Groundnuts — 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
Groundnuts — Stock Variation is currently reported for 177 countries. The highest value is 376 1000 t in India; the lowest is -155 1000 t in Nigeria.
The median across all reporting countries is 0 1000 t, and the mean is 5.07 1000 t.
The gap between the highest and lowest reporting country is a factor of about 2.
Over the past decade 44 countries rose and 33 fell. The largest increase was in Senegal (up 14,100.0%), and the largest decrease in Argentina (down 3,900.0%).
Groundnuts — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 376 1000 t | 2023 | down 51.1% | volatile |
| 2 | Senegal | 140 1000 t | 2023 | up 14,100.0% | volatile |
| 3 | China, mainland | 131 1000 t | 2023 | up 3,175.0% | volatile |
| 4 | China | 127 1000 t | 2023 | up 1,914.3% | volatile |
| 5 | Myanmar | 94 1000 t | 2023 | up 476.0% | volatile |
| 6 | Burkina Faso | 74 1000 t | 2023 | up 270.0% | volatile |
| 7 | Zimbabwe | 50 1000 t | 2023 | up 516.7% | volatile |
| 8 | Malawi | 49 1000 t | 2023 | — | volatile |
| 9 | Brazil | 40 1000 t | 2023 | up 217.6% | volatile |
| 10 | Viet Nam | 36 1000 t | 2023 | up 209.1% | volatile |
| 11 | Sierra Leone | 29 1000 t | 2023 | up 866.7% | volatile |
| 12 | Egypt | 28 1000 t | 2023 | up 333.3% | volatile |
| 13 | Mozambique | 25 1000 t | 2023 | up 200.0% | volatile |
| 14 | Kenya | 14 1000 t | 2023 | up 180.0% | volatile |
| 15 | Iran (Islamic Republic of) | 10 1000 t | 2023 | up 100.0% | volatile |
| 16 | Zambia | 9 1000 t | 2023 | up 117.0% | volatile |
| 16 | Netherlands (Kingdom of the) | 9 1000 t | 2023 | — | volatile |
| 18 | Ireland | 3 1000 t | 2023 | — | volatile |
| 18 | Türkiye | 3 1000 t | 2023 | up 250.0% | volatile |
| 20 | Switzerland | 2 1000 t | 2023 | up 100.0% | rising |
| 20 | Germany | 2 1000 t | 2023 | — | volatile |
| 20 | Finland | 2 1000 t | 2023 | up 300.0% | volatile |
| 20 | Jamaica | 2 1000 t | 2023 | — | volatile |
| 20 | Namibia | 2 1000 t | 2023 | — | volatile |
| 20 | Caribbean | 2 1000 t | 2023 | down 50.0% | volatile |
| 20 | Australia and New Zealand | 2 1000 t | 2023 | up 200.0% | flat |
| 27 | Austria | 1 1000 t | 2023 | unchanged | volatile |
| 27 | Bangladesh | 1 1000 t | 2023 | — | volatile |
| 27 | Guatemala | 1 1000 t | 2023 | down 50.0% | volatile |
| 27 | Kyrgyzstan | 1 1000 t | 2023 | — | volatile |
| 27 | Kuwait | 1 1000 t | 2023 | — | volatile |
| 27 | Sri Lanka | 1 1000 t | 2023 | up 150.0% | volatile |
| 27 | New Zealand | 1 1000 t | 2023 | up 150.0% | volatile |
| 27 | Oman | 1 1000 t | 2023 | — | volatile |
| 27 | Slovenia | 1 1000 t | 2023 | — | volatile |
| 27 | Thailand | 1 1000 t | 2023 | down 66.7% | volatile |
| 27 | Tajikistan | 1 1000 t | 2023 | up 200.0% | volatile |
| 27 | Uzbekistan | 1 1000 t | 2023 | up 133.3% | volatile |
| 27 | Democratic Republic of the Congo | 1 1000 t | 2023 | up 200.0% | volatile |
| 27 | Republic of Korea | 1 1000 t | 2023 | up 150.0% | volatile |
| 41 | Albania | 0 1000 t | 2023 | — | flat |
| 41 | United Arab Emirates | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Armenia | 0 1000 t | 2023 | — | flat |
| 41 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 41 | Australia | 0 1000 t | 2023 | — | volatile |
| 41 | Azerbaijan | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Belgium | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 41 | Bahrain | 0 1000 t | 2023 | — | flat |
| 41 | Bahamas | 0 1000 t | 2023 | — | flat |
| 41 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | volatile |
| 41 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Belize | 0 1000 t | 2023 | — | flat |
| 41 | Barbados | 0 1000 t | 2023 | — | flat |
| 41 | Bhutan | 0 1000 t | 2023 | — | flat |
| 41 | Botswana | 0 1000 t | 2023 | — | volatile |
| 41 | Canada | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Cameroon | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Congo | 0 1000 t | 2023 | — | flat |
| 41 | Colombia | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Comoros | 0 1000 t | 2023 | — | flat |
| 41 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 41 | Cuba | 0 1000 t | 2019 | — | flat |
| 41 | Cyprus | 0 1000 t | 2023 | — | flat |
| 41 | Denmark | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 41 | Algeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Ecuador | 0 1000 t | 2023 | — | volatile |
| 41 | Spain | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Estonia | 0 1000 t | 2023 | — | volatile |
| 41 | Fiji | 0 1000 t | 2023 | — | flat |
| 41 | France | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Gabon | 0 1000 t | 2023 | — | volatile |
| 41 | Georgia | 0 1000 t | 2023 | — | flat |
| 41 | Ghana | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Guinea | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Gambia | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Guinea-Bissau | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Greece | 0 1000 t | 2023 | — | volatile |
| 41 | Grenada | 0 1000 t | 2023 | — | flat |
| 41 | Guyana | 0 1000 t | 2023 | — | flat |
| 41 | Honduras | 0 1000 t | 2023 | — | flat |
| 41 | Croatia | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Haiti | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Hungary | 0 1000 t | 2023 | — | volatile |
| 41 | Iraq | 0 1000 t | 2023 | — | flat |
