Pepper — Domestic supply quantity 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
Pepper — Domestic supply quantity is currently reported for 181 countries. The highest value is 103 1000 t in Viet Nam; the lowest is -2 1000 t in Zambia.
The median across all reporting countries is 0 1000 t, and the mean is 4.09 1000 t.
The gap between the highest and lowest reporting country is a factor of about 52.
Over the past decade 29 countries rose and 19 fell. The largest increase was in Zimbabwe (up 2,000.0%), and the largest decrease in United Arab Emirates (down 100.0%).
Pepper — Domestic supply quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Viet Nam | 103 1000 t | 2023 | up 1,387.5% | volatile |
| 2 | India | 82 1000 t | 2023 | up 182.8% | rising |
| 3 | Burkina Faso | 71 1000 t | 2023 | — | volatile |
| 4 | China | 43 1000 t | 2023 | up 16.2% | rising |
| 5 | Indonesia | 41 1000 t | 2023 | unchanged | falling |
| 6 | China, mainland | 39 1000 t | 2023 | up 14.7% | rising |
| 7 | Iraq | 38 1000 t | 2023 | — | volatile |
| 8 | Sri Lanka | 31 1000 t | 2023 | up 106.7% | rising |
| 9 | Malaysia | 30 1000 t | 2023 | up 66.7% | rising |
| 10 | Brazil | 28 1000 t | 2023 | up 133.3% | rising |
| 11 | Tajikistan | 23 1000 t | 2023 | — | volatile |
| 12 | Zimbabwe | 21 1000 t | 2023 | up 2,000.0% | volatile |
| 13 | Mexico | 14 1000 t | 2023 | — | volatile |
| 14 | Pakistan | 12 1000 t | 2023 | up 100.0% | rising |
| 15 | United Kingdom of Great Britain and Northern Ireland | 10 1000 t | 2023 | down 16.7% | rising |
| 16 | Germany | 8 1000 t | 2023 | down 52.9% | falling |
| 16 | Morocco | 8 1000 t | 2023 | — | volatile |
| 18 | Canada | 7 1000 t | 2023 | up 40.0% | rising |
| 18 | Egypt | 7 1000 t | 2023 | unchanged | rising |
| 18 | Philippines | 7 1000 t | 2023 | up 40.0% | rising |
| 18 | Türkiye | 7 1000 t | 2023 | up 133.3% | rising |
| 22 | France | 6 1000 t | 2023 | unchanged | rising |
| 22 | Jordan | 6 1000 t | 2023 | up 700.0% | volatile |
| 22 | Saudi Arabia | 6 1000 t | 2023 | up 20.0% | falling |
| 25 | Ghana | 5 1000 t | 2023 | up 66.7% | rising |
| 25 | Poland | 5 1000 t | 2023 | up 25.0% | rising |
| 25 | Thailand | 5 1000 t | 2023 | up 25.0% | rising |
| 28 | Ethiopia | 4 1000 t | 2023 | — | volatile |
| 28 | Niger | 4 1000 t | 2023 | up 300.0% | volatile |
| 28 | Australia and New Zealand | 4 1000 t | 2023 | up 33.3% | rising |
| 31 | Australia | 3 1000 t | 2023 | unchanged | flat |
| 31 | Italy | 3 1000 t | 2023 | up 50.0% | rising |
| 31 | Rwanda | 3 1000 t | 2023 | up 50.0% | falling |
| 31 | Yemen | 3 1000 t | 2023 | up 200.0% | volatile |
| 31 | China, Taiwan Province of | 3 1000 t | 2023 | unchanged | rising |
| 36 | Argentina | 2 1000 t | 2023 | up 100.0% | rising |
| 36 | Austria | 2 1000 t | 2023 | up 100.0% | rising |
| 36 | Costa Rica | 2 1000 t | 2023 | up 100.0% | rising |
| 36 | Ecuador | 2 1000 t | 2023 | unchanged | volatile |
| 36 | Spain | 2 1000 t | 2023 | unchanged | falling |
| 36 | Kazakhstan | 2 1000 t | 2023 | up 100.0% | rising |
| 36 | Peru | 2 1000 t | 2023 | up 100.0% | rising |
| 36 | Uganda | 2 1000 t | 2023 | unchanged | rising |
| 36 | Ukraine | 2 1000 t | 2023 | down 33.3% | falling |
| 36 | Caribbean | 2 1000 t | 2023 | up 100.0% | rising |
| 36 | Iran (Islamic Republic of) | 2 1000 t | 2023 | up 100.0% | falling |
| 47 | Belgium | 1 1000 t | 2023 | down 50.0% | falling |
| 47 | Bangladesh | 1 1000 t | 2023 | — | volatile |
| 47 | Switzerland | 1 1000 t | 2023 | unchanged | flat |
| 47 | Czechia | 1 1000 t | 2023 | unchanged | flat |
| 47 | Denmark | 1 1000 t | 2023 | unchanged | flat |
| 47 | Dominican Republic | 1 1000 t | 2023 | — | volatile |
