Sweet potatoes — 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
Sweet potatoes — Stock Variation is currently reported for 100 countries. The highest value is 2,029 1000 t in China; the lowest is -317 1000 t in Malawi.
The median across all reporting countries is 0 1000 t, and the mean is 42.47 1000 t.
The gap between the highest and lowest reporting country is a factor of about 6.
Over the past decade 32 countries rose and 31 fell. The largest increase was in Democratic People's Republic of Korea (up 2,980.0%), and the largest decrease in Egypt (down 350.0%).
Sweet potatoes — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 2,029 1000 t | 2023 | up 46.4% | volatile |
| 2 | China, mainland | 2,025 1000 t | 2023 | up 45.7% | volatile |
| 3 | Democratic People's Republic of Korea | 154 1000 t | 2018 | up 2,980.0% | volatile |
| 4 | India | 125 1000 t | 2023 | up 531.0% | volatile |
| 5 | Zambia | 91 1000 t | 2023 | up 139.5% | volatile |
| 6 | Cameroon | 44 1000 t | 2023 | up 158.8% | volatile |
| 7 | Guinea | 42 1000 t | 2023 | up 200.0% | rising |
| 8 | Kenya | 37 1000 t | 2023 | up 121.5% | volatile |
| 9 | Niger | 30 1000 t | 2023 | up 200.0% | volatile |
| 10 | Brazil | 22 1000 t | 2023 | up 833.3% | volatile |
| 11 | Zimbabwe | 20 1000 t | 2023 | — | volatile |
| 12 | Sierra Leone | 17 1000 t | 2023 | up 142.9% | volatile |
| 13 | Haiti | 12 1000 t | 2023 | down 80.0% | volatile |
| 14 | Dominican Republic | 10 1000 t | 2023 | up 100.0% | volatile |
| 15 | Laos | 7 1000 t | 2023 | up 216.7% | volatile |
| 15 | Lao People's Democratic Republic | 7 1000 t | 2023 | up 216.7% | volatile |
| 17 | Saudi Arabia | 4 1000 t | 2023 | up 300.0% | rising |
| 18 | Guatemala | 3 1000 t | 2023 | — | volatile |
| 18 | Cambodia | 3 1000 t | 2023 | up 200.0% | rising |
| 18 | China, Taiwan Province of | 3 1000 t | 2023 | up 175.0% | volatile |
| 18 | Netherlands (Kingdom of the) | 3 1000 t | 2023 | — | volatile |
| 22 | United Arab Emirates | 2 1000 t | 2023 | up 300.0% | volatile |
| 22 | Indonesia | 2 1000 t | 2023 | down 98.9% | volatile |
| 22 | Pakistan | 2 1000 t | 2023 | up 100.0% | rising |
| 22 | Thailand | 2 1000 t | 2023 | unchanged | volatile |
| 26 | Australia | 1 1000 t | 2023 | — | volatile |
| 26 | Caribbean | 1 1000 t | 2023 | down 98.4% | volatile |
| 28 | Albania | 0 1000 t | 2023 | — | flat |
| 28 | Argentina | 0 1000 t | 2023 | up 100.0% | volatile |
| 28 | Austria | 0 1000 t | 2023 | — | volatile |
| 28 | Burkina Faso | 0 1000 t | 2023 | down 100.0% | flat |
| 28 | Bangladesh | 0 1000 t | 2023 | up 100.0% | flat |
| 28 | Bahamas | 0 1000 t | 2023 | — | volatile |
| 28 | Barbados | 0 1000 t | 2023 | — | volatile |
| 28 | Canada | 0 1000 t | 2023 | down 100.0% | flat |
| 28 | Switzerland | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 28 | Cote d'Ivoire | 0 1000 t | 2023 | up 100.0% | volatile |
| 28 | Comoros | 0 1000 t | 2023 | — | volatile |
| 28 | Cuba | 0 1000 t | 2019 | — | volatile |
| 28 | Czechia | 0 1000 t | 2023 | — | volatile |
| 28 | Denmark | 0 1000 t | 2023 | — | volatile |
| 28 | Spain | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Ethiopia | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Finland | 0 1000 t | 2023 | — | volatile |
| 28 | Fiji | 0 1000 t | 2023 | — | volatile |
| 28 | Ghana | 0 1000 t | 2023 | up 100.0% | volatile |
| 28 | Greece | 0 1000 t | 2023 | — | volatile |
| 28 | Guyana | 0 1000 t | 2023 | — | volatile |
| 28 | Honduras | 0 1000 t | 2023 | up 100.0% | volatile |
| 28 | Hungary | 0 1000 t | 2023 | — | volatile |
| 28 | Iceland | 0 1000 t | 2023 | — | volatile |
| 28 | Israel | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Italy | 0 1000 t | 2023 | up 100.0% | volatile |
