Apples and products — 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...
What the numbers show
Apples and products — Stock Variation is currently reported for 161 countries. The highest value is 738 1000 t in China; the lowest is -204 1000 t in Hungary.
The median across all reporting countries is 0 1000 t, and the mean is 10.67 1000 t.
The gap between the highest and lowest reporting country is a factor of about 4.
Over the past decade 46 countries rose and 51 fell. The largest increase was in United Kingdom (up 1,242.9%), and the largest decrease in Guatemala (down 500.0%).
Apples and products — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 738 1000 t | 2023 | up 169.3% | volatile |
| 2 | China, mainland | 719 1000 t | 2023 | up 171.3% | volatile |
| 3 | Turkey | 153 1000 t | 2023 | down 59.0% | volatile |
| 3 | Türkiye | 153 1000 t | 2023 | down 59.0% | volatile |
| 5 | Chile | 115 1000 t | 2023 | up 282.5% | volatile |
| 6 | United Kingdom | 94 1000 t | 2023 | up 1,242.9% | volatile |
| 6 | United Kingdom of Great Britain and Northern Ireland | 94 1000 t | 2023 | up 1,242.9% | volatile |
| 8 | Afghanistan | 81 1000 t | 2023 | up 307.7% | volatile |
| 9 | Democratic People's Republic of Korea | 75 1000 t | 2018 | up 250.0% | volatile |
| 10 | France | 55 1000 t | 2023 | — | volatile |
| 11 | Denmark | 38 1000 t | 2023 | up 100.0% | volatile |
| 12 | Brazil | 27 1000 t | 2023 | up 184.4% | volatile |
| 13 | New Zealand | 24 1000 t | 2023 | up 134.3% | volatile |
| 14 | Canada | 22 1000 t | 2023 | up 283.3% | volatile |
| 14 | Greece | 22 1000 t | 2023 | up 10.0% | volatile |
| 16 | Thailand | 20 1000 t | 2023 | up 900.0% | volatile |
| 16 | Australia and New Zealand | 20 1000 t | 2023 | up 119.2% | volatile |
| 18 | Bangladesh | 18 1000 t | 2023 | up 260.0% | volatile |
| 19 | China, Taiwan Province of | 17 1000 t | 2023 | up 183.3% | volatile |
| 20 | Romania | 12 1000 t | 2023 | up 1,100.0% | volatile |
| 20 | Saudi Arabia | 12 1000 t | 2023 | — | volatile |
| 22 | Honduras | 10 1000 t | 2023 | — | volatile |
| 22 | Indonesia | 10 1000 t | 2023 | unchanged | volatile |
| 24 | Lithuania | 9 1000 t | 2023 | — | volatile |
| 24 | Senegal | 9 1000 t | 2023 | — | volatile |
| 26 | Italy | 7 1000 t | 2023 | — | volatile |
| 26 | Sweden | 7 1000 t | 2023 | up 40.0% | volatile |
| 28 | Argentina | 6 1000 t | 2023 | down 92.1% | volatile |
| 29 | Croatia | 5 1000 t | 2023 | down 83.3% | volatile |
| 29 | North Macedonia | 5 1000 t | 2023 | — | volatile |
| 31 | Libya | 4 1000 t | 2023 | down 77.8% | volatile |
| 32 | Nepal | 3 1000 t | 2023 | up 250.0% | volatile |
| 33 | Colombia | 2 1000 t | 2023 | up 100.0% | volatile |
| 33 | Estonia | 2 1000 t | 2023 | — | volatile |
| 33 | India | 2 1000 t | 2023 | up 100.5% | volatile |
| 33 | Kenya | 2 1000 t | 2023 | up 100.0% | volatile |
| 33 | Portugal | 2 1000 t | 2023 | down 91.7% | volatile |
| 33 | Russia | 2 1000 t | 2023 | — | volatile |
| 33 | Slovakia | 2 1000 t | 2023 | up 300.0% | volatile |
| 33 | Ukraine | 2 1000 t | 2023 | down 60.0% | volatile |
| 33 | Russian Federation | 2 1000 t | 2023 | — | volatile |
| 42 | Bosnia and Herzegovina | 1 1000 t | 2023 | up 200.0% | volatile |
| 42 | Iceland | 1 1000 t | 2023 | unchanged | volatile |
| 42 | Kyrgyzstan | 1 1000 t | 2023 | unchanged | volatile |
| 42 | Namibia | 1 1000 t | 2023 | — | volatile |
| 42 | Yemen | 1 1000 t | 2023 | down 85.7% | volatile |
| 42 | Zimbabwe | 1 1000 t | 2023 | up 200.0% | volatile |
| 42 | Democratic Republic of the Congo | 1 1000 t | 2023 | unchanged | volatile |
| 42 | Caribbean | 1 1000 t | 2023 | — | volatile |
| 42 | Netherlands (Kingdom of the) | 1 1000 t | 2023 | — | volatile |
