Sugar beet — 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
Sugar beet — Stock Variation is currently reported for 54 countries. The highest value is 3,784 1000 t in Russia; the lowest is -814 1000 t in Morocco.
The median across all reporting countries is 0 1000 t, and the mean is 414.39 1000 t.
The gap between the highest and lowest reporting country is a factor of about 5.
Over the past decade 36 countries rose and 9 fell. The largest increase was in Poland (up 2,166.7%), and the largest decrease in Netherlands (Kingdom of the) (down 442.2%).
Sugar beet — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Russia | 3,784 1000 t | 2023 | up 289.2% | volatile |
| 1 | Russian Federation | 3,784 1000 t | 2023 | up 289.2% | volatile |
| 3 | Turkey | 3,084 1000 t | 2023 | up 365.4% | volatile |
| 3 | Türkiye | 3,084 1000 t | 2023 | up 365.4% | volatile |
| 5 | Ukraine | 2,767 1000 t | 2023 | up 397.7% | volatile |
| 6 | Egypt | 1,725 1000 t | 2023 | up 372.5% | volatile |
| 7 | United Kingdom | 1,006 1000 t | 2023 | up 711.3% | volatile |
| 7 | United Kingdom of Great Britain and Northern Ireland | 1,006 1000 t | 2023 | up 711.3% | volatile |
| 9 | Iran (Islamic Republic of) | 904 1000 t | 2023 | up 29.1% | volatile |
| 10 | Poland | 558 1000 t | 2023 | up 2,166.7% | volatile |
| 11 | China | 405 1000 t | 2023 | up 111.5% | volatile |
| 11 | China, mainland | 405 1000 t | 2023 | up 111.5% | volatile |
| 13 | Spain | 331 1000 t | 2023 | up 165.7% | volatile |
| 14 | Switzerland | 261 1000 t | 2023 | up 736.6% | volatile |
| 15 | France | 249 1000 t | 2023 | up 109.4% | volatile |
| 16 | Belarus | 93 1000 t | 2023 | up 119.9% | volatile |
| 17 | Serbia | 85 1000 t | 2023 | down 64.0% | volatile |
| 18 | Kazakhstan | 73 1000 t | 2023 | up 262.2% | volatile |
| 19 | Belgium | 28 1000 t | 2023 | up 109.3% | volatile |
| 20 | Italy | 13 1000 t | 2023 | — | volatile |
| 21 | Luxembourg | 1 1000 t | 2023 | — | volatile |
| 21 | Pakistan | 1 1000 t | 2023 | — | volatile |
| 23 | Czechia | 0 1000 t | 2023 | down 100.0% | volatile |
| 23 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | volatile |
| 23 | Canada | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Colombia | 0 1000 t | 2023 | — | volatile |
| 23 | Armenia | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Albania | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Afghanistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 23 | Finland | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Croatia | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Hungary | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Kyrgyzstan | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Lithuania | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Greece | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 23 | Oman | 0 1000 t | 2023 | — | volatile |
| 23 | Germany | 0 1000 t | 2023 | down 100.0% | volatile |
| 23 | Portugal | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Romania | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Slovakia | 0 1000 t | 2023 | — | volatile |
| 23 | Sweden | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Tunisia | 0 1000 t | 2023 | down 100.0% | volatile |
| 23 | Denmark | 0 1000 t | 2023 | up 100.0% | volatile |
| 120 | Syria | -2 1000 t | 2023 | up 87.5% | volatile |
| 120 | Syrian Arab Republic | -2 1000 t | 2023 | up 87.5% | volatile |
| 120 | Chile | -2 1000 t | 2023 | unchanged | volatile |
| 123 | Turkmenistan | -8 1000 t | 2023 | down 116.7% | volatile |
| 124 | Austria | -17 1000 t | 2023 | up 90.9% | volatile |
| 125 | Republic of Moldova | -28 1000 t | 2023 | down 128.3% | volatile |
| 125 | Moldova | -28 1000 t | 2023 | down 128.3% | volatile |
| 127 | Netherlands (Kingdom of the) | -154 1000 t | 2023 | down 442.2% | volatile |
| 128 | United States | -215 1000 t | 2023 | up 81.1% | volatile |
| 129 | Morocco | -814 1000 t | 2023 | up 2.5% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 14,597 1000 t
- Europe 8,975 1000 t
- Eastern Europe 7,174 1000 t
- Asia 4,929 1000 t
- Western Asia 3,082 1000 t
- European Union (27) 1,008 1000 t
- Northern Europe 1,006 1000 t
- Northern Africa 911 1000 t
- Net Food Importing Developing Countries (NFIDCs) 911 1000 t
- Africa 910 1000 t
- Southern Asia 905 1000 t
- Eastern Asia 878 1000 t
- Southern Europe 429 1000 t
- Western Europe 366 1000 t
- Central Asia 64 1000 t
- Land Locked Developing Countries (LLDCs) 35 1000 t
- Western Africa -1 1000 t
- Least Developed Countries (LDCs) -1 1000 t
- South America -2 1000 t
- Low Income Food Deficit Countries (LIFDCs) -3 1000 t
- Northern America -215 1000 t
- United States of America -215 1000 t
- Americas -217 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.