Rape and Mustard Oil — 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 Mustard Oil — Stock Variation is currently reported for 87 countries. The highest value is 195 1000 t in Russia; the lowest is -74 1000 t in Poland.
The median across all reporting countries is 0 1000 t, and the mean is 6.41 1000 t.
The gap between the highest and lowest reporting country is a factor of about 3.
Over the past decade 24 countries rose and 17 fell. The largest increase was in United States (up 850.0%), and the largest decrease in Poland (down 2,366.7%).
Rape and Mustard Oil — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Russia | 195 1000 t | 2023 | up 400.0% | volatile |
| 1 | Russian Federation | 195 1000 t | 2023 | up 400.0% | volatile |
| 3 | China | 75 1000 t | 2023 | down 91.8% | volatile |
| 3 | China, mainland | 75 1000 t | 2023 | down 91.8% | volatile |
| 5 | Pakistan | 55 1000 t | 2023 | — | volatile |
| 6 | Canada | 45 1000 t | 2023 | — | volatile |
| 7 | United States | 30 1000 t | 2023 | up 850.0% | volatile |
| 8 | Czechia | 21 1000 t | 2023 | up 400.0% | volatile |
| 8 | India | 21 1000 t | 2023 | up 158.3% | volatile |
| 10 | United Arab Emirates | 12 1000 t | 2023 | up 136.4% | volatile |
| 11 | Ireland | 9 1000 t | 2023 | down 50.0% | volatile |
| 12 | Sweden | 8 1000 t | 2023 | — | volatile |
| 13 | Latvia | 7 1000 t | 2023 | — | volatile |
| 14 | Hungary | 6 1000 t | 2023 | up 154.5% | volatile |
| 15 | Spain | 5 1000 t | 2023 | — | volatile |
| 15 | Romania | 5 1000 t | 2023 | — | volatile |
| 17 | Israel | 4 1000 t | 2023 | — | volatile |
| 18 | Australia | 3 1000 t | 2023 | up 50.0% | volatile |
| 18 | Nepal | 3 1000 t | 2023 | — | volatile |
| 18 | Ukraine | 3 1000 t | 2023 | up 160.0% | volatile |
| 18 | Australia and New Zealand | 3 1000 t | 2023 | up 50.0% | volatile |
| 22 | Belgium | 2 1000 t | 2023 | — | volatile |
| 22 | Portugal | 2 1000 t | 2023 | — | flat |
| 22 | Republic of Korea | 2 1000 t | 2023 | up 114.3% | volatile |
| 25 | United Kingdom | 1 1000 t | 2023 | up 200.0% | volatile |
| 25 | Iceland | 1 1000 t | 2023 | — | volatile |
| 25 | Nigeria | 1 1000 t | 2023 | — | volatile |
| 25 | Vietnam | 1 1000 t | 2023 | — | volatile |
| 25 | Viet Nam | 1 1000 t | 2023 | — | volatile |
| 25 | United Kingdom of Great Britain and Northern Ireland | 1 1000 t | 2023 | up 200.0% | volatile |
| 31 | Austria | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | Bangladesh | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | Bulgaria | 0 1000 t | 2023 | up 100.0% | flat |
| 31 | Botswana | 0 1000 t | 2023 | — | volatile |
| 31 | Switzerland | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | Cote d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 31 | Colombia | 0 1000 t | 2023 | — | flat |
| 31 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 31 | Denmark | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Dominican Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Egypt | 0 1000 t | 2023 | — | volatile |
| 31 | Ethiopia | 0 1000 t | 2023 | down 100.0% | flat |
| 31 | Finland | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | Fiji | 0 1000 t | 2023 | down 100.0% | flat |
| 31 | Croatia | 0 1000 t | 2023 | — | volatile |
| 31 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Kenya | 0 1000 t | 2023 | — | volatile |
| 31 | Lebanon | 0 1000 t | 2023 | — | flat |
| 31 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 31 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 31 | Morocco | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Mongolia | 0 1000 t | 2023 | — | volatile |
| 31 | New Zealand | 0 1000 t | 2023 | — | volatile |
| 31 | Philippines | 0 1000 t | 2023 | up 100.0% | flat |
| 31 | Paraguay | 0 1000 t | 2023 | — | volatile |
| 31 | Qatar | 0 1000 t | 2023 | — | volatile |
| 31 | Saudi Arabia | 0 1000 t | 2023 | — | volatile |
| 31 | Serbia | 0 1000 t | 2023 | — | volatile |
| 31 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 31 | Turkey | 0 1000 t | 2023 | — | volatile |
| 31 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 31 | Uzbekistan | 0 1000 t | 2023 | — | volatile |
| 31 | Yemen | 0 1000 t | 2023 | — | volatile |
| 31 | Melanesia | 0 1000 t | 2023 | down 100.0% | flat |
| 31 | Caribbean | 0 1000 t | 2023 | — | volatile |
| 31 | China, Hong Kong SAR | 0 1000 t | 2023 | down 100.0% | flat |
| 31 | Iran (Islamic Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 31 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 31 | Türkiye | 0 1000 t | 2023 | — | volatile |
| 31 | Côte d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 31 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
| 168 | Bosnia and Herzegovina | -1 1000 t | 2023 | up 66.7% | volatile |
| 168 | Italy | -1 1000 t | 2023 | — | volatile |
| 168 | Panama | -1 1000 t | 2023 | — | flat |
| 168 | Slovakia | -1 1000 t | 2023 | up 95.7% | volatile |
| 172 | Argentina | -2 1000 t | 2023 | — | volatile |
| 173 | Estonia | -3 1000 t | 2023 | up 85.7% | volatile |
| 174 | Algeria | -4 1000 t | 2023 | — | volatile |
| 174 | Malaysia | -4 1000 t | 2023 | down 166.7% | volatile |
| 176 | Germany | -7 1000 t | 2023 | — | volatile |
| 176 | Norway | -7 1000 t | 2023 | up 30.0% | volatile |
| 178 | Mexico | -13 1000 t | 2023 | down 44.4% | volatile |
| 179 | France | -20 1000 t | 2023 | down 253.8% | volatile |
| 179 | Netherlands (Kingdom of the) | -20 1000 t | 2023 | — | volatile |
| 181 | Chile | -23 1000 t | 2023 | — | volatile |
| 182 | Belarus | -53 1000 t | 2023 | down 340.9% | volatile |
| 183 | Poland | -74 1000 t | 2023 | down 2,366.7% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 267 1000 t
- Asia 153 1000 t
- Eastern Europe 102 1000 t
- Southern Asia 79 1000 t
- Europe 77 1000 t
- Northern America 75 1000 t
- Eastern Asia 61 1000 t
- Net Food Importing Developing Countries (NFIDCs) 58 1000 t
- Americas 37 1000 t
- United States of America 30 1000 t
- Western Asia 16 1000 t
- Northern Europe 15 1000 t
- Southern Europe 5 1000 t
- Oceania 3 1000 t
- Land Locked Developing Countries (LLDCs) 3 1000 t
- Least Developed Countries (LDCs) 2 1000 t
- Low Income Food Deficit Countries (LIFDCs) 2 1000 t
- Small island developing States (SIDS) 1 1000 t
- Central Asia 0 1000 t
- Eastern Africa 0 1000 t
- Southern Africa 0 1000 t
- Western Africa 0 1000 t
- Africa -3 1000 t
- South-Eastern Asia -3 1000 t
- Northern Africa -4 1000 t
- Central America -14 1000 t
- South America -25 1000 t
- Western Europe -45 1000 t
- European Union (27) -61 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.