| 42 | China, Macao SAR | 1 1000 t | 2023 | — | volatile |
| 52 | Angola | 0 1000 t | 2023 | — | volatile |
| 52 | Armenia | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 52 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 52 | Bahrain | 0 1000 t | 2023 | — | flat |
| 52 | Bahamas | 0 1000 t | 2023 | down 100.0% | flat |
| 52 | Barbados | 0 1000 t | 2023 | — | volatile |
| 52 | Bhutan | 0 1000 t | 2023 | — | volatile |
| 52 | Botswana | 0 1000 t | 2023 | — | volatile |
| 52 | Switzerland | 0 1000 t | 2023 | — | volatile |
| 52 | Cote d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 52 | Cameroon | 0 1000 t | 2023 | down 100.0% | flat |
| 52 | Congo | 0 1000 t | 2023 | — | volatile |
| 52 | Costa Rica | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Czechia | 0 1000 t | 2023 | down 100.0% | falling |
| 52 | Dominican Republic | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Algeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Egypt | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Spain | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Ethiopia | 0 1000 t | 2023 | — | volatile |
| 52 | Finland | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Fiji | 0 1000 t | 2023 | — | volatile |
| 52 | Gabon | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Ghana | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Guinea | 0 1000 t | 2023 | — | volatile |
| 52 | Haiti | 0 1000 t | 2023 | — | volatile |
| 52 | Ireland | 0 1000 t | 2023 | — | volatile |
| 52 | Iraq | 0 1000 t | 2023 | — | volatile |
| 52 | Israel | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Jamaica | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Jordan | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Cambodia | 0 1000 t | 2023 | — | volatile |
| 52 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | volatile |
| 52 | Kuwait | 0 1000 t | 2023 | — | volatile |
| 52 | Liberia | 0 1000 t | 2023 | — | volatile |
| 52 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 52 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 52 | Lesotho | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 52 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 52 | Maldives | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Malta | 0 1000 t | 2023 | — | volatile |
| 52 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 52 | Montenegro | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Mongolia | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Mauritania | 0 1000 t | 2023 | — | volatile |
| 52 | Mauritius | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Malawi | 0 1000 t | 2023 | — | volatile |
| 52 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 52 | New Caledonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Niger | 0 1000 t | 2023 | — | volatile |
| 52 | Nicaragua | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Norway | 0 1000 t | 2023 | down 100.0% | flat |
| 52 | Oman | 0 1000 t | 2023 | — | volatile |
| 52 | Panama | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Philippines | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Papua New Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Paraguay | 0 1000 t | 2023 | — | volatile |
| 52 | French Polynesia | 0 1000 t | 2023 | — | volatile |
| 52 | Qatar | 0 1000 t | 2023 | — | volatile |
| 52 | Sierra Leone | 0 1000 t | 2023 | — | volatile |
