Starchy Roots — 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...
Countries reporting
182
Highest
4,044 1000 t
China
Lowest
-1,185 1000 t
Russian Federation
Median
0 1000 t
Years covered
14
2010–2023
Data points
3,046
What the numbers show
Starchy Roots — Stock Variation is currently reported for 182 countries. The highest value is 4,044 1000 t in China; the lowest is -1,185 1000 t in Russian Federation.
The median across all reporting countries is 0 1000 t, and the mean is 88.65 1000 t.
The gap between the highest and lowest reporting country is a factor of about 3.
Over the past decade 85 countries rose and 59 fell. The largest increase was in Laos (up 20,014.3%), and the largest decrease in Kazakhstan (down 20,600.0%).
Starchy Roots — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 4,044 1000 t | 2023 | up 279.7% | volatile |
| 2 | China, mainland | 4,008 1000 t | 2023 | up 278.2% | volatile |
| 3 | United Republic of Tanzania | 1,600 1000 t | 2023 | up 132.2% | volatile |
| 4 | Laos | 1,394 1000 t | 2023 | up 20,014.3% | volatile |
| 4 | Lao People's Democratic Republic | 1,394 1000 t | 2023 | up 20,014.3% | volatile |
| 6 | Ghana | 1,029 1000 t | 2023 | up 1,844.1% | volatile |
| 7 | Belgium | 964 1000 t | 2023 | up 496.7% | volatile |
| 8 | United Kingdom | 602 1000 t | 2023 | up 144.7% | volatile |
| 8 | United Kingdom of Great Britain and Northern Ireland | 602 1000 t | 2023 | up 144.7% | volatile |
| 10 | Netherlands (Kingdom of the) | 500 1000 t | 2023 | — | volatile |
| 11 | Turkey | 440 1000 t | 2023 | up 159.5% | volatile |
| 11 | Türkiye | 440 1000 t | 2023 | up 159.5% | volatile |
| 13 | Uzbekistan | 403 1000 t | 2023 | up 407.6% | volatile |
| 14 | Denmark | 300 1000 t | 2023 | up 9,900.0% | volatile |
| 15 | Cameroon | 298 1000 t | 2023 | up 82.8% | volatile |
| 16 | France | 275 1000 t | 2023 | up 118.0% | volatile |
| 17 | Nigeria | 268 1000 t | 2023 | down 96.4% | volatile |
| 18 | Ukraine | 267 1000 t | 2023 | up 115.1% | volatile |
| 19 | Sierra Leone | 217 1000 t | 2023 | up 5,525.0% | volatile |
| 20 | Bolivia (Plurinational State of) | 152 1000 t | 2023 | up 406.7% | volatile |
| 21 | Guinea | 140 1000 t | 2023 | up 3,400.0% | volatile |
| 22 | India | 125 1000 t | 2023 | down 69.7% | volatile |
| 23 | Portugal | 113 1000 t | 2023 | up 135.4% | volatile |
| 24 | Saudi Arabia | 93 1000 t | 2023 | — | volatile |
| 25 | Romania | 91 1000 t | 2023 | up 102.2% | volatile |
| 26 | Brazil | 88 1000 t | 2023 | up 150.9% | volatile |
| 27 | Zambia | 84 1000 t | 2023 | up 127.0% | volatile |
| 28 | Vietnam | 75 1000 t | 2023 | up 36.4% | volatile |
| 28 | Viet Nam | 75 1000 t | 2023 | up 36.4% | volatile |
| 30 | Lebanon | 48 1000 t | 2023 | up 173.8% | volatile |
| 30 | Thailand | 48 1000 t | 2023 | up 115.2% | volatile |
| 32 | Philippines | 46 1000 t | 2023 | up 84.0% | volatile |
| 33 | Ireland | 40 1000 t | 2023 | up 25.0% | volatile |
| 33 | Zimbabwe | 40 1000 t | 2023 | up 4,100.0% | volatile |
| 35 | Tajikistan | 39 1000 t | 2023 | down 60.6% | volatile |
| 36 | Indonesia | 38 1000 t | 2023 | down 65.8% | volatile |
| 37 | Dominican Republic | 37 1000 t | 2023 | up 640.0% | volatile |
| 38 | Argentina | 36 1000 t | 2023 | up 126.5% | volatile |
| 39 | Italy | 35 1000 t | 2023 | up 128.7% | volatile |
| 39 | Caribbean | 35 1000 t | 2023 | down 49.3% | volatile |
| 41 | Albania | 34 1000 t | 2023 | — | volatile |
| 42 | Kenya | 32 1000 t | 2023 | down 88.8% | volatile |
| 43 | Croatia | 30 1000 t | 2023 | — | volatile |
| 43 | Niger | 30 1000 t | 2023 | up 11.1% | volatile |
| 43 | China, Taiwan Province of | 30 1000 t | 2023 | up 900.0% | volatile |
| 46 | Norway | 19 1000 t | 2023 | up 216.7% | volatile |
| 47 | Morocco | 16 1000 t | 2023 | up 220.0% | volatile |
| 48 | Pakistan | 15 1000 t | 2023 | up 1,400.0% | volatile |
| 49 | Greece | 14 1000 t | 2023 | — | volatile |
| 50 | Bulgaria | 12 1000 t | 2023 | down 66.7% | volatile |
| 50 | Haiti | 12 1000 t | 2023 | down 83.1% | volatile |
| 52 | Bosnia and Herzegovina | 11 1000 t | 2023 | down 57.7% | volatile |
| 52 | Canada | 11 1000 t | 2023 | down 26.7% | volatile |
| 54 | Burkina Faso | 10 1000 t | 2023 | down 81.1% | volatile |
| 55 | Lithuania | 8 1000 t | 2023 | up 108.0% | volatile |
