Barley and products — Food 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
Barley and products — Food is currently reported for 176 countries. The highest value is 2,334 1000 t in China; the lowest is 0 1000 t in China, Macao SAR.
The median across all reporting countries is 1 1000 t, and the mean is 68.01 1000 t.
Over the past decade 39 countries rose and 42 fell. The largest increase was in Mauritania (up 2,200.0%), and the largest decrease in Bosnia and Herzegovina (down 100.0%).
Barley and products — Food: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 2,334 1000 t | 2023 | up 1,543.7% | volatile |
| 2 | China, mainland | 2,325 1000 t | 2023 | up 1,775.0% | volatile |
| 3 | Ethiopia | 1,888 1000 t | 2023 | up 25.4% | rising |
| 4 | India | 1,113 1000 t | 2023 | up 25.8% | rising |
| 5 | Morocco | 950 1000 t | 2023 | down 11.9% | falling |
| 6 | Algeria | 393 1000 t | 2023 | down 33.7% | falling |
| 7 | Russian Federation | 299 1000 t | 2023 | up 119.9% | rising |
| 8 | Spain | 251 1000 t | 2023 | up 765.5% | volatile |
| 9 | United Kingdom of Great Britain and Northern Ireland | 223 1000 t | 2023 | up 291.2% | volatile |
| 10 | Finland | 133 1000 t | 2023 | up 343.3% | volatile |
| 11 | Peru | 130 1000 t | 2023 | down 2.3% | flat |
| 12 | Uzbekistan | 127 1000 t | 2023 | up 95.4% | rising |
| 13 | Ukraine | 124 1000 t | 2023 | up 14.8% | rising |
| 14 | Poland | 115 1000 t | 2023 | down 44.4% | falling |
| 15 | Tunisia | 104 1000 t | 2023 | up 50.7% | rising |
| 16 | Senegal | 73 1000 t | 2023 | — | volatile |
| 17 | Thailand | 72 1000 t | 2023 | up 500.0% | volatile |
| 18 | Indonesia | 69 1000 t | 2023 | up 590.0% | volatile |
| 19 | Belarus | 65 1000 t | 2023 | up 261.1% | rising |
| 20 | Colombia | 63 1000 t | 2023 | up 50.0% | rising |
| 21 | North Macedonia | 61 1000 t | 2023 | — | volatile |
| 22 | Libya | 60 1000 t | 2023 | up 13.2% | rising |
| 23 | Netherlands (Kingdom of the) | 58 1000 t | 2023 | up 11.5% | rising |
| 24 | Republic of Korea | 53 1000 t | 2023 | up 23.3% | rising |
| 25 | Tajikistan | 52 1000 t | 2023 | up 10.6% | rising |
| 26 | France | 51 1000 t | 2023 | up 168.4% | rising |
| 27 | Philippines | 44 1000 t | 2023 | up 528.6% | volatile |
| 28 | Pakistan | 41 1000 t | 2023 | down 25.5% | falling |
| 29 | Germany | 39 1000 t | 2023 | up 50.0% | volatile |
| 30 | Lithuania | 36 1000 t | 2023 | up 38.5% | rising |
| 31 | Iran (Islamic Republic of) | 33 1000 t | 2023 | down 21.4% | falling |
| 32 | Kazakhstan | 32 1000 t | 2023 | down 75.2% | volatile |
| 33 | Chile | 30 1000 t | 2023 | up 114.3% | rising |
| 34 | Azerbaijan | 27 1000 t | 2023 | — | volatile |
| 34 | Portugal | 27 1000 t | 2023 | up 8.0% | falling |
| 36 | Lao People's Democratic Republic | 26 1000 t | 2023 | — | volatile |
| 37 | Georgia | 25 1000 t | 2023 | up 400.0% | volatile |
| 38 | Yemen | 24 1000 t | 2023 | down 11.1% | falling |
| 39 | Latvia | 23 1000 t | 2023 | down 47.7% | falling |
| 39 | Mauritania | 23 1000 t | 2023 | up 2,200.0% | volatile |
| 41 | Iraq | 22 1000 t | 2023 | down 82.7% | falling |
| 41 | Italy | 22 1000 t | 2023 | up 37.5% | falling |
| 43 | Democratic Republic of the Congo | 19 1000 t | 2023 | — | volatile |
| 44 | Armenia | 18 1000 t | 2023 | down 25.0% | falling |
| 45 | Romania | 17 1000 t | 2023 | down 19.0% | falling |
| 46 | Belgium | 16 1000 t | 2023 | up 166.7% | volatile |
| 47 | Jordan | 15 1000 t | 2023 | up 400.0% | volatile |
| 48 | Canada | 14 1000 t | 2023 | down 48.1% | volatile |
| 49 | Greece | 13 1000 t | 2023 | up 44.4% | volatile |
| 49 | Iceland | 13 1000 t | 2023 | — | volatile |
| 49 | Nepal | 13 1000 t | 2023 | down 62.9% | falling |
