Spices — 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 — Stock Variation is currently reported for 130 countries. The highest value is 1,084 1000 t in India; the lowest is -19 1000 t in Indonesia.
The median across all reporting countries is 0 1000 t, and the mean is 14.3 1000 t.
The gap between the highest and lowest reporting country is a factor of about 57.
Over the past decade 37 countries rose and 23 fell. The largest increase was in Brazil (up 2,300.0%), and the largest decrease in Syria (down 550.0%).
Spices — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 1,084 1000 t | 2023 | up 617.9% | volatile |
| 2 | China | 224 1000 t | 2023 | up 961.5% | volatile |
| 3 | China, mainland | 223 1000 t | 2023 | up 957.7% | volatile |
| 4 | Turkey | 73 1000 t | 2023 | up 160.7% | volatile |
| 4 | Türkiye | 73 1000 t | 2023 | up 160.7% | volatile |
| 6 | Bangladesh | 72 1000 t | 2023 | up 460.0% | volatile |
| 7 | Ethiopia | 34 1000 t | 2023 | up 126.7% | volatile |
| 8 | Brazil | 22 1000 t | 2023 | up 2,300.0% | volatile |
| 8 | United States | 22 1000 t | 2023 | — | volatile |
| 10 | Netherlands (Kingdom of the) | 16 1000 t | 2023 | — | volatile |
| 11 | Iraq | 14 1000 t | 2023 | up 1,500.0% | volatile |
| 12 | Guatemala | 10 1000 t | 2023 | — | volatile |
| 13 | United Kingdom | 8 1000 t | 2023 | — | volatile |
| 13 | Pakistan | 8 1000 t | 2023 | down 38.5% | volatile |
| 13 | Vietnam | 8 1000 t | 2023 | down 38.5% | volatile |
| 13 | Viet Nam | 8 1000 t | 2023 | down 38.5% | volatile |
| 13 | United Kingdom of Great Britain and Northern Ireland | 8 1000 t | 2023 | — | volatile |
| 18 | Canada | 7 1000 t | 2023 | up 600.0% | volatile |
| 19 | Ghana | 6 1000 t | 2023 | up 700.0% | volatile |
| 20 | Myanmar | 4 1000 t | 2023 | — | volatile |
| 21 | Burkina Faso | 3 1000 t | 2023 | — | volatile |
| 21 | Cameroon | 3 1000 t | 2023 | up 250.0% | volatile |
| 21 | Fiji | 3 1000 t | 2023 | up 250.0% | volatile |
| 21 | Kazakhstan | 3 1000 t | 2023 | up 400.0% | volatile |
| 21 | Melanesia | 3 1000 t | 2023 | up 250.0% | volatile |
| 26 | Saudi Arabia | 2 1000 t | 2023 | — | volatile |
| 26 | Caribbean | 2 1000 t | 2023 | up 100.0% | volatile |
| 28 | Austria | 1 1000 t | 2023 | unchanged | volatile |
| 28 | Belgium | 1 1000 t | 2023 | — | volatile |
| 28 | Switzerland | 1 1000 t | 2023 | unchanged | falling |
| 28 | Cote d'Ivoire | 1 1000 t | 2023 | up 200.0% | volatile |
| 28 | Czechia | 1 1000 t | 2023 | — | volatile |
| 28 | Germany | 1 1000 t | 2023 | down 75.0% | volatile |
| 28 | Ecuador | 1 1000 t | 2023 | — | volatile |
| 28 | Cambodia | 1 1000 t | 2023 | — | volatile |
| 28 | Kuwait | 1 1000 t | 2023 | unchanged | volatile |
| 28 | Nepal | 1 1000 t | 2023 | — | volatile |
| 28 | Oman | 1 1000 t | 2023 | — | volatile |
| 28 | Peru | 1 1000 t | 2023 | unchanged | volatile |
| 28 | Portugal | 1 1000 t | 2023 | up 200.0% | volatile |
| 28 | Romania | 1 1000 t | 2023 | up 200.0% | volatile |
| 28 | Sweden | 1 1000 t | 2023 | — | volatile |
| 28 | Ukraine | 1 1000 t | 2023 | up 150.0% | volatile |
| 28 | Saint Vincent and the Grenadines | 1 1000 t | 2023 | — | volatile |
| 28 | Yemen | 1 1000 t | 2023 | down 66.7% | volatile |
| 28 | South Africa | 1 1000 t | 2023 | unchanged | volatile |
| 28 | Zimbabwe | 1 1000 t | 2023 | — | volatile |
| 28 | Côte d'Ivoire | 1 1000 t | 2023 | up 200.0% | volatile |
| 28 | United Republic of Tanzania | 1 1000 t | 2023 | up 200.0% | volatile |
| 28 | China, Taiwan Province of | 1 1000 t | 2023 | — | volatile |
| 28 | Democratic People's Republic of Korea | 1 1000 t | 2018 | — | volatile |
| 52 | Angola | 0 1000 t | 2023 | — | volatile |
| 52 | Albania | 0 1000 t | 2023 | — | volatile |
| 52 | Argentina | 0 1000 t | 2023 | — | flat |
| 52 | Australia | 0 1000 t | 2023 | — | flat |
| 52 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 52 | Bulgaria | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | volatile |
| 52 | Belarus | 0 1000 t | 2023 | — | volatile |
| 52 | Bhutan | 0 1000 t | 2023 | — | flat |
| 52 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Congo | 0 1000 t | 2023 | — | volatile |
| 52 | Colombia | 0 1000 t | 2023 | — | volatile |
| 52 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 52 | Cuba | 0 1000 t | 2019 | up 100.0% | volatile |
| 52 | Denmark | 0 1000 t | 2023 | — | volatile |
