Fruits - Excluding Wine — 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
186
Highest
830 1000 t
China
Lowest
-248 1000 t
Philippines
Median
0 1000 t
Years covered
14
2010–2023
Data points
3,046
What the numbers show
Fruits - Excluding Wine — Stock Variation is currently reported for 186 countries. The highest value is 830 1000 t in China; the lowest is -248 1000 t in Philippines.
The median across all reporting countries is 0 1000 t, and the mean is 20.04 1000 t.
The gap between the highest and lowest reporting country is a factor of about 3.
Over the past decade 64 countries rose and 76 fell. The largest increase was in Czechia (up 3,600.0%), and the largest decrease in Moldova (down 1,466.7%).
Fruits - Excluding Wine — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 830 1000 t | 2023 | up 137.1% | volatile |
| 2 | China, mainland | 792 1000 t | 2023 | up 253.6% | volatile |
| 3 | India | 566 1000 t | 2023 | up 394.8% | volatile |
| 4 | Brazil | 480 1000 t | 2023 | up 678.3% | volatile |
| 5 | Netherlands (Kingdom of the) | 251 1000 t | 2023 | up 120.2% | volatile |
| 6 | Turkey | 186 1000 t | 2023 | down 49.6% | volatile |
| 6 | Türkiye | 186 1000 t | 2023 | down 49.6% | volatile |
| 8 | Indonesia | 182 1000 t | 2023 | up 171.6% | volatile |
| 9 | United States | 125 1000 t | 2023 | up 283.8% | volatile |
| 10 | Chile | 116 1000 t | 2023 | up 222.1% | volatile |
| 11 | United Kingdom | 102 1000 t | 2023 | — | volatile |
| 11 | United Kingdom of Great Britain and Northern Ireland | 102 1000 t | 2023 | — | volatile |
| 13 | Thailand | 88 1000 t | 2023 | up 137.4% | volatile |
| 14 | Democratic People's Republic of Korea | 75 1000 t | 2018 | up 250.0% | volatile |
| 15 | Republic of Korea | 70 1000 t | 2023 | up 42.9% | volatile |
| 16 | France | 55 1000 t | 2023 | up 277.4% | volatile |
| 17 | Egypt | 47 1000 t | 2023 | up 148.5% | volatile |
| 18 | Austria | 41 1000 t | 2023 | up 241.7% | volatile |
| 18 | Lebanon | 41 1000 t | 2023 | up 1,466.7% | volatile |
| 20 | Denmark | 40 1000 t | 2023 | down 34.4% | volatile |
| 20 | Saudi Arabia | 40 1000 t | 2023 | down 24.5% | volatile |
| 22 | Vietnam | 36 1000 t | 2023 | down 32.1% | volatile |
| 22 | Viet Nam | 36 1000 t | 2023 | down 32.1% | volatile |
| 22 | China, Taiwan Province of | 36 1000 t | 2023 | down 65.0% | volatile |
| 25 | Czechia | 35 1000 t | 2023 | up 3,600.0% | volatile |
| 26 | New Zealand | 30 1000 t | 2023 | up 130.6% | volatile |
| 27 | Ecuador | 25 1000 t | 2023 | up 200.0% | volatile |
| 28 | Romania | 24 1000 t | 2023 | up 185.7% | volatile |
| 29 | Canada | 23 1000 t | 2023 | down 66.7% | volatile |
| 29 | Portugal | 23 1000 t | 2023 | down 52.1% | volatile |
| 31 | Australia and New Zealand | 22 1000 t | 2023 | up 123.2% | volatile |
| 32 | Bangladesh | 21 1000 t | 2023 | up 200.0% | volatile |
| 32 | Algeria | 21 1000 t | 2023 | down 12.5% | volatile |
| 32 | Greece | 21 1000 t | 2023 | down 58.0% | volatile |
| 32 | Mexico | 21 1000 t | 2023 | down 90.7% | volatile |
| 36 | Senegal | 18 1000 t | 2023 | up 125.0% | volatile |
| 37 | Sweden | 16 1000 t | 2023 | — | volatile |
| 38 | Israel | 15 1000 t | 2023 | up 137.5% | volatile |
| 39 | Croatia | 14 1000 t | 2023 | down 53.3% | volatile |
| 39 | Slovenia | 14 1000 t | 2023 | up 180.0% | volatile |
| 41 | Caribbean | 13 1000 t | 2023 | up 218.2% | volatile |
| 42 | Armenia | 11 1000 t | 2023 | up 1,000.0% | volatile |
| 42 | Honduras | 11 1000 t | 2023 | up 1,000.0% | volatile |
| 44 | Lithuania | 9 1000 t | 2023 | — | volatile |
| 45 | Argentina | 8 1000 t | 2023 | up 106.6% | volatile |
| 45 | Ukraine | 8 1000 t | 2023 | down 69.2% | volatile |
| 47 | Kuwait | 7 1000 t | 2023 | up 16.7% | volatile |
| 47 | Slovakia | 7 1000 t | 2023 | up 133.3% | volatile |
| 49 | Italy | 6 1000 t | 2023 | up 115.0% | volatile |
| 49 | Trinidad and Tobago | 6 1000 t | 2023 | down 25.0% | volatile |
| 51 | Ireland | 5 1000 t | 2023 | — | volatile |
| 51 | Kyrgyzstan | 5 1000 t | 2023 | up 400.0% | volatile |
| 51 | Libya | 5 1000 t | 2023 | down 88.9% | volatile |
| 51 | North Macedonia | 5 1000 t | 2023 | — | volatile |
| 55 | Finland | 4 1000 t | 2023 | down 78.9% | volatile |
| 55 | Jamaica | 4 1000 t | 2023 | up 180.0% | volatile |
| 55 | Norway | 4 1000 t | 2023 | down 91.8% | volatile |
