Spices, Other — 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
Spices, Other — Stock Variation is currently reported for 181 countries. The highest value is 769 1000 t in India; the lowest is -28 1000 t in Indonesia.
The median across all reporting countries is 0 1000 t, and the mean is 7.07 1000 t.
The gap between the highest and lowest reporting country is a factor of about 27.
Over the past decade 25 countries rose and 18 fell. The largest increase was in India (up 8,644.4%), and the largest decrease in Syrian Arab Republic (down 1,000.0%).
Spices, Other — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 769 1000 t | 2023 | up 8,644.4% | volatile |
| 2 | China | 226 1000 t | 2023 | up 489.7% | volatile |
| 2 | China, mainland | 226 1000 t | 2023 | up 489.7% | volatile |
| 4 | Türkiye | 73 1000 t | 2023 | up 217.4% | volatile |
| 5 | Netherlands (Kingdom of the) | 17 1000 t | 2023 | — | volatile |
| 6 | Guatemala | 10 1000 t | 2023 | — | volatile |
| 7 | Canada | 6 1000 t | 2023 | up 200.0% | volatile |
| 7 | United Kingdom of Great Britain and Northern Ireland | 6 1000 t | 2023 | — | volatile |
| 9 | Myanmar | 4 1000 t | 2023 | — | volatile |
| 9 | Viet Nam | 4 1000 t | 2023 | down 73.3% | volatile |
| 11 | Brazil | 3 1000 t | 2023 | up 400.0% | volatile |
| 11 | Fiji | 3 1000 t | 2023 | up 250.0% | volatile |
| 11 | Melanesia | 3 1000 t | 2023 | up 250.0% | volatile |
| 14 | Belgium | 1 1000 t | 2023 | — | volatile |
| 14 | Bangladesh | 1 1000 t | 2023 | up 110.0% | volatile |
| 14 | Czechia | 1 1000 t | 2023 | — | volatile |
| 14 | Iraq | 1 1000 t | 2023 | up 200.0% | volatile |
| 14 | Kazakhstan | 1 1000 t | 2023 | — | volatile |
| 14 | Kuwait | 1 1000 t | 2023 | unchanged | volatile |
| 14 | Oman | 1 1000 t | 2023 | — | volatile |
| 14 | Pakistan | 1 1000 t | 2023 | down 50.0% | volatile |
| 14 | Peru | 1 1000 t | 2023 | unchanged | flat |
| 14 | Romania | 1 1000 t | 2023 | up 200.0% | volatile |
| 14 | Saudi Arabia | 1 1000 t | 2023 | — | volatile |
| 14 | Sweden | 1 1000 t | 2023 | — | volatile |
| 14 | Ukraine | 1 1000 t | 2023 | up 150.0% | volatile |
| 14 | Uzbekistan | 1 1000 t | 2023 | — | volatile |
| 14 | Saint Vincent and the Grenadines | 1 1000 t | 2023 | — | volatile |
| 14 | Yemen | 1 1000 t | 2023 | down 66.7% | volatile |
| 14 | Caribbean | 1 1000 t | 2023 | unchanged | volatile |
| 14 | United Republic of Tanzania | 1 1000 t | 2023 | — | volatile |
| 32 | Angola | 0 1000 t | 2023 | — | volatile |
| 32 | Albania | 0 1000 t | 2023 | — | volatile |
| 32 | Argentina | 0 1000 t | 2023 | — | flat |
| 32 | Armenia | 0 1000 t | 2023 | — | flat |
| 32 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 32 | Australia | 0 1000 t | 2023 | — | flat |
| 32 | Austria | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 32 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 32 | Bulgaria | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Bahrain | 0 1000 t | 2023 | — | flat |
| 32 | Bahamas | 0 1000 t | 2023 | — | flat |
| 32 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 32 | Belarus | 0 1000 t | 2023 | — | volatile |
| 32 | Belize | 0 1000 t | 2023 | — | flat |
| 32 | Barbados | 0 1000 t | 2023 | — | flat |
| 32 | Bhutan | 0 1000 t | 2023 | — | flat |
| 32 | Botswana | 0 1000 t | 2023 | — | flat |
| 32 | Switzerland | 0 1000 t | 2023 | — | volatile |
| 32 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Cameroon | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Congo | 0 1000 t | 2023 | — | volatile |
