Rape and Mustardseed — 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
Rape and Mustardseed — Stock Variation is currently reported for 156 countries. The highest value is 1,625 1000 t in Australia; the lowest is -833 1000 t in Russian Federation.
The median across all reporting countries is 0 1000 t, and the mean is 16.53 1000 t.
The gap between the highest and lowest reporting country is a factor of about 2.
Over the past decade 26 countries rose and 18 fell. The largest increase was in India (up 2,044.4%), and the largest decrease in China (down 1,136.8%).
Rape and Mustardseed — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Australia | 1,625 1000 t | 2023 | up 394.9% | volatile |
| 1 | Australia and New Zealand | 1,625 1000 t | 2023 | up 394.4% | volatile |
| 3 | India | 700 1000 t | 2023 | up 2,044.4% | volatile |
| 4 | Germany | 478 1000 t | 2023 | down 74.1% | volatile |
| 5 | Canada | 257 1000 t | 2023 | down 93.7% | volatile |
| 6 | Czechia | 187 1000 t | 2023 | — | volatile |
| 7 | Bangladesh | 100 1000 t | 2023 | up 143.9% | volatile |
| 8 | Ukraine | 82 1000 t | 2023 | up 151.2% | volatile |
| 9 | Pakistan | 44 1000 t | 2023 | up 188.0% | volatile |
| 10 | Austria | 21 1000 t | 2023 | — | volatile |
| 11 | Hungary | 15 1000 t | 2023 | down 87.5% | volatile |
| 12 | Mexico | 7 1000 t | 2023 | up 105.1% | volatile |
| 13 | Lithuania | 6 1000 t | 2023 | up 112.0% | volatile |
| 14 | Brazil | 3 1000 t | 2023 | up 200.0% | volatile |
| 14 | Italy | 3 1000 t | 2023 | up 175.0% | volatile |
| 16 | Luxembourg | 1 1000 t | 2023 | — | volatile |
| 17 | Albania | 0 1000 t | 2023 | — | flat |
| 17 | Argentina | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Armenia | 0 1000 t | 2023 | — | flat |
| 17 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 17 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 17 | Belgium | 0 1000 t | 2023 | up 100.0% | flat |
| 17 | Burkina Faso | 0 1000 t | 2020 | — | flat |
| 17 | Bahrain | 0 1000 t | 2023 | — | flat |
| 17 | Bahamas | 0 1000 t | 2023 | — | flat |
| 17 | Bosnia and Herzegovina | 0 1000 t | 2023 | down 100.0% | flat |
| 17 | Belarus | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Belize | 0 1000 t | 2023 | — | flat |
| 17 | Barbados | 0 1000 t | 2023 | — | flat |
| 17 | Bhutan | 0 1000 t | 2023 | — | flat |
| 17 | Botswana | 0 1000 t | 2023 | — | flat |
| 17 | Cameroon | 0 1000 t | 2023 | — | flat |
| 17 | Colombia | 0 1000 t | 2023 | — | flat |
| 17 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 17 | Cuba | 0 1000 t | 2019 | — | flat |
| 17 | Cyprus | 0 1000 t | 2023 | — | flat |
| 17 | Algeria | 0 1000 t | 2023 | — | volatile |
| 17 | Ecuador | 0 1000 t | 2023 | — | flat |
| 17 | Egypt | 0 1000 t | 2023 | — | flat |
| 17 | Fiji | 0 1000 t | 2023 | — | flat |
| 17 | France | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Gabon | 0 1000 t | 2023 | — | flat |
| 17 | Georgia | 0 1000 t | 2023 | — | flat |
| 17 | Ghana | 0 1000 t | 2023 | — | flat |
| 17 | Gambia | 0 1000 t | 2023 | — | flat |
| 17 | Grenada | 0 1000 t | 2023 | — | flat |
| 17 | Guatemala | 0 1000 t | 2023 | — | flat |
| 17 | Guyana | 0 1000 t | 2023 | — | flat |
| 17 | Honduras | 0 1000 t | 2023 | — | flat |
| 17 | Indonesia | 0 1000 t | 2023 | — | flat |
| 17 | Iceland | 0 1000 t | 2023 | — | flat |
| 17 | Israel | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Jamaica | 0 1000 t | 2023 | — | flat |
| 17 | Jordan | 0 1000 t | 2023 | — | flat |
| 17 | Kenya | 0 1000 t | 2023 | — | flat |
| 17 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 17 | Cambodia | 0 1000 t | 2023 | — | flat |
| 17 | Kuwait | 0 1000 t | 2023 | — | flat |
| 17 | Lebanon | 0 1000 t | 2023 | — | flat |
| 17 | Libya | 0 1000 t | 2023 | — | flat |
| 17 | Saint Lucia | 0 1000 t | 2021 | — | flat |
| 17 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 17 | Morocco | 0 1000 t | 2023 | — | volatile |
| 17 | Madagascar | 0 1000 t | 2023 | — | flat |
| 17 | Maldives | 0 1000 t | 2023 | — | flat |
| 17 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 17 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 17 | Malta | 0 1000 t | 2023 | — | flat |
| 17 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 17 | Montenegro | 0 1000 t | 2019 | — | flat |
| 17 | Mozambique | 0 1000 t | 2023 | — | flat |
| 17 | Mauritania | 0 1000 t | 2018 | — | flat |
| 17 | Mauritius | 0 1000 t | 2023 | — | flat |
| 17 | Malawi | 0 1000 t | 2023 | — | flat |
| 17 | Namibia | 0 1000 t | 2023 | — | flat |
| 17 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 17 | Niger | 0 1000 t | 2019 | — | flat |
| 17 | Nigeria | 0 1000 t | 2023 | — | flat |