| 47 | Algeria | 1 1000 t | 2023 | down 66.7% | falling |
| 47 | Finland | 1 1000 t | 2023 | — | volatile |
| 47 | Greece | 1 1000 t | 2023 | unchanged | flat |
| 47 | Hungary | 1 1000 t | 2023 | unchanged | flat |
| 47 | Ireland | 1 1000 t | 2023 | unchanged | flat |
| 47 | Israel | 1 1000 t | 2023 | unchanged | volatile |
| 47 | Cambodia | 1 1000 t | 2023 | down 50.0% | volatile |
| 47 | Kuwait | 1 1000 t | 2023 | unchanged | flat |
| 47 | Lebanon | 1 1000 t | 2023 | — | volatile |
| 47 | Libya | 1 1000 t | 2023 | — | volatile |
| 47 | Mauritania | 1 1000 t | 2023 | — | volatile |
| 47 | Norway | 1 1000 t | 2023 | — | volatile |
| 47 | New Zealand | 1 1000 t | 2023 | unchanged | flat |
| 47 | Oman | 1 1000 t | 2023 | unchanged | flat |
| 47 | Portugal | 1 1000 t | 2023 | — | volatile |
| 47 | Qatar | 1 1000 t | 2023 | — | flat |
| 47 | Romania | 1 1000 t | 2023 | down 50.0% | falling |
| 47 | Senegal | 1 1000 t | 2023 | unchanged | rising |
| 47 | Sweden | 1 1000 t | 2023 | unchanged | rising |
| 47 | Uzbekistan | 1 1000 t | 2023 | — | volatile |
| 47 | China, Hong Kong SAR | 1 1000 t | 2023 | — | volatile |
| 47 | Republic of Korea | 1 1000 t | 2023 | down 75.0% | rising |
| 47 | Russian Federation | 1 1000 t | 2023 | down 88.9% | falling |
| 47 | Venezuela (Bolivarian Republic of) | 1 1000 t | 2023 | — | volatile |
| 47 | Côte d'Ivoire | 1 1000 t | 2023 | — | volatile |
| 47 | Netherlands (Kingdom of the) | 1 1000 t | 2023 | down 80.0% | falling |
| 79 | Afghanistan | 0 1000 t | 2023 | — | flat |
| 79 | Angola | 0 1000 t | 2023 | — | flat |
| 79 | Albania | 0 1000 t | 2023 | — | flat |
| 79 | United Arab Emirates | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Armenia | 0 1000 t | 2023 | — | flat |
| 79 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 79 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 79 | Bulgaria | 0 1000 t | 2023 | — | flat |
| 79 | Bahrain | 0 1000 t | 2023 | — | flat |
| 79 | Bahamas | 0 1000 t | 2023 | — | flat |
| 79 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 79 | Belarus | 0 1000 t | 2023 | — | flat |
| 79 | Belize | 0 1000 t | 2023 | — | flat |
| 79 | Barbados | 0 1000 t | 2023 | — | flat |
| 79 | Bhutan | 0 1000 t | 2023 | — | flat |
| 79 | Botswana | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Chile | 0 1000 t | 2023 | — | volatile |
| 79 | Cameroon | 0 1000 t | 2023 | — | flat |
| 79 | Congo | 0 1000 t | 2023 | — | flat |
| 79 | Colombia | 0 1000 t | 2023 | — | volatile |
| 79 | Comoros | 0 1000 t | 2023 | — | flat |
| 79 | Cuba | 0 1000 t | 2019 | — | flat |
| 79 | Cyprus | 0 1000 t | 2023 | — | flat |
| 79 | Djibouti | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Estonia | 0 1000 t | 2023 | — | flat |
| 79 | Fiji | 0 1000 t | 2023 | — | flat |
| 79 | Gabon | 0 1000 t | 2023 | — | flat |
| 79 | Georgia | 0 1000 t | 2023 | — | flat |
| 79 | Guinea | 0 1000 t | 2023 | — | flat |
| 79 | Gambia | 0 1000 t | 2023 | — | volatile |
| 79 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 79 | Grenada | 0 1000 t | 2023 | — | flat |
| 79 | Guatemala | 0 1000 t | 2023 | — | flat |
| 79 | Guyana | 0 1000 t | 2023 | — | flat |
| 79 | Honduras | 0 1000 t | 2023 | — | flat |
| 79 | Croatia | 0 1000 t | 2023 | — | volatile |
| 79 | Haiti | 0 1000 t | 2023 | — | flat |
| 79 | Iceland | 0 1000 t | 2023 | — | flat |
| 79 | Jamaica | 0 1000 t | 2023 | — | flat |
| 79 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 79 | Kiribati | 0 1000 t | 2023 | — | flat |
| 79 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 79 | Liberia | 0 1000 t | 2023 | — | flat |