| 55 | Nepal | 4 1000 t | 2023 | up 157.1% | volatile |
| 59 | Bahamas | 3 1000 t | 2023 | down 50.0% | volatile |
| 59 | Colombia | 3 1000 t | 2023 | unchanged | volatile |
| 59 | Estonia | 3 1000 t | 2023 | — | volatile |
| 59 | Namibia | 3 1000 t | 2023 | down 72.7% | volatile |
| 59 | Oman | 3 1000 t | 2023 | up 50.0% | volatile |
| 59 | Democratic Republic of the Congo | 3 1000 t | 2023 | up 50.0% | volatile |
| 65 | Ghana | 2 1000 t | 2023 | down 86.7% | volatile |
| 65 | Peru | 2 1000 t | 2023 | up 100.0% | volatile |
| 65 | Zimbabwe | 2 1000 t | 2023 | up 300.0% | volatile |
| 65 | Melanesia | 2 1000 t | 2023 | down 66.7% | volatile |
| 69 | Burkina Faso | 1 1000 t | 2023 | up 200.0% | volatile |
| 69 | Bosnia and Herzegovina | 1 1000 t | 2023 | up 200.0% | volatile |
| 69 | Bhutan | 1 1000 t | 2023 | — | volatile |
| 69 | Botswana | 1 1000 t | 2023 | down 75.0% | volatile |
| 69 | Iraq | 1 1000 t | 2023 | up 133.3% | volatile |
| 69 | Iceland | 1 1000 t | 2023 | unchanged | volatile |
| 69 | Jordan | 1 1000 t | 2023 | down 91.7% | volatile |
| 69 | Kazakhstan | 1 1000 t | 2023 | down 97.2% | volatile |
| 69 | Mauritania | 1 1000 t | 2023 | — | volatile |
| 69 | Malawi | 1 1000 t | 2023 | up 133.3% | volatile |
| 69 | Papua New Guinea | 1 1000 t | 2023 | unchanged | volatile |
| 69 | Tunisia | 1 1000 t | 2023 | unchanged | volatile |
| 69 | Yemen | 1 1000 t | 2023 | down 90.9% | volatile |
| 69 | Zambia | 1 1000 t | 2023 | up 114.3% | volatile |
| 69 | China, Hong Kong SAR | 1 1000 t | 2023 | down 95.7% | volatile |
| 69 | China, Macao SAR | 1 1000 t | 2023 | unchanged | volatile |
| 85 | Angola | 0 1000 t | 2023 | — | volatile |
| 85 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 85 | Barbados | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | Switzerland | 0 1000 t | 2023 | — | volatile |
| 85 | Cameroon | 0 1000 t | 2023 | — | volatile |
| 85 | Congo | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Costa Rica | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 85 | Dominican Republic | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | Fiji | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Gabon | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Guinea | 0 1000 t | 2023 | — | volatile |
| 85 | Gambia | 0 1000 t | 2023 | — | volatile |
| 85 | Grenada | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Guyana | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | Haiti | 0 1000 t | 2023 | — | volatile |
| 85 | Cambodia | 0 1000 t | 2023 | — | volatile |
| 85 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | volatile |
| 85 | Laos | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Liberia | 0 1000 t | 2023 | — | volatile |
| 85 | Saint Lucia | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | Sri Lanka | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | Lesotho | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 85 | Marshall Islands | 0 1000 t | 2023 | — | volatile |
| 85 | Malta | 0 1000 t | 2023 | up 100.0% | flat |
| 85 | Montenegro | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | Mongolia | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Mozambique | 0 1000 t | 2023 | down 100.0% | flat |
| 85 | Mauritius | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 85 | New Caledonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Niger | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | Nicaragua | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Panama | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Paraguay | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | French Polynesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Qatar | 0 1000 t | 2023 | — | volatile |
| 85 | Rwanda | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Solomon Islands | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Sierra Leone | 0 1000 t | 2023 | — | volatile |
| 85 | El Salvador | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | Sao Tome and Principe | 0 1000 t | 2023 | — | volatile |
| 85 | Suriname | 0 1000 t | 2023 | — | volatile |
| 85 | Seychelles | 0 1000 t | 2023 | — | volatile |
| 85 | Tajikistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | Turkmenistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | East Timor | 0 1000 t | 2023 | — | volatile |