| 17 | Nicaragua | 0 1000 t | 2021 | — | flat |
| 17 | Norway | 0 1000 t | 2023 | — | flat |
| 17 | Nauru | 0 1000 t | 2023 | — | flat |
| 17 | New Zealand | 0 1000 t | 2023 | — | flat |
| 17 | Oman | 0 1000 t | 2023 | — | flat |
| 17 | Panama | 0 1000 t | 2023 | — | flat |
| 17 | Peru | 0 1000 t | 2023 | — | flat |
| 17 | Philippines | 0 1000 t | 2023 | — | flat |
| 17 | Paraguay | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 17 | Qatar | 0 1000 t | 2023 | — | flat |
| 17 | Saudi Arabia | 0 1000 t | 2023 | — | flat |
| 17 | Senegal | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 17 | El Salvador | 0 1000 t | 2023 | — | flat |
| 17 | Serbia | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Suriname | 0 1000 t | 2023 | — | flat |
| 17 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 17 | Eswatini | 0 1000 t | 2023 | — | flat |
| 17 | Seychelles | 0 1000 t | 2023 | — | flat |
| 17 | Thailand | 0 1000 t | 2023 | up 100.0% | flat |
| 17 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 17 | Tonga | 0 1000 t | 2023 | — | flat |
| 17 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 17 | Tunisia | 0 1000 t | 2023 | — | flat |
| 17 | Uganda | 0 1000 t | 2023 | — | flat |
| 17 | Uruguay | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Uzbekistan | 0 1000 t | 2023 | — | flat |
| 17 | Samoa | 0 1000 t | 2023 | — | flat |
| 17 | Yemen | 0 1000 t | 2023 | — | flat |
| 17 | Zambia | 0 1000 t | 2023 | — | flat |
| 17 | Zimbabwe | 0 1000 t | 2023 | — | flat |
| 17 | Micronesia | 0 1000 t | 2023 | — | flat |
| 17 | Cabo Verde | 0 1000 t | 2021 | — | flat |
| 17 | Melanesia | 0 1000 t | 2023 | — | flat |
| 17 | Polynesia | 0 1000 t | 2023 | — | flat |
| 17 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 17 | Caribbean | 0 1000 t | 2023 | — | flat |
| 17 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 17 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 17 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | flat |
| 17 | Republic of Korea | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Syrian Arab Republic | 0 1000 t | 2023 | — | flat |
| 17 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 17 | Viet Nam | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 17 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 17 | China, Taiwan Province of | 0 1000 t | 2023 | — | flat |
| 17 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
| 128 | Croatia | -1 1000 t | 2023 | down 116.7% | volatile |
| 128 | Ireland | -1 1000 t | 2023 | — | volatile |
| 128 | Türkiye | -1 1000 t | 2023 | up 98.7% | volatile |
| 131 | Switzerland | -2 1000 t | 2023 | — | volatile |
| 131 | Chile | -2 1000 t | 2023 | up 75.0% | volatile |
| 131 | Ethiopia | -2 1000 t | 2023 | — | volatile |
| 131 | Malaysia | -2 1000 t | 2023 | down 300.0% | volatile |
| 135 | Estonia | -4 1000 t | 2023 | — | volatile |
| 135 | Portugal | -4 1000 t | 2023 | — | volatile |
| 137 | United Kingdom of Great Britain and Northern Ireland | -5 1000 t | 2023 | — | volatile |
| 138 | Latvia | -6 1000 t | 2023 | down 154.5% | volatile |
| 139 | Finland | -8 1000 t | 2023 | up 42.9% | volatile |
| 140 | United Arab Emirates | -15 1000 t | 2023 | up 82.6% | volatile |
| 140 | Mongolia | -15 1000 t | 2023 | — | volatile |
| 142 | Republic of Moldova | -16 1000 t | 2023 | down 128.6% | volatile |
| 143 | Nepal | -22 1000 t | 2023 | — | volatile |
| 144 | Slovakia | -27 1000 t | 2023 | up 81.5% | volatile |
| 145 | Spain | -32 1000 t | 2023 | down 228.0% | volatile |
| 146 | Greece | -38 1000 t | 2023 | down 850.0% | volatile |
| 147 | Bulgaria | -40 1000 t | 2023 | up 40.3% | volatile |
| 148 | Netherlands (Kingdom of the) | -51 1000 t | 2023 | up 82.7% | volatile |
| 149 | Sweden | -52 1000 t | 2023 | — | volatile |
| 150 | Denmark | -60 1000 t | 2023 | — | volatile |
| 151 | Kazakhstan | -111 1000 t | 2023 | down 458.1% | volatile |
| 152 | Romania | -125 1000 t | 2023 | up 3.1% | volatile |
| 153 | China | -197 1000 t | 2023 | down 1,136.8% | volatile |
| 153 | China, mainland | -197 1000 t | 2023 | down 1,136.8% | volatile |
| 155 | Poland | -707 1000 t | 2023 | down 104.3% | volatile |
| 156 | Russian Federation | -833 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.
- Oceania 1,625 1000 t
- World 1,120 1000 t
- Southern Asia 822 1000 t
- Asia 497 1000 t
- Western Europe 447 1000 t
- Americas 208 1000 t
- Northern America 199 1000 t
- Net Food Importing Developing Countries (NFIDCs) 105 1000 t
- Least Developed Countries (LDCs) 76 1000 t
- South Africa 9 1000 t
- Southern Africa 9 1000 t
- Africa 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.