| 32 | Colombia | 0 1000 t | 2023 | — | volatile |
| 32 | Comoros | 0 1000 t | 2023 | — | volatile |
| 32 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 32 | Cuba | 0 1000 t | 2019 | — | flat |
| 32 | Cyprus | 0 1000 t | 2023 | — | flat |
| 32 | Germany | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Djibouti | 0 1000 t | 2023 | — | flat |
| 32 | Denmark | 0 1000 t | 2023 | — | volatile |
| 32 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 32 | Algeria | 0 1000 t | 2023 | — | volatile |
| 32 | Ecuador | 0 1000 t | 2023 | — | flat |
| 32 | Egypt | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Spain | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Estonia | 0 1000 t | 2023 | — | volatile |
| 32 | Ethiopia | 0 1000 t | 2023 | — | volatile |
| 32 | Finland | 0 1000 t | 2023 | — | flat |
| 32 | France | 0 1000 t | 2023 | — | flat |
| 32 | Gabon | 0 1000 t | 2023 | — | flat |
| 32 | Georgia | 0 1000 t | 2023 | — | flat |
| 32 | Ghana | 0 1000 t | 2023 | — | volatile |
| 32 | Guinea | 0 1000 t | 2023 | — | flat |
| 32 | Gambia | 0 1000 t | 2023 | — | flat |
| 32 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 32 | Greece | 0 1000 t | 2023 | — | volatile |
| 32 | Grenada | 0 1000 t | 2023 | — | flat |
| 32 | Guyana | 0 1000 t | 2023 | — | volatile |
| 32 | Honduras | 0 1000 t | 2023 | — | flat |
| 32 | Croatia | 0 1000 t | 2023 | — | volatile |
| 32 | Haiti | 0 1000 t | 2023 | — | flat |
| 32 | Hungary | 0 1000 t | 2023 | — | volatile |
| 32 | Ireland | 0 1000 t | 2023 | — | volatile |
| 32 | Iceland | 0 1000 t | 2023 | — | flat |
| 32 | Israel | 0 1000 t | 2023 | — | volatile |
| 32 | Italy | 0 1000 t | 2023 | — | volatile |
| 32 | Jamaica | 0 1000 t | 2023 | down 100.0% | flat |
| 32 | Jordan | 0 1000 t | 2023 | — | volatile |
| 32 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 32 | Cambodia | 0 1000 t | 2023 | — | flat |
| 32 | Kiribati | 0 1000 t | 2023 | — | flat |
| 32 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 32 | Lebanon | 0 1000 t | 2023 | — | flat |
| 32 | Liberia | 0 1000 t | 2023 | — | flat |
| 32 | Libya | 0 1000 t | 2023 | — | flat |
| 32 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 32 | Sri Lanka | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Lesotho | 0 1000 t | 2023 | — | flat |
| 32 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 32 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 32 | Latvia | 0 1000 t | 2023 | — | flat |
| 32 | Morocco | 0 1000 t | 2023 | — | volatile |
| 32 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 32 | Maldives | 0 1000 t | 2023 | — | volatile |
| 32 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 32 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 32 | Malta | 0 1000 t | 2023 | — | flat |
| 32 | Montenegro | 0 1000 t | 2023 | — | flat |
| 32 | Mongolia | 0 1000 t | 2023 | — | flat |
| 32 | Mozambique | 0 1000 t | 2023 | — | flat |
| 32 | Mauritania | 0 1000 t | 2023 | — | flat |
| 32 | Mauritius | 0 1000 t | 2023 | — | flat |
| 32 | Malawi | 0 1000 t | 2023 | — | flat |
| 32 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 32 | Namibia | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 32 | Niger | 0 1000 t | 2023 | — | flat |
| 32 | Nicaragua | 0 1000 t | 2023 | — | flat |
| 32 | Norway | 0 1000 t | 2023 | — | volatile |
| 32 | Nauru | 0 1000 t | 2023 | — | flat |
| 32 | New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Panama | 0 1000 t | 2023 | — | flat |
