Pineapples 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
Pineapples and products — Stock Variation is currently reported for 139 countries. The highest value is 243 1000 t in Netherlands (Kingdom of the); the lowest is -247 1000 t in Philippines.
The median across all reporting countries is 0 1000 t, and the mean is 2.27 1000 t.
Over the past decade 40 countries rose and 44 fell. The largest increase was in Netherlands (Kingdom of the) (up 586.0%), and the largest decrease in Philippines (down 1,472.2%).
Pineapples and products — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Netherlands (Kingdom of the) | 243 1000 t | 2023 | up 586.0% | volatile |
| 2 | Indonesia | 153 1000 t | 2023 | up 313.5% | volatile |
| 3 | Lebanon | 61 1000 t | 2023 | up 221.1% | volatile |
| 4 | Austria | 25 1000 t | 2023 | up 316.7% | volatile |
| 4 | Vietnam | 25 1000 t | 2023 | up 316.7% | volatile |
| 4 | Viet Nam | 25 1000 t | 2023 | up 316.7% | volatile |
| 7 | China | 23 1000 t | 2023 | down 42.5% | volatile |
| 8 | China, mainland | 18 1000 t | 2023 | up 20.0% | volatile |
| 9 | Thailand | 13 1000 t | 2023 | up 103.9% | volatile |
| 9 | Iran (Islamic Republic of) | 13 1000 t | 2023 | up 44.4% | volatile |
| 11 | Morocco | 8 1000 t | 2023 | — | volatile |
| 12 | China, Taiwan Province of | 5 1000 t | 2023 | down 80.0% | volatile |
| 13 | Egypt | 4 1000 t | 2023 | up 233.3% | volatile |
| 14 | Spain | 3 1000 t | 2023 | — | volatile |
| 14 | Greece | 3 1000 t | 2023 | — | volatile |
| 14 | El Salvador | 3 1000 t | 2023 | up 111.1% | volatile |
| 17 | Jamaica | 2 1000 t | 2023 | up 150.0% | volatile |
| 17 | Romania | 2 1000 t | 2023 | up 300.0% | volatile |
| 17 | Zambia | 2 1000 t | 2023 | — | volatile |
| 17 | Caribbean | 2 1000 t | 2023 | up 140.0% | volatile |
| 17 | Republic of Korea | 2 1000 t | 2023 | unchanged | volatile |
| 22 | Germany | 1 1000 t | 2023 | — | volatile |
| 22 | Guatemala | 1 1000 t | 2023 | down 87.5% | volatile |
| 22 | Ireland | 1 1000 t | 2023 | — | volatile |
| 22 | Poland | 1 1000 t | 2023 | down 92.9% | volatile |
| 22 | Slovenia | 1 1000 t | 2023 | down 75.0% | volatile |
| 22 | Turkey | 1 1000 t | 2023 | — | volatile |
| 22 | Uzbekistan | 1 1000 t | 2023 | — | volatile |
| 22 | Türkiye | 1 1000 t | 2023 | — | volatile |
| 30 | Angola | 0 1000 t | 2023 | — | volatile |
| 30 | United Arab Emirates | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Argentina | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Antigua and Barbuda | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Australia | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 30 | Belgium | 0 1000 t | 2023 | — | volatile |
| 30 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 30 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 30 | Bulgaria | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Bahrain | 0 1000 t | 2023 | — | volatile |
| 30 | Bahamas | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | volatile |
| 30 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Brazil | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Canada | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Switzerland | 0 1000 t | 2023 | — | volatile |
| 30 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Cote d'Ivoire | 0 1000 t | 2023 | down 100.0% | flat |
| 30 | Congo | 0 1000 t | 2023 | — | volatile |
| 30 | Colombia | 0 1000 t | 2023 | — | volatile |
| 30 | Costa Rica | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Cuba | 0 1000 t | 2019 | up 100.0% | volatile |
| 30 | Cyprus | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Czechia | 0 1000 t | 2023 | — | volatile |
| 30 | Denmark | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Algeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Ecuador | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Estonia | 0 1000 t | 2023 | — | volatile |
| 30 | Ethiopia | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Finland | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Fiji | 0 1000 t | 2023 | — | volatile |
| 30 | France | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | United Kingdom | 0 1000 t | 2023 | — | volatile |
| 30 | Ghana | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Guinea | 0 1000 t | 2023 | — | volatile |
| 30 | Guyana | 0 1000 t | 2023 | — | volatile |
| 30 | Honduras | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Croatia | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Haiti | 0 1000 t | 2023 | — | volatile |
| 30 | Hungary | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | India | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Israel | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Italy | 0 1000 t | 2023 | — | volatile |
