 | Poland | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Paraguay | 0 1000 t | 2023 | — | flat |
| 56 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 56 | Qatar | 0 1000 t | 2023 | — | volatile |
| 56 | Rwanda | 0 1000 t | 2023 | — | flat |
| 56 | Senegal | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 56 | Sierra Leone | 0 1000 t | 2023 | — | volatile |
| 56 | El Salvador | 0 1000 t | 2023 | — | volatile |
| 56 | Serbia | 0 1000 t | 2023 | — | flat |
| 56 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 56 | Suriname | 0 1000 t | 2023 | — | flat |
| 56 | Slovenia | 0 1000 t | 2023 | — | flat |
| 56 | Eswatini | 0 1000 t | 2023 | down 100.0% | flat |
| 56 | Seychelles | 0 1000 t | 2023 | — | flat |
| 56 | Tajikistan | 0 1000 t | 2023 | — | volatile |
| 56 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 56 | Tonga | 0 1000 t | 2023 | — | flat |
| 56 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 56 | Tunisia | 0 1000 t | 2023 | — | volatile |
| 56 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 56 | Uganda | 0 1000 t | 2023 | — | flat |
| 56 | Uruguay | 0 1000 t | 2023 | — | flat |
| 56 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 56 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 56 | Samoa | 0 1000 t | 2023 | — | flat |
| 56 | Zambia | 0 1000 t | 2023 | — | flat |
| 56 | Micronesia | 0 1000 t | 2023 | — | flat |
| 56 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 56 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 56 | Melanesia | 0 1000 t | 2023 | — | flat |
| 56 | Polynesia | 0 1000 t | 2023 | — | flat |
| 56 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 56 | Caribbean | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 56 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 56 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 56 | United Republic of Tanzania | 0 1000 t | 2023 | up 100.0% | volatile |
| 56 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | volatile |
| 56 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
| 56 | China, Macao SAR | 0 1000 t | 2023 | down 100.0% | volatile |
| 166 | Argentina | -1 1000 t | 2023 | up 50.0% | volatile |
| 166 | Barbados | -1 1000 t | 2023 | — | volatile |
| 166 | Chile | -1 1000 t | 2023 | — | volatile |
| 166 | Egypt | -1 1000 t | 2023 | down 125.0% | volatile |
| 166 | Guinea | -1 1000 t | 2023 | — | volatile |
| 166 | Pakistan | -1 1000 t | 2023 | down 114.3% | volatile |
| 166 | Slovakia | -1 1000 t | 2023 | unchanged | volatile |
| 166 | Syrian Arab Republic | -1 1000 t | 2023 | up 96.6% | volatile |
| 174 | Colombia | -3 1000 t | 2023 | — | volatile |
| 174 | China, Hong Kong SAR | -3 1000 t | 2023 | — | volatile |
| 176 | Brazil | -4 1000 t | 2023 | down 500.0% | volatile |
| 176 | Mozambique | -4 1000 t | 2023 | — | volatile |
| 176 | Ukraine | -4 1000 t | 2023 | — | volatile |
| 179 | Burkina Faso | -7 1000 t | 2023 | down 333.3% | volatile |
| 180 | Belgium | -13 1000 t | 2023 | down 1,200.0% | volatile |
| 181 | Mexico | -15 1000 t | 2023 | down 475.0% | volatile |
| 182 | Côte d'Ivoire | -108 1000 t | 2023 | down 391.9% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 690 1000 t
- Asia 568 1000 t
- South-eastern Asia 225 1000 t
- Southern Asia 214 1000 t
- Northern America 134 1000 t
- Americas 112 1000 t
- United States of America 106 1000 t
- Europe 66 1000 t
- Eastern Asia 57 1000 t
- Land Locked Developing Countries (LLDCs) 57 1000 t
- Western Asia 54 1000 t
- European Union (27) 48 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.