| 52 | Switzerland | 11 1000 t | 2023 | down 15.4% | falling |
| 53 | Lebanon | 10 1000 t | 2023 | up 400.0% | volatile |
| 53 | Malaysia | 10 1000 t | 2023 | — | volatile |
| 55 | Burkina Faso | 9 1000 t | 2023 | up 80.0% | rising |
| 55 | Sweden | 9 1000 t | 2023 | down 40.0% | falling |
| 55 | China, Taiwan Province of | 9 1000 t | 2023 | down 50.0% | falling |
| 59 | Bangladesh | 8 1000 t | 2023 | — | volatile |
| 59 | Cyprus | 8 1000 t | 2023 | down 20.0% | falling |
| 59 | Estonia | 8 1000 t | 2023 | down 50.0% | falling |
| 62 | Slovakia | 7 1000 t | 2023 | down 30.0% | rising |
| 62 | Republic of Moldova | 7 1000 t | 2023 | up 16.7% | rising |
| 64 | Haiti | 6 1000 t | 2023 | — | volatile |
| 64 | Slovenia | 6 1000 t | 2023 | up 50.0% | rising |
| 64 | Democratic People's Republic of Korea | 6 1000 t | 2018 | down 88.2% | volatile |
| 67 | Hungary | 5 1000 t | 2023 | up 400.0% | volatile |
| 68 | Austria | 4 1000 t | 2023 | up 33.3% | rising |
| 69 | Afghanistan | 3 1000 t | 2023 | down 91.7% | volatile |
| 69 | Guinea-Bissau | 3 1000 t | 2023 | up 50.0% | volatile |
| 69 | Croatia | 3 1000 t | 2023 | unchanged | flat |
| 69 | Ireland | 3 1000 t | 2023 | unchanged | volatile |
| 69 | New Zealand | 3 1000 t | 2023 | unchanged | rising |
| 69 | Uganda | 3 1000 t | 2023 | down 57.1% | volatile |
| 69 | Zimbabwe | 3 1000 t | 2023 | unchanged | flat |
| 69 | Australia and New Zealand | 3 1000 t | 2023 | unchanged | rising |
| 77 | Bulgaria | 2 1000 t | 2023 | down 66.7% | volatile |
| 77 | Bhutan | 2 1000 t | 2023 | — | volatile |
| 77 | Gambia | 2 1000 t | 2023 | — | volatile |
| 77 | Liberia | 2 1000 t | 2023 | up 100.0% | rising |
| 77 | Paraguay | 2 1000 t | 2023 | unchanged | flat |
| 77 | Sao Tome and Principe | 2 1000 t | 2023 | unchanged | volatile |
| 77 | Uruguay | 2 1000 t | 2023 | down 66.7% | falling |
| 84 | Albania | 1 1000 t | 2023 | down 66.7% | volatile |
| 84 | Bahrain | 1 1000 t | 2023 | — | flat |
| 84 | Bahamas | 1 1000 t | 2023 | — | volatile |
| 84 | Barbados | 1 1000 t | 2023 | — | volatile |
| 84 | Dominican Republic | 1 1000 t | 2023 | — | volatile |
| 84 | Grenada | 1 1000 t | 2023 | — | volatile |
| 84 | Israel | 1 1000 t | 2023 | down 50.0% | volatile |
| 84 | Kyrgyzstan | 1 1000 t | 2023 | — | volatile |
| 84 | Mauritius | 1 1000 t | 2023 | down 50.0% | falling |
| 84 | Saudi Arabia | 1 1000 t | 2023 | — | volatile |
| 84 | Melanesia | 1 1000 t | 2023 | — | volatile |
| 95 | Angola | 0 1000 t | 2023 | — | flat |
| 95 | United Arab Emirates | 0 1000 t | 2023 | — | flat |
| 95 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 95 | Australia | 0 1000 t | 2023 | — | flat |
| 95 | Bosnia and Herzegovina | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Belize | 0 1000 t | 2023 | — | flat |
| 95 | Brazil | 0 1000 t | 2023 | — | flat |
| 95 | Botswana | 0 1000 t | 2023 | — | flat |
| 95 | Cameroon | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Congo | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Comoros | 0 1000 t | 2023 | — | flat |
| 95 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 95 | Cuba | 0 1000 t | 2019 | — | flat |
| 95 | Czechia | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Djibouti | 0 1000 t | 2023 | — | flat |
| 95 | Denmark | 0 1000 t | 2023 | — | flat |
| 95 | Ecuador | 0 1000 t | 2023 | — | flat |
| 95 | Egypt | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Fiji | 0 1000 t | 2023 | — | flat |
| 95 | Gabon | 0 1000 t | 2023 | — | flat |
| 95 | Ghana | 0 1000 t | 2023 | — | volatile |
| 95 | Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Guatemala | 0 1000 t | 2023 | — | flat |