| 52 | El Salvador | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Slovenia | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Eswatini | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Tajikistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Turkmenistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Trinidad and Tobago | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Tunisia | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 52 | United States | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Uzbekistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | South Africa | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Zambia | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Cabo Verde | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Melanesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Polynesia | 0 1000 t | 2023 | — | volatile |
| 52 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 52 | China, Hong Kong SAR | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Republic of Korea | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | flat |
| 52 | Côte d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 52 | United Republic of Tanzania | 0 1000 t | 2023 | down 100.0% | flat |
| 168 | Bulgaria | -1 1000 t | 2023 | up 75.0% | volatile |
| 168 | Cuba | -1 1000 t | 2019 | — | volatile |
| 168 | Cyprus | -1 1000 t | 2023 | up 66.7% | volatile |
| 168 | Ecuador | -1 1000 t | 2023 | — | flat |
| 168 | Kazakhstan | -1 1000 t | 2023 | down 116.7% | volatile |
| 173 | Australia | -4 1000 t | 2023 | up 88.2% | volatile |
| 173 | Austria | -4 1000 t | 2023 | up 86.7% | volatile |
| 173 | Guatemala | -4 1000 t | 2023 | down 500.0% | volatile |
| 176 | Georgia | -5 1000 t | 2023 | — | volatile |
| 176 | Nigeria | -5 1000 t | 2023 | down 150.0% | volatile |
| 178 | Latvia | -8 1000 t | 2023 | down 300.0% | volatile |
| 179 | Pakistan | -13 1000 t | 2023 | up 27.8% | volatile |
| 180 | Belgium | -18 1000 t | 2023 | — | volatile |
| 181 | Lebanon | -21 1000 t | 2023 | up 19.2% | volatile |
| 182 | Azerbaijan | -27 1000 t | 2023 | down 3.8% | volatile |
| 183 | Iran (Islamic Republic of) | -28 1000 t | 2023 | down 107.9% | volatile |
| 184 | Syria | -30 1000 t | 2023 | down 330.8% | volatile |
| 184 | Syrian Arab Republic | -30 1000 t | 2023 | down 330.8% | volatile |
| 186 | Morocco | -31 1000 t | 2023 | down 219.2% | volatile |
| 187 | Germany | -46 1000 t | 2023 | up 78.2% | volatile |
| 188 | Moldova | -47 1000 t | 2023 | — | volatile |
| 188 | Republic of Moldova | -47 1000 t | 2023 | — | volatile |
| 190 | Serbia | -53 1000 t | 2023 | — | volatile |
| 191 | United Arab Emirates | -77 1000 t | 2023 | down 327.8% | volatile |
| 192 | Belarus | -93 1000 t | 2023 | down 57.6% | volatile |
| 193 | Poland | -94 1000 t | 2023 | down 38.2% | volatile |
| 194 | Hungary | -204 1000 t | 2023 | down 207.4% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Asia 818 1000 t
- Eastern Asia 720 1000 t
- World 703 1000 t
- Americas 178 1000 t
- South America 149 1000 t
- Northern Europe 143 1000 t
- Least Developed Countries (LDCs) 116 1000 t
- Net Food Importing Developing Countries (NFIDCs) 85 1000 t
- Southern Asia 63 1000 t
- Low Income Food Deficit Countries (LIFDCs) 59 1000 t
- South-Eastern Asia 30 1000 t
- Northern America 22 1000 t
- Oceania 20 1000 t
- Land Locked Developing Countries (LLDCs) 17 1000 t
- Central America 6 1000 t
- Eastern Africa 5 1000 t
- Western Asia 5 1000 t
- Western Africa 4 1000 t
- Middle Africa 2 1000 t
- Small island developing States (SIDS) 0 1000 t
- Central Asia 0 1000 t
- Southern Africa 0 1000 t
- United States of America 0 1000 t
- Southern Europe -9 1000 t
- Western Europe -11 1000 t
- Africa -16 1000 t
- Northern Africa -27 1000 t
- European Union (27) -211 1000 t
- Europe -298 1000 t
- Eastern Europe -420 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.