| 28 | Jamaica | 0 1000 t | 2023 | up 100.0% | volatile |
| 28 | Kuwait | 0 1000 t | 2023 | — | volatile |
| 28 | Liberia | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 28 | Morocco | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Madagascar | 0 1000 t | 2023 | up 100.0% | volatile |
| 28 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Mozambique | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Malaysia | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Nigeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Norway | 0 1000 t | 2023 | — | volatile |
| 28 | Nepal | 0 1000 t | 2023 | — | volatile |
| 28 | New Zealand | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Papua New Guinea | 0 1000 t | 2023 | up 100.0% | volatile |
| 28 | Poland | 0 1000 t | 2023 | up 100.0% | volatile |
| 28 | Portugal | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Rwanda | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Senegal | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Serbia | 0 1000 t | 2023 | — | volatile |
| 28 | Suriname | 0 1000 t | 2023 | — | volatile |
| 28 | Sweden | 0 1000 t | 2023 | — | volatile |
| 28 | Tonga | 0 1000 t | 2023 | — | volatile |
| 28 | Uruguay | 0 1000 t | 2023 | up 100.0% | volatile |
| 28 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | volatile |
| 28 | South Africa | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Cabo Verde | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Polynesia | 0 1000 t | 2023 | — | volatile |
| 28 | Democratic Republic of the Congo | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 28 | Republic of Korea | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Australia and New Zealand | 0 1000 t | 2023 | down 100.0% | volatile |
| 28 | Côte d'Ivoire | 0 1000 t | 2023 | up 100.0% | volatile |
| 28 | United Republic of Tanzania | 0 1000 t | 2023 | down 100.0% | volatile |
| 169 | Ecuador | -1 1000 t | 2023 | — | volatile |
| 169 | Myanmar | -1 1000 t | 2023 | — | volatile |
| 169 | Philippines | -1 1000 t | 2023 | down 110.0% | volatile |
| 169 | Bolivia (Plurinational State of) | -1 1000 t | 2023 | — | volatile |
| 173 | Mauritania | -2 1000 t | 2023 | — | flat |
| 174 | Solomon Islands | -3 1000 t | 2023 | — | volatile |
| 174 | Melanesia | -3 1000 t | 2023 | down 50.0% | volatile |
| 176 | Vietnam | -8 1000 t | 2023 | down 157.1% | volatile |
| 176 | Viet Nam | -8 1000 t | 2023 | down 157.1% | volatile |
| 178 | Egypt | -25 1000 t | 2023 | down 350.0% | volatile |
| 179 | United States | -26 1000 t | 2023 | down 123.2% | volatile |
| 180 | Angola | -55 1000 t | 2023 | — | volatile |
| 181 | Malawi | -317 1000 t | 2023 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Asia 2,188 1000 t
- Eastern Asia 2,049 1000 t
- World 2,012 1000 t
- Southern Asia 128 1000 t
- Western Africa 26 1000 t
- South America 21 1000 t
- Western Asia 7 1000 t
- South-Eastern Asia 4 1000 t
- European Union (27) 3 1000 t
- Europe 3 1000 t
- Western Europe 3 1000 t
- Central America 3 1000 t
- Americas 0 1000 t
- Eastern Europe 0 1000 t
- Southern Africa 0 1000 t
- Northern Europe 0 1000 t
- Southern Europe 0 1000 t
- Small island developing States (SIDS) -1 1000 t
- Oceania -2 1000 t
- Middle Africa -11 1000 t
- Northern Africa -23 1000 t
- Northern America -26 1000 t
- United States of America -26 1000 t
- Low Income Food Deficit Countries (LIFDCs) -154 1000 t
- Eastern Africa -169 1000 t
- Africa -176 1000 t
- Net Food Importing Developing Countries (NFIDCs) -230 1000 t
- Least Developed Countries (LDCs) -234 1000 t
- Land Locked Developing Countries (LLDCs) -234 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.