| 79 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 79 | Lesotho | 0 1000 t | 2023 | — | volatile |
| 79 | Lithuania | 0 1000 t | 2023 | — | flat |
| 79 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 79 | Latvia | 0 1000 t | 2023 | — | flat |
| 79 | Madagascar | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Maldives | 0 1000 t | 2023 | — | flat |
| 79 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 79 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 79 | Malta | 0 1000 t | 2023 | — | flat |
| 79 | Myanmar | 0 1000 t | 2023 | — | flat |
| 79 | Montenegro | 0 1000 t | 2023 | — | flat |
| 79 | Mongolia | 0 1000 t | 2023 | — | flat |
| 79 | Mozambique | 0 1000 t | 2023 | — | volatile |
| 79 | Mauritius | 0 1000 t | 2023 | — | flat |
| 79 | Malawi | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Namibia | 0 1000 t | 2023 | — | volatile |
| 79 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 79 | Nigeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Nicaragua | 0 1000 t | 2023 | — | flat |
| 79 | Nepal | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Nauru | 0 1000 t | 2023 | — | flat |
| 79 | Panama | 0 1000 t | 2023 | — | flat |
| 79 | Papua New Guinea | 0 1000 t | 2023 | — | volatile |
| 79 | Paraguay | 0 1000 t | 2023 | — | flat |
| 79 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 79 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 79 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 79 | El Salvador | 0 1000 t | 2023 | — | flat |
| 79 | Serbia | 0 1000 t | 2023 | — | flat |
| 79 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 79 | Suriname | 0 1000 t | 2023 | — | flat |
| 79 | Slovakia | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Slovenia | 0 1000 t | 2023 | — | flat |
| 79 | Eswatini | 0 1000 t | 2023 | — | flat |
| 79 | Seychelles | 0 1000 t | 2023 | — | flat |
| 79 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 79 | Tonga | 0 1000 t | 2023 | — | flat |
| 79 | Trinidad and Tobago | 0 1000 t | 2023 | — | volatile |
| 79 | Tunisia | 0 1000 t | 2023 | down 100.0% | falling |
| 79 | Uruguay | 0 1000 t | 2023 | — | flat |
| 79 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 79 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 79 | Samoa | 0 1000 t | 2023 | — | flat |
| 79 | Micronesia | 0 1000 t | 2023 | — | flat |
| 79 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 79 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 79 | Melanesia | 0 1000 t | 2023 | — | volatile |
| 79 | Polynesia | 0 1000 t | 2023 | — | flat |
| 79 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 79 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 79 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 79 | Syrian Arab Republic | 0 1000 t | 2023 | — | volatile |
| 79 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 79 | United Republic of Tanzania | 0 1000 t | 2023 | — | volatile |
| 79 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | flat |
| 79 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
| 79 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
| 180 | Kenya | -1 1000 t | 2023 | — | volatile |
| 181 | Zambia | -2 1000 t | 2023 | — | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 774 1000 t
- Asia 463 1000 t
- South-eastern Asia 188 1000 t
- Net Food Importing Developing Countries (NFIDCs) 163 1000 t
- Low Income Food Deficit Countries (LIFDCs) 139 1000 t
- Africa 134 1000 t
- Land Locked Developing Countries (LLDCs) 133 1000 t
- Southern Asia 130 1000 t
- Americas 120 1000 t
- Least Developed Countries (LDCs) 94 1000 t
- Western Africa 84 1000 t
- Northern America 65 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.