Groundnuts — 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...
What the numbers show
Groundnuts — Residuals is currently reported for 56 countries. The highest value is 379 1000 t in Senegal; the lowest is -51 1000 t in Madagascar.
The median across all reporting countries is 0 1000 t, and the mean is 9.14 1000 t.
The gap between the highest and lowest reporting country is a factor of about 7.
Over the past decade 7 countries rose and 1 fell. The largest increase was in Senegal (up 419.2%), and the largest decrease in Argentina (down 100.0%).
Groundnuts — Residuals: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Senegal | 379 1000 t | 2023 | up 419.2% | volatile |
| 2 | Guinea | 296 1000 t | 2023 | — | volatile |
| 3 | Latvia | 0 1000 t | 2023 | — | volatile |
| 3 | Vanuatu | 0 1000 t | 2023 | — | volatile |
| 3 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 3 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 3 | Maldives | 0 1000 t | 2023 | — | volatile |
| 3 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 3 | Mozambique | 0 1000 t | 2023 | — | volatile |
| 3 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 3 | Caribbean | 0 1000 t | 2023 | — | volatile |
| 3 | Poland | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Portugal | 0 1000 t | 2023 | — | volatile |
| 3 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 3 | Russia | 0 1000 t | 2023 | — | volatile |
| 3 | Melanesia | 0 1000 t | 2023 | — | volatile |
| 3 | Trinidad and Tobago | 0 1000 t | 2023 | — | volatile |
| 3 | Uganda | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Uzbekistan | 0 1000 t | 2023 | — | volatile |
| 3 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 3 | Argentina | 0 1000 t | 2023 | down 100.0% | volatile |
| 3 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 3 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 3 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | volatile |
| 3 | Chile | 0 1000 t | 2023 | — | volatile |
| 3 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | volatile |
| 3 | Cote d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 3 | Egypt | 0 1000 t | 2023 | — | volatile |
| 3 | United Kingdom | 0 1000 t | 2023 | — | volatile |
| 3 | Ghana | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | China, Taiwan Province of | 0 1000 t | 2023 | — | volatile |
| 3 | Haiti | 0 1000 t | 2023 | — | volatile |
| 3 | Côte d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 3 | Kenya | 0 1000 t | 2023 | — | volatile |
| 3 | Cambodia | 0 1000 t | 2023 | — | volatile |
| 3 | Kuwait | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Libya | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Russian Federation | 0 1000 t | 2023 | — | volatile |
| 177 | China, mainland | -1 1000 t | 2023 | — | volatile |
| 177 | United Arab Emirates | -1 1000 t | 2023 | — | volatile |
| 177 | Venezuela (Bolivarian Republic of) | -1 1000 t | 2023 | — | volatile |
| 177 | Luxembourg | -1 1000 t | 2023 | — | volatile |
| 177 | Greece | -1 1000 t | 2023 | — | volatile |
| 177 | China | -1 1000 t | 2023 | — | volatile |
| 183 | Brazil | -2 1000 t | 2023 | — | volatile |
| 183 | Viet Nam | -2 1000 t | 2023 | — | volatile |
| 183 | Vietnam | -2 1000 t | 2023 | — | volatile |
| 186 | Morocco | -5 1000 t | 2023 | — | volatile |
| 186 | Slovakia | -5 1000 t | 2023 | — | volatile |
| 188 | Indonesia | -11 1000 t | 2023 | — | volatile |
| 188 | Paraguay | -11 1000 t | 2023 | — | volatile |
| 190 | United States | -12 1000 t | 2023 | — | volatile |
| 191 | South Africa | -14 1000 t | 2023 | — | volatile |
| 192 | Belgium | -19 1000 t | 2023 | — | volatile |
| 193 | Nicaragua | -23 1000 t | 2023 | up 43.9% | volatile |
| 194 | Madagascar | -51 1000 t | 2023 | — | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Least Developed Countries (LDCs) 856 1000 t
- Net Food Importing Developing Countries (NFIDCs) 850 1000 t
- Africa 837 1000 t
- Low Income Food Deficit Countries (LIFDCs) 833 1000 t
- World 748 1000 t
- Western Africa 653 1000 t
- Middle Africa 254 1000 t
- Land Locked Developing Countries (LLDCs) 243 1000 t
- Southern Asia 0 1000 t
- Northern Europe 0 1000 t
- Oceania 0 1000 t
- Central Asia 0 1000 t
- Small island developing States (SIDS) 0 1000 t
- Eastern Asia -1 1000 t
- Western Asia -1 1000 t
- Southern Europe -1 1000 t
- Eastern Europe -5 1000 t
- Northern Africa -5 1000 t
- Northern America -12 1000 t
- United States of America -12 1000 t
- South-Eastern Asia -13 1000 t
- South America -14 1000 t
- Asia -14 1000 t
- Southern Africa -14 1000 t
- Western Europe -19 1000 t
- Central America -23 1000 t
- Europe -25 1000 t
- European Union (27) -25 1000 t
- Americas -49 1000 t
- Eastern Africa -51 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.