| 56 | Spain | 7 1000 t | 2023 | up 106.2% | volatile |
| 57 | Jamaica | 6 1000 t | 2023 | up 166.7% | volatile |
| 57 | China, Hong Kong SAR | 6 1000 t | 2023 | up 250.0% | volatile |
| 59 | Cyprus | 5 1000 t | 2023 | up 122.7% | volatile |
| 59 | Guatemala | 5 1000 t | 2023 | down 61.5% | volatile |
| 59 | Slovenia | 5 1000 t | 2023 | up 116.7% | volatile |
| 62 | Estonia | 4 1000 t | 2023 | — | volatile |
| 63 | Finland | 3 1000 t | 2023 | down 25.0% | volatile |
| 63 | Honduras | 3 1000 t | 2023 | up 200.0% | volatile |
| 63 | Namibia | 3 1000 t | 2023 | down 57.1% | volatile |
| 63 | Poland | 3 1000 t | 2023 | up 101.6% | volatile |
| 63 | Senegal | 3 1000 t | 2023 | up 133.3% | volatile |
| 68 | Czechia | 2 1000 t | 2023 | up 140.0% | volatile |
| 68 | Iceland | 2 1000 t | 2023 | unchanged | volatile |
| 68 | North Macedonia | 2 1000 t | 2023 | — | volatile |
| 68 | Montenegro | 2 1000 t | 2023 | up 200.0% | volatile |
| 68 | Mongolia | 2 1000 t | 2023 | down 87.5% | volatile |
| 68 | Oman | 2 1000 t | 2023 | — | volatile |
| 68 | East Timor | 2 1000 t | 2023 | — | volatile |
| 68 | Uruguay | 2 1000 t | 2023 | up 109.1% | volatile |
| 68 | Saint Vincent and the Grenadines | 2 1000 t | 2023 | — | volatile |
| 68 | Timor-Leste | 2 1000 t | 2023 | — | volatile |
| 78 | Australia | 1 1000 t | 2023 | — | volatile |
| 78 | Belize | 1 1000 t | 2023 | — | volatile |
| 78 | Georgia | 1 1000 t | 2023 | — | volatile |
| 78 | Maldives | 1 1000 t | 2023 | up 200.0% | volatile |
| 78 | Tunisia | 1 1000 t | 2023 | up 110.0% | volatile |
| 78 | Democratic Republic of the Congo | 1 1000 t | 2023 | down 97.2% | volatile |
| 84 | Armenia | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 84 | Austria | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Bahamas | 0 1000 t | 2023 | — | volatile |
| 84 | Bhutan | 0 1000 t | 2023 | — | volatile |
| 84 | Botswana | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Congo | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Comoros | 0 1000 t | 2023 | — | volatile |
| 84 | Costa Rica | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Cuba | 0 1000 t | 2019 | — | volatile |
| 84 | Djibouti | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Fiji | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Gabon | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Guinea-Bissau | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Grenada | 0 1000 t | 2023 | — | volatile |
| 84 | Guyana | 0 1000 t | 2023 | — | volatile |
| 84 | Hungary | 0 1000 t | 2023 | — | volatile |
| 84 | Jordan | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Kuwait | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Liberia | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Libya | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 84 | Sri Lanka | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Luxembourg | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Latvia | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Malta | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Mauritius | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | New Caledonia | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Nepal | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Panama | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Papua New Guinea | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | French Polynesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Rwanda | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | El Salvador | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Serbia | 0 1000 t | 2023 | — | volatile |
| 84 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 84 | Suriname | 0 1000 t | 2023 | — | volatile |
| 84 | Syria | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Turkmenistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Tonga | 0 1000 t | 2023 | — | volatile |
| 84 | Trinidad and Tobago | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Vanuatu | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Cabo Verde | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Iran (Islamic Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Republic of Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Syrian Arab Republic | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Australia and New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | China, Macao SAR | 0 1000 t | 2023 | — | volatile |