| 30 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | flat |
| 30 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 30 | Kuwait | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Libya | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 30 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 30 | Luxembourg | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Latvia | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Maldives | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Marshall Islands | 0 1000 t | 2023 | — | volatile |
| 30 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 30 | Malta | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 30 | Montenegro | 0 1000 t | 2023 | — | volatile |
| 30 | Mongolia | 0 1000 t | 2023 | — | volatile |
| 30 | Mauritania | 0 1000 t | 2023 | — | volatile |
| 30 | Mauritius | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Malawi | 0 1000 t | 2023 | — | volatile |
| 30 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 30 | Namibia | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | New Caledonia | 0 1000 t | 2023 | down 100.0% | flat |
| 30 | Niger | 0 1000 t | 2023 | — | volatile |
| 30 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 30 | Nicaragua | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Norway | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Nepal | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Oman | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Pakistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Panama | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Peru | 0 1000 t | 2023 | — | flat |
| 30 | Portugal | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | French Polynesia | 0 1000 t | 2023 | — | volatile |
| 30 | Qatar | 0 1000 t | 2023 | — | volatile |
| 30 | Russia | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Saudi Arabia | 0 1000 t | 2023 | — | volatile |
| 30 | Senegal | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Sao Tome and Principe | 0 1000 t | 2023 | — | volatile |
| 30 | Suriname | 0 1000 t | 2023 | — | volatile |
| 30 | Slovakia | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Sweden | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Eswatini | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Syria | 0 1000 t | 2023 | up 100.0% | flat |
| 30 | Trinidad and Tobago | 0 1000 t | 2023 | — | volatile |
| 30 | Tunisia | 0 1000 t | 2023 | down 100.0% | flat |
| 30 | Ukraine | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 30 | United States | 0 1000 t | 2023 | — | volatile |
| 30 | Yemen | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | South Africa | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Micronesia | 0 1000 t | 2023 | — | volatile |
| 30 | Cabo Verde | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Melanesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Polynesia | 0 1000 t | 2023 | — | volatile |
| 30 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 30 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 30 | Russian Federation | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Syrian Arab Republic | 0 1000 t | 2023 | up 100.0% | flat |
| 30 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Australia and New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Côte d'Ivoire | 0 1000 t | 2023 | down 100.0% | flat |
| 30 | United Republic of Tanzania | 0 1000 t | 2023 | down 100.0% | flat |
| 30 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | volatile |
| 183 | Kenya | -80 1000 t | 2023 | down 29.0% | volatile |
| 184 | Philippines | -247 1000 t | 2023 | down 1,472.2% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Europe 281 1000 t
- European Union (27) 280 1000 t
- Western Europe 270 1000 t
- World 268 1000 t
- Western Asia 63 1000 t
- Asia 47 1000 t
- Eastern Asia 26 1000 t
- Southern Asia 13 1000 t
- Northern Africa 12 1000 t
- Southern Europe 7 1000 t
- Americas 6 1000 t
- Eastern Europe 3 1000 t
- Central America 3 1000 t
- Land Locked Developing Countries (LLDCs) 3 1000 t
- Small island developing States (SIDS) 2 1000 t
- Least Developed Countries (LDCs) 2 1000 t
- Central Asia 1 1000 t
- Northern Europe 1 1000 t
- Oceania 0 1000 t
- South America 0 1000 t
- Northern America 0 1000 t
- Southern Africa 0 1000 t
- Middle Africa 0 1000 t
- United States of America 0 1000 t
- Western Africa -2 1000 t
- South-Eastern Asia -56 1000 t
- Net Food Importing Developing Countries (NFIDCs) -61 1000 t
- Africa -66 1000 t
- Eastern Africa -76 1000 t
- Low Income Food Deficit Countries (LIFDCs) -78 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.