Tea (including mate) — 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
Tea (including mate) — Stock Variation is currently reported for 104 countries. The highest value is 86 1000 t in China, mainland; the lowest is -391 1000 t in Türkiye.
The median across all reporting countries is 0 1000 t, and the mean is -6.04 1000 t.
Over the past decade 26 countries rose and 26 fell. The largest increase was in Laos (up 300.0%), and the largest decrease in Turkey (down 2,200.0%).
Tea (including mate) — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China, mainland | 86 1000 t | 2023 | up 213.2% | volatile |
| 2 | China | 78 1000 t | 2023 | up 206.8% | volatile |
| 3 | Kenya | 29 1000 t | 2023 | up 131.5% | volatile |
| 4 | Thailand | 26 1000 t | 2023 | — | volatile |
| 5 | Laos | 4 1000 t | 2023 | up 300.0% | volatile |
| 5 | Lao People's Democratic Republic | 4 1000 t | 2023 | up 300.0% | volatile |
| 7 | Philippines | 2 1000 t | 2023 | up 300.0% | volatile |
| 7 | Uzbekistan | 2 1000 t | 2023 | up 100.0% | volatile |
| 7 | Zimbabwe | 2 1000 t | 2023 | up 133.3% | volatile |
| 10 | Italy | 1 1000 t | 2023 | — | volatile |
| 10 | Mauritania | 1 1000 t | 2023 | unchanged | volatile |
| 10 | Nepal | 1 1000 t | 2023 | — | flat |
| 10 | Syria | 1 1000 t | 2023 | down 87.5% | volatile |
| 10 | Syrian Arab Republic | 1 1000 t | 2023 | down 87.5% | volatile |
| 15 | Afghanistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Angola | 0 1000 t | 2023 | — | volatile |
| 15 | Argentina | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Australia | 0 1000 t | 2023 | — | volatile |
| 15 | Austria | 0 1000 t | 2023 | — | volatile |
| 15 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 15 | Belgium | 0 1000 t | 2023 | — | volatile |
| 15 | Burkina Faso | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Bangladesh | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 15 | Bahrain | 0 1000 t | 2023 | — | volatile |
| 15 | Brazil | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Canada | 0 1000 t | 2023 | — | volatile |
| 15 | Chile | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Cote d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 15 | Cameroon | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 15 | Czechia | 0 1000 t | 2023 | — | volatile |
| 15 | Germany | 0 1000 t | 2023 | — | volatile |
| 15 | Denmark | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Algeria | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Egypt | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Spain | 0 1000 t | 2023 | — | volatile |
| 15 | United Kingdom | 0 1000 t | 2023 | — | volatile |
| 15 | Georgia | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Ghana | 0 1000 t | 2023 | — | volatile |
| 15 | Guinea | 0 1000 t | 2023 | — | flat |
| 15 | Gambia | 0 1000 t | 2023 | — | volatile |
| 15 | Greece | 0 1000 t | 2023 | — | volatile |
| 15 | Hungary | 0 1000 t | 2023 | — | volatile |
| 15 | Indonesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | India | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Ireland | 0 1000 t | 2023 | — | volatile |
| 15 | Iraq | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Jordan | 0 1000 t | 2023 | — | flat |
| 15 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | flat |
| 15 | Kuwait | 0 1000 t | 2023 | — | volatile |
| 15 | Lebanon | 0 1000 t | 2023 | down 100.0% | flat |
| 15 | Libya | 0 1000 t | 2023 | — | volatile |
| 15 | Sri Lanka | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Morocco | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Mexico | 0 1000 t | 2023 | — | volatile |
| 15 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 15 | Mongolia | 0 1000 t | 2023 | down 100.0% | flat |
| 15 | Mozambique | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Malawi | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Namibia | 0 1000 t | 2023 | — | volatile |
| 15 | Niger | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 15 | New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Oman | 0 1000 t | 2023 | — | flat |
| 15 | Peru | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Papua New Guinea | 0 1000 t | 2023 | — | volatile |
| 15 | Poland | 0 1000 t | 2023 | up 100.0% | flat |
| 15 | Portugal | 0 1000 t | 2023 | — | volatile |
| 15 | Paraguay | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Russia | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Rwanda | 0 1000 t | 2023 | — | volatile |
| 15 | Saudi Arabia | 0 1000 t | 2023 | — | flat |
| 15 | Eswatini | 0 1000 t | 2023 | — | volatile |
| 15 | Tajikistan | 0 1000 t | 2023 | — | volatile |
| 15 | Turkmenistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Tunisia | 0 1000 t | 2023 | — | flat |
| 15 | Ukraine | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Uruguay | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Vietnam | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Yemen | 0 1000 t | 2023 | — | volatile |
| 15 | Melanesia | 0 1000 t | 2023 | — | volatile |
| 15 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 15 | Iran (Islamic Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Russian Federation | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Viet Nam | 0 1000 t | 2023 | up 100.0% | volatile |
| 15 | Australia and New Zealand | 0 1000 t | 2023 | — | volatile |
| 15 | Côte d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 15 | China, Taiwan Province of | 0 1000 t | 2023 | down 100.0% | volatile |
| 15 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | volatile |
| 15 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | volatile |
| 181 | Ethiopia | -1 1000 t | 2023 | down 200.0% | volatile |
| 181 | South Africa | -1 1000 t | 2023 | up 50.0% | volatile |
| 181 | Republic of Korea | -1 1000 t | 2023 | unchanged | volatile |
| 184 | Kyrgyzstan | -2 1000 t | 2023 | — | flat |
| 184 | Pakistan | -2 1000 t | 2023 | up 60.0% | volatile |
| 184 | Senegal | -2 1000 t | 2023 | — | flat |
| 187 | Belarus | -4 1000 t | 2023 | — | volatile |
| 188 | China, Hong Kong SAR | -8 1000 t | 2023 | — | volatile |
| 189 | United Republic of Tanzania | -9 1000 t | 2023 | down 1,000.0% | volatile |
| 190 | United States | -23 1000 t | 2023 | — | volatile |
| 191 | United Arab Emirates | -31 1000 t | 2023 | down 542.9% | volatile |
| 192 | Turkey | -391 1000 t | 2023 | down 2,200.0% | volatile |
| 192 | Türkiye | -391 1000 t | 2023 | down 2,200.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Eastern Asia 78 1000 t
- South-Eastern Asia 32 1000 t
- Low Income Food Deficit Countries (LIFDCs) 23 1000 t
- Net Food Importing Developing Countries (NFIDCs) 23 1000 t
- Eastern Africa 22 1000 t
- Africa 21 1000 t
- Land Locked Developing Countries (LLDCs) 6 1000 t
- Middle Africa 2 1000 t
- European Union (27) 1 1000 t
- Northern Europe 1 1000 t
- Southern Europe 1 1000 t
- Oceania 0 1000 t
- South America 0 1000 t
- Small island developing States (SIDS) 0 1000 t
- Western Europe 0 1000 t
- Northern Africa 0 1000 t
- Central America 0 1000 t
- Southern Asia 0 1000 t
- Central Asia -1 1000 t
- Southern Africa -1 1000 t
- Europe -2 1000 t
- Western Africa -2 1000 t
- Least Developed Countries (LDCs) -4 1000 t
- Eastern Europe -4 1000 t
- Northern America -23 1000 t
- United States of America -23 1000 t
- Americas -24 1000 t
- Asia -311 1000 t
- World -316 1000 t
- Western Asia -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.