| 41 | Iceland | 0 1000 t | 2023 | — | flat |
| 41 | Israel | 0 1000 t | 2023 | — | volatile |
| 41 | Italy | 0 1000 t | 2023 | — | volatile |
| 41 | Jordan | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Cambodia | 0 1000 t | 2023 | — | volatile |
| 41 | Kiribati | 0 1000 t | 2023 | — | flat |
| 41 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | volatile |
| 41 | Lebanon | 0 1000 t | 2023 | — | volatile |
| 41 | Liberia | 0 1000 t | 2023 | — | flat |
| 41 | Libya | 0 1000 t | 2023 | — | volatile |
| 41 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 41 | Lithuania | 0 1000 t | 2023 | — | flat |
| 41 | Luxembourg | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Latvia | 0 1000 t | 2023 | — | volatile |
| 41 | Madagascar | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Maldives | 0 1000 t | 2023 | — | flat |
| 41 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 41 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 41 | Malta | 0 1000 t | 2023 | — | flat |
| 41 | Montenegro | 0 1000 t | 2023 | — | volatile |
| 41 | Mongolia | 0 1000 t | 2023 | — | volatile |
| 41 | Mauritania | 0 1000 t | 2023 | — | flat |
| 41 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 41 | Malaysia | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 41 | Niger | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Nicaragua | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Nepal | 0 1000 t | 2023 | — | flat |
| 41 | Nauru | 0 1000 t | 2023 | — | flat |
| 41 | Pakistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Panama | 0 1000 t | 2023 | — | volatile |
| 41 | Peru | 0 1000 t | 2023 | — | volatile |
| 41 | Philippines | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Papua New Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Poland | 0 1000 t | 2023 | — | flat |
| 41 | Portugal | 0 1000 t | 2023 | — | volatile |
| 41 | Paraguay | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 41 | Qatar | 0 1000 t | 2023 | — | flat |
| 41 | Romania | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Rwanda | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Saudi Arabia | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 41 | El Salvador | 0 1000 t | 2023 | — | flat |
| 41 | Serbia | 0 1000 t | 2023 | — | flat |
| 41 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 41 | Suriname | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Slovakia | 0 1000 t | 2023 | — | volatile |
| 41 | Sweden | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Eswatini | 0 1000 t | 2023 | — | volatile |
| 41 | Seychelles | 0 1000 t | 2023 | — | flat |
| 41 | Tonga | 0 1000 t | 2023 | — | flat |
| 41 | Trinidad and Tobago | 0 1000 t | 2023 | — | volatile |
| 41 | Tunisia | 0 1000 t | 2023 | — | volatile |
| 41 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 41 | Uganda | 0 1000 t | 2023 | — | flat |
| 41 | Ukraine | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Uruguay | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 41 | Vanuatu | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Samoa | 0 1000 t | 2023 | — | flat |
| 41 | Yemen | 0 1000 t | 2023 | — | volatile |
| 41 | Micronesia | 0 1000 t | 2023 | — | flat |
| 41 | Timor-Leste | 0 1000 t | 2023 | — | volatile |
| 41 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 41 | Melanesia | 0 1000 t | 2023 | — | volatile |
| 41 | Polynesia | 0 1000 t | 2023 | — | flat |
| 41 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 41 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 41 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 41 | Russian Federation | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Syrian Arab Republic | 0 1000 t | 2023 | — | volatile |
| 41 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Côte d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 41 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | down 100.0% | flat |
| 41 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
| 41 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
| 166 | Czechia | -1 1000 t | 2023 | — | volatile |
| 166 | Mexico | -1 1000 t | 2023 | down 200.0% | volatile |
| 168 | Norway | -4 1000 t | 2023 | — | volatile |
| 168 | China, Taiwan Province of | -4 1000 t | 2023 | up 63.6% | volatile |
| 170 | Ethiopia | -5 1000 t | 2023 | down 400.0% | volatile |
| 170 | Indonesia | -5 1000 t | 2023 | up 95.2% | volatile |
| 172 | Lao People's Democratic Republic | -7 1000 t | 2023 | down 275.0% | volatile |
| 173 | Morocco | -8 1000 t | 2023 | — | volatile |
| 174 | United Republic of Tanzania | -25 1000 t | 2023 | down 1,350.0% | volatile |
| 175 | Angola | -48 1000 t | 2023 | down 223.1% | volatile |
| 176 | Argentina | -114 1000 t | 2023 | down 3,900.0% | volatile |
| 177 | Nigeria | -155 1000 t | 2023 | down 12.3% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Asia 644 1000 t
- World 435 1000 t
- Southern Asia 388 1000 t
- Net Food Importing Developing Countries (NFIDCs) 149 1000 t
- Eastern Asia 130 1000 t
- Low Income Food Deficit Countries (LIFDCs) 130 1000 t
- South-eastern Asia 119 1000 t
- Eastern Africa 116 1000 t
- Least Developed Countries (LDCs) 110 1000 t
- Western Africa 77 1000 t
- Land Locked Developing Countries (LLDCs) 67 1000 t
- European Union (27) 18 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.