Maize and products — 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
Maize and products — Residuals is currently reported for 89 countries. The highest value is 610 1000 t in Kazakhstan; the lowest is -319 1000 t in Germany.
The median across all reporting countries is 0 1000 t, and the mean is 11.19 1000 t.
The gap between the highest and lowest reporting country is a factor of about 2.
Over the past decade 22 countries rose and 19 fell. The largest increase was in France (up 376.2%), and the largest decrease in Italy (down 329.2%).
Maize and products — Residuals: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Kazakhstan | 610 1000 t | 2023 | up 157.4% | volatile |
| 2 | Venezuela (Bolivarian Republic of) | 489 1000 t | 2023 | up 7.5% | volatile |
| 3 | Nigeria | 304 1000 t | 2023 | up 13.4% | rising |
| 4 | Austria | 192 1000 t | 2023 | up 5.5% | volatile |
| 5 | Canada | 141 1000 t | 2023 | down 7.8% | falling |
| 6 | France | 100 1000 t | 2023 | up 376.2% | volatile |
| 7 | United States | 28 1000 t | 2023 | down 98.6% | volatile |
| 8 | Ghana | 25 1000 t | 2023 | — | volatile |
| 9 | Bulgaria | 7 1000 t | 2023 | up 75.0% | volatile |
| 10 | Hungary | 5 1000 t | 2023 | up 105.4% | volatile |
| 11 | Croatia | 2 1000 t | 2023 | up 125.0% | volatile |
| 11 | Romania | 2 1000 t | 2023 | down 99.4% | volatile |
| 11 | Ukraine | 2 1000 t | 2023 | down 99.9% | volatile |
| 14 | Namibia | 1 1000 t | 2023 | — | volatile |
| 15 | Afghanistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Azerbaijan | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 15 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | volatile |
| 15 | Belize | 0 1000 t | 2023 | — | volatile |
| 15 | Barbados | 0 1000 t | 2023 | — | volatile |
| 15 | Bhutan | 0 1000 t | 2023 | — | volatile |
| 15 | Botswana | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | China | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Cameroon | 0 1000 t | 2023 | — | volatile |
| 15 | Colombia | 0 1000 t | 2023 | — | volatile |
| 15 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 15 | Czechia | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 15 | Egypt | 0 1000 t | 2023 | — | volatile |
| 15 | Spain | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | United Kingdom | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Georgia | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Guinea-Bissau | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Greece | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Guatemala | 0 1000 t | 2023 | — | volatile |
| 15 | Guyana | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Honduras | 0 1000 t | 2023 | — | volatile |
| 15 | Indonesia | 0 1000 t | 2023 | — | volatile |
| 15 | India | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Cambodia | 0 1000 t | 2023 | — | volatile |
| 15 | Liberia | 0 1000 t | 2023 | — | volatile |
| 15 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 15 | Lesotho | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 15 | Latvia | 0 1000 t | 2023 | — | volatile |
| 15 | Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Mexico | 0 1000 t | 2023 | — | volatile |
| 15 | Mongolia | 0 1000 t | 2023 | — | volatile |
| 15 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 15 | Nicaragua | 0 1000 t | 2023 | — | volatile |
| 15 | New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Pakistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Panama | 0 1000 t | 2023 | — | volatile |
| 15 | Rwanda | 0 1000 t | 2023 | — | volatile |
| 15 | Saudi Arabia | 0 1000 t | 2023 | — | volatile |
| 15 | Serbia | 0 1000 t | 2023 | — | volatile |
| 15 | Slovenia | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Turkmenistan | 0 1000 t | 2023 | — | volatile |
| 15 | Turkey | 0 1000 t | 2023 | — | volatile |
| 15 | Uganda | 0 1000 t | 2023 | — | volatile |
| 15 | Zambia | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Caribbean | 0 1000 t | 2023 | — | volatile |
| 15 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 15 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | volatile |
| 15 | Republic of Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Türkiye | 0 1000 t | 2023 | — | volatile |
| 15 | Australia and New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | China, mainland | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | United Republic of Tanzania | 0 1000 t | 2023 | — | volatile |
| 15 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | volatile |
| 179 | Estonia | -1 1000 t | 2023 | up 50.0% | rising |
| 179 | Micronesia | -1 1000 t | 2023 | — | volatile |
| 179 | Micronesia (Federated States of) | -1 1000 t | 2023 | — | volatile |
| 182 | Myanmar | -2 1000 t | 2023 | — | volatile |
| 183 | Armenia | -4 1000 t | 2023 | down 113.3% | volatile |
| 184 | Chile | -5 1000 t | 2023 | — | volatile |
| 185 | Lithuania | -6 1000 t | 2023 | — | volatile |
| 186 | Democratic Republic of the Congo | -10 1000 t | 2023 | — | volatile |
| 187 | Ireland | -21 1000 t | 2023 | — | volatile |
| 188 | Thailand | -28 1000 t | 2023 | — | volatile |
| 189 | Malaysia | -41 1000 t | 2023 | — | volatile |
| 190 | Poland | -75 1000 t | 2023 | — | volatile |
| 191 | Belgium | -84 1000 t | 2023 | up 56.2% | volatile |
| 192 | Brazil | -110 1000 t | 2023 | — | volatile |
| 193 | Italy | -204 1000 t | 2023 | down 329.2% | volatile |
| 194 | Germany | -319 1000 t | 2023 | down 234.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 984 1000 t
- Central Asia 610 1000 t
- Land Locked Developing Countries (LLDCs) 606 1000 t
- Americas 543 1000 t
- Asia 524 1000 t
- Net Food Importing Developing Countries (NFIDCs) 478 1000 t
- South America 374 1000 t
- Western Africa 328 1000 t
- Africa 319 1000 t
- Northern America 169 1000 t
- United States of America 28 1000 t
- Southern Africa 1 1000 t
- Eastern Africa 0 1000 t
- Northern Africa 0 1000 t
- Central America 0 1000 t
- Southern Asia 0 1000 t
- Oceania -1 1000 t
- Small island developing States (SIDS) -1 1000 t
- Western Asia -4 1000 t
- Middle Africa -10 1000 t
- Eastern Asia -11 1000 t
- Low Income Food Deficit Countries (LIFDCs) -11 1000 t
- Least Developed Countries (LDCs) -12 1000 t
- Northern Europe -28 1000 t
- Eastern Europe -59 1000 t
- South-Eastern Asia -71 1000 t
- Western Europe -112 1000 t
- Southern Europe -203 1000 t
- Europe -401 1000 t
- European Union (27) -403 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.