| 146 | Bahrain | -1 1000 t | 2023 | — | volatile |
| 146 | Barbados | -1 1000 t | 2023 | — | volatile |
| 146 | Ecuador | -1 1000 t | 2023 | down 200.0% | volatile |
| 146 | Ethiopia | -1 1000 t | 2023 | down 100.3% | volatile |
| 146 | Myanmar | -1 1000 t | 2023 | — | volatile |
| 146 | Mauritania | -1 1000 t | 2023 | up 80.0% | flat |
| 146 | Eswatini | -1 1000 t | 2023 | unchanged | volatile |
| 153 | Gambia | -2 1000 t | 2023 | — | flat |
| 153 | Samoa | -2 1000 t | 2023 | down 300.0% | volatile |
| 153 | Polynesia | -2 1000 t | 2023 | down 300.0% | volatile |
| 156 | Afghanistan | -3 1000 t | 2023 | up 98.7% | volatile |
| 156 | Cote d'Ivoire | -3 1000 t | 2023 | up 40.0% | volatile |
| 156 | Peru | -3 1000 t | 2023 | down 150.0% | volatile |
| 156 | Côte d'Ivoire | -3 1000 t | 2023 | up 40.0% | volatile |
| 160 | Algeria | -5 1000 t | 2023 | down 101.8% | volatile |
| 160 | Lesotho | -5 1000 t | 2023 | down 200.0% | volatile |
| 160 | Solomon Islands | -5 1000 t | 2023 | down 150.0% | volatile |
| 160 | Yemen | -5 1000 t | 2023 | up 90.6% | volatile |
| 160 | Melanesia | -5 1000 t | 2023 | down 400.0% | volatile |
| 165 | Mozambique | -7 1000 t | 2023 | down 107.5% | volatile |
| 165 | Nicaragua | -7 1000 t | 2023 | down 158.3% | volatile |
| 167 | Sweden | -9 1000 t | 2023 | down 550.0% | volatile |
| 168 | Qatar | -10 1000 t | 2023 | — | volatile |
| 168 | United States | -10 1000 t | 2023 | up 91.7% | volatile |
| 170 | Israel | -11 1000 t | 2023 | up 52.2% | volatile |
| 171 | Belarus | -12 1000 t | 2023 | up 96.0% | volatile |
| 172 | Malaysia | -13 1000 t | 2023 | down 1,400.0% | volatile |
| 173 | Slovakia | -15 1000 t | 2023 | up 34.8% | volatile |
| 174 | South Africa | -24 1000 t | 2023 | up 63.1% | volatile |
| 175 | Switzerland | -25 1000 t | 2023 | down 196.2% | volatile |
| 175 | Egypt | -25 1000 t | 2023 | down 19.0% | volatile |
| 177 | Iraq | -27 1000 t | 2023 | down 123.7% | volatile |
| 178 | Bangladesh | -30 1000 t | 2023 | up 85.2% | volatile |
| 179 | Mexico | -38 1000 t | 2023 | up 37.7% | volatile |
| 180 | Azerbaijan | -43 1000 t | 2023 | down 222.9% | volatile |
| 181 | Cambodia | -56 1000 t | 2023 | — | volatile |
| 181 | Republic of Korea | -56 1000 t | 2023 | down 130.3% | volatile |
| 183 | Angola | -67 1000 t | 2023 | down 112.0% | volatile |
| 184 | Kyrgyzstan | -77 1000 t | 2023 | down 862.5% | volatile |
| 185 | Madagascar | -80 1000 t | 2023 | down 433.3% | volatile |
| 186 | Chile | -83 1000 t | 2023 | down 130.6% | volatile |
| 187 | Democratic People's Republic of Korea | -117 1000 t | 2018 | down 2,440.0% | volatile |
| 188 | United Arab Emirates | -128 1000 t | 2023 | down 884.6% | volatile |
| 189 | Germany | -156 1000 t | 2023 | up 86.8% | volatile |
| 190 | Kazakhstan | -205 1000 t | 2023 | down 20,600.0% | volatile |
| 191 | Malawi | -436 1000 t | 2023 | down 229.8% | volatile |
| 192 | Colombia | -564 1000 t | 2023 | down 2,269.2% | volatile |
| 193 | Russia | -1,185 1000 t | 2023 | — | volatile |
| 193 | Russian Federation | -1,185 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.
- World 10,891 1000 t
- Asia 6,277 1000 t
- Eastern Asia 4,112 1000 t
- Africa 3,048 1000 t
- Net Food Importing Developing Countries (NFIDCs) 2,790 1000 t
- Least Developed Countries (LDCs) 2,728 1000 t
- European Union (27) 2,231 1000 t
- Low Income Food Deficit Countries (LIFDCs) 2,221 1000 t
- Europe 1,945 1000 t
- Western Africa 1,619 1000 t
- Western Europe 1,559 1000 t
- South-Eastern Asia 1,533 1000 t
- Land Locked Developing Countries (LLDCs) 1,331 1000 t
- Eastern Africa 1,235 1000 t
- Northern Europe 970 1000 t
- Western Asia 363 1000 t
- Southern Europe 251 1000 t
- Middle Africa 232 1000 t
- Central Asia 160 1000 t
- Southern Asia 109 1000 t
- Small island developing States (SIDS) 33 1000 t
- Northern America 1 1000 t
- Oceania -6 1000 t
- Northern Africa -10 1000 t
- United States of America -10 1000 t
- Southern Africa -28 1000 t
- Central America -36 1000 t
- Americas -373 1000 t
- South America -374 1000 t
- Eastern Europe -836 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.