| 85 | Tonga | 0 1000 t | 2023 | — | volatile |
| 85 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 85 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Samoa | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Micronesia | 0 1000 t | 2023 | — | volatile |
| 85 | Timor-Leste | 0 1000 t | 2023 | — | volatile |
| 85 | Cabo Verde | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Polynesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 85 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Lao People's Democratic Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | United Republic of Tanzania | 0 1000 t | 2023 | down 100.0% | volatile |
| 85 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | volatile |
| 154 | Albania | -1 1000 t | 2023 | up 50.0% | volatile |
| 154 | Belize | -1 1000 t | 2023 | — | volatile |
| 154 | Cuba | -1 1000 t | 2019 | up 75.0% | volatile |
| 154 | Madagascar | -1 1000 t | 2023 | down 133.3% | volatile |
| 154 | Maldives | -1 1000 t | 2023 | up 75.0% | volatile |
| 159 | Cote d'Ivoire | -2 1000 t | 2023 | down 150.0% | volatile |
| 159 | Myanmar | -2 1000 t | 2023 | down 140.0% | volatile |
| 159 | Eswatini | -2 1000 t | 2023 | down 100.0% | volatile |
| 159 | Côte d'Ivoire | -2 1000 t | 2023 | down 150.0% | volatile |
| 163 | Bahrain | -3 1000 t | 2023 | — | volatile |
| 163 | Cyprus | -3 1000 t | 2023 | down 200.0% | volatile |
| 163 | Ethiopia | -3 1000 t | 2023 | down 250.0% | volatile |
| 163 | Nigeria | -3 1000 t | 2023 | — | volatile |
| 167 | Georgia | -4 1000 t | 2023 | down 108.0% | volatile |
| 167 | Russia | -4 1000 t | 2023 | — | volatile |
| 167 | Russian Federation | -4 1000 t | 2023 | — | volatile |
| 170 | Latvia | -6 1000 t | 2023 | down 200.0% | volatile |
| 170 | Pakistan | -6 1000 t | 2023 | down 20.0% | volatile |
| 172 | Guatemala | -7 1000 t | 2023 | down 177.8% | volatile |
| 173 | Bulgaria | -8 1000 t | 2023 | — | volatile |
| 174 | Australia | -9 1000 t | 2023 | down 400.0% | volatile |
| 175 | Iran (Islamic Republic of) | -10 1000 t | 2023 | down 102.8% | volatile |
| 176 | Afghanistan | -11 1000 t | 2023 | up 62.1% | volatile |
| 177 | Spain | -12 1000 t | 2023 | up 64.7% | volatile |
| 178 | Belgium | -16 1000 t | 2023 | down 101.9% | volatile |
| 179 | Morocco | -21 1000 t | 2023 | down 231.2% | volatile |
| 180 | Germany | -24 1000 t | 2023 | up 88.6% | volatile |
| 181 | Azerbaijan | -26 1000 t | 2023 | down 4.0% | volatile |
| 182 | Syria | -27 1000 t | 2023 | down 228.6% | volatile |
| 182 | Syrian Arab Republic | -27 1000 t | 2023 | down 228.6% | volatile |
| 184 | Uzbekistan | -28 1000 t | 2023 | down 247.4% | volatile |
| 185 | Moldova | -47 1000 t | 2023 | down 1,466.7% | volatile |
| 185 | Republic of Moldova | -47 1000 t | 2023 | down 1,466.7% | volatile |
| 187 | South Africa | -52 1000 t | 2023 | down 152.0% | volatile |
| 188 | Serbia | -53 1000 t | 2023 | — | volatile |
| 189 | Kenya | -77 1000 t | 2023 | down 20.3% | volatile |
| 190 | Belarus | -93 1000 t | 2023 | down 97.9% | volatile |
| 191 | Poland | -98 1000 t | 2023 | down 476.5% | volatile |
| 192 | United Arab Emirates | -109 1000 t | 2023 | down 1.9% | volatile |
| 193 | Hungary | -203 1000 t | 2023 | down 206.8% | volatile |
| 194 | Philippines | -248 1000 t | 2023 | down 410.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 2,559 1000 t
- Asia 1,638 1000 t
- Eastern Asia 905 1000 t
- Americas 820 1000 t
- South America 635 1000 t
- Southern Asia 564 1000 t
- Western Europe 308 1000 t
- European Union (27) 198 1000 t
- Northern Europe 177 1000 t
- Northern America 148 1000 t
- Western Asia 134 1000 t
- Europe 125 1000 t
- United States of America 125 1000 t
- South-Eastern Asia 57 1000 t
- Northern Africa 54 1000 t
- Least Developed Countries (LDCs) 40 1000 t
- Oceania 24 1000 t
- Central America 24 1000 t
- Southern Europe 19 1000 t
- Western Africa 15 1000 t
- Small island developing States (SIDS) 13 1000 t
- Net Food Importing Developing Countries (NFIDCs) 10 1000 t
- Middle Africa 4 1000 t
- Central Asia -22 1000 t
- Africa -48 1000 t
- Southern Africa -51 1000 t
- Eastern Africa -70 1000 t
- Land Locked Developing Countries (LLDCs) -83 1000 t
- Low Income Food Deficit Countries (LIFDCs) -117 1000 t
- Eastern Europe -379 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.