| 95 | Guyana | 0 1000 t | 2023 | — | flat |
| 95 | Honduras | 0 1000 t | 2023 | — | flat |
| 95 | Jamaica | 0 1000 t | 2023 | — | flat |
| 95 | Kenya | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Cambodia | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Kiribati | 0 1000 t | 2023 | — | flat |
| 95 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 95 | Kuwait | 0 1000 t | 2023 | — | flat |
| 95 | Saint Lucia | 0 1000 t | 2021 | — | flat |
| 95 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 95 | Lesotho | 0 1000 t | 2023 | — | volatile |
| 95 | Luxembourg | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Madagascar | 0 1000 t | 2023 | — | flat |
| 95 | Maldives | 0 1000 t | 2023 | — | flat |
| 95 | Mexico | 0 1000 t | 2023 | — | flat |
| 95 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 95 | Malta | 0 1000 t | 2023 | — | flat |
| 95 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 95 | Montenegro | 0 1000 t | 2023 | — | flat |
| 95 | Mongolia | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Mozambique | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Malawi | 0 1000 t | 2023 | — | flat |
| 95 | Namibia | 0 1000 t | 2023 | — | flat |
| 95 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 95 | Niger | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Nigeria | 0 1000 t | 2023 | — | flat |
| 95 | Nicaragua | 0 1000 t | 2023 | — | flat |
| 95 | Norway | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Nauru | 0 1000 t | 2023 | — | flat |
| 95 | Oman | 0 1000 t | 2023 | — | flat |
| 95 | Panama | 0 1000 t | 2023 | — | flat |
| 95 | Papua New Guinea | 0 1000 t | 2023 | — | volatile |
| 95 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 95 | Qatar | 0 1000 t | 2023 | — | volatile |
| 95 | Rwanda | 0 1000 t | 2023 | down 100.0% | volatile |
| 95 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 95 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 95 | El Salvador | 0 1000 t | 2023 | — | flat |
| 95 | Serbia | 0 1000 t | 2023 | — | flat |
| 95 | Suriname | 0 1000 t | 2023 | — | flat |
| 95 | Eswatini | 0 1000 t | 2023 | — | flat |
| 95 | Seychelles | 0 1000 t | 2023 | — | flat |
| 95 | Turkmenistan | 0 1000 t | 2023 | — | volatile |
| 95 | Tonga | 0 1000 t | 2023 | — | flat |
| 95 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 95 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 95 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 95 | Samoa | 0 1000 t | 2023 | — | flat |
| 95 | Zambia | 0 1000 t | 2023 | — | flat |
| 95 | Micronesia | 0 1000 t | 2023 | — | flat |
| 95 | Timor-Leste | 0 1000 t | 2023 | — | volatile |
| 95 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 95 | Polynesia | 0 1000 t | 2023 | — | flat |
| 95 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 95 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 95 | Syrian Arab Republic | 0 1000 t | 2023 | — | volatile |
| 95 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 95 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 95 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 95 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 11,071 1000 t
- Asia 4,289 1000 t
- Africa 3,593 1000 t
- Net Food Importing Developing Countries (NFIDCs) 3,409 1000 t
- Eastern Asia 2,485 1000 t
- Low Income Food Deficit Countries (LIFDCs) 2,328 1000 t
- Land Locked Developing Countries (LLDCs) 2,315 1000 t
- Least Developed Countries (LDCs) 2,163 1000 t
- Eastern Africa 1,895 1000 t
- Europe 1,657 1000 t
- Americas 1,528 1000 t
- Northern Africa 1,509 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.