| 32 | Philippines | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Papua New Guinea | 0 1000 t | 2023 | — | volatile |
| 32 | Portugal | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Paraguay | 0 1000 t | 2023 | — | flat |
| 32 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 32 | Qatar | 0 1000 t | 2023 | — | flat |
| 32 | Rwanda | 0 1000 t | 2023 | — | flat |
| 32 | Senegal | 0 1000 t | 2023 | — | volatile |
| 32 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 32 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 32 | El Salvador | 0 1000 t | 2023 | — | flat |
| 32 | Serbia | 0 1000 t | 2023 | — | flat |
| 32 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 32 | Suriname | 0 1000 t | 2023 | — | flat |
| 32 | Slovakia | 0 1000 t | 2023 | — | volatile |
| 32 | Slovenia | 0 1000 t | 2023 | — | flat |
| 32 | Eswatini | 0 1000 t | 2023 | — | flat |
| 32 | Seychelles | 0 1000 t | 2023 | — | flat |
| 32 | Thailand | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 32 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 32 | Tonga | 0 1000 t | 2023 | — | flat |
| 32 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 32 | Tunisia | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 32 | Uganda | 0 1000 t | 2023 | — | flat |
| 32 | Uruguay | 0 1000 t | 2023 | — | flat |
| 32 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 32 | Samoa | 0 1000 t | 2023 | — | flat |
| 32 | Zambia | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Zimbabwe | 0 1000 t | 2023 | — | flat |
| 32 | Micronesia | 0 1000 t | 2023 | — | flat |
| 32 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 32 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 32 | Polynesia | 0 1000 t | 2023 | — | flat |
| 32 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 32 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 32 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 32 | Republic of Korea | 0 1000 t | 2023 | down 100.0% | volatile |
| 32 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 32 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 32 | Australia and New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 32 | Côte d'Ivoire | 0 1000 t | 2023 | up 100.0% | flat |
| 32 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | volatile |
| 32 | China, Taiwan Province of | 0 1000 t | 2023 | — | volatile |
| 32 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
| 32 | China, Macao SAR | 0 1000 t | 2023 | — | volatile |
| 172 | Afghanistan | -1 1000 t | 2023 | down 150.0% | volatile |
| 173 | Poland | -2 1000 t | 2023 | down 300.0% | volatile |
| 174 | Kenya | -3 1000 t | 2023 | down 200.0% | volatile |
| 174 | Russian Federation | -3 1000 t | 2023 | — | volatile |
| 176 | United Arab Emirates | -6 1000 t | 2023 | down 220.0% | volatile |
| 177 | Nepal | -9 1000 t | 2023 | — | volatile |
| 177 | Syrian Arab Republic | -9 1000 t | 2023 | down 1,000.0% | volatile |
| 179 | Nigeria | -11 1000 t | 2023 | down 134.4% | volatile |
| 180 | Iran (Islamic Republic of) | -16 1000 t | 2023 | down 45.5% | volatile |
| 181 | Indonesia | -28 1000 t | 2023 | up 9.7% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 1,057 1000 t
- Asia 1,017 1000 t
- Southern Asia 744 1000 t
- Eastern Asia 228 1000 t
- Western Asia 63 1000 t
- Americas 28 1000 t
- Europe 23 1000 t
- European Union (27) 20 1000 t
- Western Europe 19 1000 t
- Northern America 12 1000 t
- Central America 10 1000 t
- Northern Europe 7 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.