| 52 | Algeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Egypt | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Spain | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Estonia | 0 1000 t | 2023 | — | volatile |
| 52 | Finland | 0 1000 t | 2023 | — | volatile |
| 52 | France | 0 1000 t | 2023 | — | volatile |
| 52 | Gambia | 0 1000 t | 2023 | — | volatile |
| 52 | Greece | 0 1000 t | 2023 | — | volatile |
| 52 | Guyana | 0 1000 t | 2023 | — | volatile |
| 52 | Honduras | 0 1000 t | 2023 | — | volatile |
| 52 | Croatia | 0 1000 t | 2023 | — | volatile |
| 52 | Hungary | 0 1000 t | 2023 | — | volatile |
| 52 | Ireland | 0 1000 t | 2023 | — | volatile |
| 52 | Israel | 0 1000 t | 2023 | — | volatile |
| 52 | Italy | 0 1000 t | 2023 | — | volatile |
| 52 | Jamaica | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Jordan | 0 1000 t | 2023 | — | volatile |
| 52 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 52 | Laos | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Lebanon | 0 1000 t | 2023 | — | volatile |
| 52 | Libya | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 52 | Morocco | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Madagascar | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Maldives | 0 1000 t | 2023 | — | volatile |
| 52 | Mexico | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 52 | Malawi | 0 1000 t | 2023 | — | volatile |
| 52 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 52 | Namibia | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Niger | 0 1000 t | 2023 | up 100.0% | flat |
| 52 | Norway | 0 1000 t | 2023 | — | volatile |
| 52 | New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Philippines | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Papua New Guinea | 0 1000 t | 2023 | — | volatile |
| 52 | Qatar | 0 1000 t | 2023 | — | volatile |
| 52 | Senegal | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Sierra Leone | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Slovakia | 0 1000 t | 2023 | — | flat |
| 52 | Zambia | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 52 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 52 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 52 | Republic of Korea | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | volatile |
| 52 | Australia and New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 52 | Lao People's Democratic Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 52 | China, Macao SAR | 0 1000 t | 2023 | — | volatile |
| 179 | Afghanistan | -1 1000 t | 2023 | down 150.0% | volatile |
| 179 | Sri Lanka | -1 1000 t | 2023 | up 88.9% | volatile |
| 179 | Tunisia | -1 1000 t | 2023 | unchanged | volatile |
| 182 | Poland | -2 1000 t | 2023 | down 300.0% | volatile |
| 182 | Russia | -2 1000 t | 2023 | — | volatile |
| 182 | Russian Federation | -2 1000 t | 2023 | — | volatile |
| 185 | Kenya | -3 1000 t | 2023 | down 200.0% | volatile |
| 186 | Comoros | -4 1000 t | 2023 | — | volatile |
| 187 | Uzbekistan | -7 1000 t | 2023 | — | volatile |
| 188 | United Arab Emirates | -8 1000 t | 2023 | down 300.0% | volatile |
| 189 | Syria | -9 1000 t | 2023 | down 550.0% | volatile |
| 189 | Syrian Arab Republic | -9 1000 t | 2023 | down 550.0% | volatile |
| 191 | Nigeria | -11 1000 t | 2023 | down 135.5% | volatile |
| 192 | Thailand | -13 1000 t | 2023 | up 7.1% | volatile |
| 193 | Iran (Islamic Republic of) | -16 1000 t | 2023 | down 33.3% | volatile |
| 194 | Indonesia | -19 1000 t | 2023 | up 32.1% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 1,554 1000 t
- Asia 1,427 1000 t
- Southern Asia 1,147 1000 t
- Eastern Asia 227 1000 t
- Net Food Importing Developing Countries (NFIDCs) 118 1000 t
- Least Developed Countries (LDCs) 110 1000 t
- Western Asia 76 1000 t
- Americas 64 1000 t
- Eastern Africa 31 1000 t
- Africa 30 1000 t
- Land Locked Developing Countries (LLDCs) 30 1000 t
- Europe 29 1000 t
- Northern America 29 1000 t
- South America 24 1000 t
- United States of America 22 1000 t
- European Union (27) 21 1000 t
- Western Europe 19 1000 t
- Low Income Food Deficit Countries (LIFDCs) 17 1000 t
- Central America 10 1000 t
- Northern Europe 9 1000 t
- Oceania 3 1000 t
- Middle Africa 3 1000 t
- Southern Africa 1 1000 t
- Southern Europe 1 1000 t
- Small island developing States (SIDS) 0 1000 t
- Eastern Europe -1 1000 t
- Northern Africa -1 1000 t
- Western Africa -4 1000 t
- Central Asia -5 1000 t
- South-Eastern Asia -18 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.