Rape and Mustardseed — Losses 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 — Losses is currently reported for 69 countries. The highest value is 951 1000 t in India; the lowest is 0 1000 t in Uzbekistan.
The median across all reporting countries is 3 1000 t, and the mean is 70.61 1000 t.
Over the past decade 27 countries rose and 20 fell. The largest increase was in Russian Federation (up 9,900.0%), and the largest decrease in Croatia (down 100.0%).
Rape and Mustardseed — Losses: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 951 1000 t | 2023 | up 61.7% | rising |
| 2 | France | 695 1000 t | 2023 | up 5.1% | falling |
| 3 | China, mainland | 621 1000 t | 2023 | up 20.1% | rising |
| 3 | China | 621 1000 t | 2023 | up 20.1% | rising |
| 5 | Canada | 587 1000 t | 2023 | up 1.4% | falling |
| 6 | Germany | 257 1000 t | 2023 | up 164.9% | rising |
| 7 | Australia and New Zealand | 172 1000 t | 2023 | up 115.0% | rising |
| 8 | Australia | 171 1000 t | 2023 | up 113.8% | rising |
| 9 | United Kingdom of Great Britain and Northern Ireland | 139 1000 t | 2023 | down 24.9% | falling |
| 10 | Poland | 138 1000 t | 2023 | up 72.5% | rising |
| 11 | Russian Federation | 100 1000 t | 2023 | up 9,900.0% | volatile |
| 12 | Belgium | 91 1000 t | 2023 | up 122.0% | falling |
| 13 | Bangladesh | 53 1000 t | 2023 | up 140.9% | rising |
| 14 | Pakistan | 28 1000 t | 2023 | up 64.7% | rising |
| 15 | Czechia | 26 1000 t | 2023 | up 13.0% | rising |
| 16 | Uruguay | 24 1000 t | 2023 | up 1,100.0% | volatile |
| 17 | Slovakia | 23 1000 t | 2023 | down 17.9% | falling |
| 18 | Iran (Islamic Republic of) | 19 1000 t | 2023 | up 46.2% | rising |
| 19 | Lithuania | 16 1000 t | 2023 | down 48.4% | rising |
| 20 | Mexico | 12 1000 t | 2023 | down 14.3% | falling |
| 21 | Brazil | 11 1000 t | 2023 | up 266.7% | rising |
| 22 | Serbia | 10 1000 t | 2023 | up 400.0% | volatile |
| 23 | Spain | 9 1000 t | 2023 | up 800.0% | volatile |
| 23 | Belarus | 9 1000 t | 2023 | up 28.6% | rising |
| 23 | Hungary | 9 1000 t | 2023 | up 350.0% | volatile |
| 26 | Latvia | 7 1000 t | 2023 | up 133.3% | rising |
| 26 | Finland | 7 1000 t | 2023 | up 16.7% | falling |
| 28 | Bulgaria | 6 1000 t | 2023 | down 14.3% | falling |
| 29 | Türkiye | 5 1000 t | 2023 | unchanged | falling |
| 29 | Paraguay | 5 1000 t | 2023 | down 37.5% | falling |
| 29 | Chile | 5 1000 t | 2023 | down 58.3% | flat |
| 32 | Sweden | 4 1000 t | 2023 | down 20.0% | flat |
| 32 | Ukraine | 4 1000 t | 2023 | down 83.3% | volatile |
| 32 | Nepal | 4 1000 t | 2023 | up 33.3% | rising |
| 35 | Argentina | 3 1000 t | 2023 | down 72.7% | volatile |
| 35 | Estonia | 3 1000 t | 2023 | down 57.1% | falling |
| 35 | Greece | 3 1000 t | 2023 | up 200.0% | rising |
| 35 | Ireland | 3 1000 t | 2023 | up 200.0% | rising |
| 35 | Kazakhstan | 3 1000 t | 2023 | unchanged | rising |
| 35 | Austria | 3 1000 t | 2023 | down 72.7% | volatile |
| 41 | Myanmar | 2 1000 t | 2023 | down 33.3% | falling |
| 41 | Switzerland | 2 1000 t | 2023 | down 50.0% | falling |
| 41 | Ethiopia | 2 1000 t | 2023 | down 60.0% | volatile |
| 41 | Algeria | 2 1000 t | 2023 | unchanged | flat |
| 41 | Republic of Moldova | 2 1000 t | 2023 | up 100.0% | volatile |
| 46 | Mongolia | 1 1000 t | 2023 | down 66.7% | volatile |
| 46 | Romania | 1 1000 t | 2023 | down 80.0% | volatile |
| 46 | Luxembourg | 1 1000 t | 2023 | down 50.0% | volatile |
| 46 | Bosnia and Herzegovina | 1 1000 t | 2023 | — | volatile |
| 46 | Italy | 1 1000 t | 2023 | down 50.0% | falling |
| 51 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | flat |
| 51 | Republic of Korea | 0 1000 t | 2023 | — | flat |
| 51 | Bahrain | 0 1000 t | 2023 | — | flat |
| 51 | China, Taiwan Province of | 0 1000 t | 2023 | — | flat |
| 51 | Denmark | 0 1000 t | 2023 | — | flat |
| 51 | Colombia | 0 1000 t | 2019 | — | flat |
| 51 | Bhutan | 0 1000 t | 2023 | — | flat |
| 51 | Croatia | 0 1000 t | 2023 | down 100.0% | volatile |
| 51 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 51 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 51 | Morocco | 0 1000 t | 2023 | — | flat |
| 51 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 51 | Norway | 0 1000 t | 2023 | — | volatile |
| 51 | New Zealand | 0 1000 t | 2023 | — | flat |
| 51 | Rwanda | 0 1000 t | 2019 | — | flat |
| 51 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 51 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 51 | Tunisia | 0 1000 t | 2023 | — | flat |
| 51 | Uzbekistan | 0 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.
- World 4,131 1000 t
- Asia 1,696 1000 t
- Europe 1,574 1000 t
- European Union (27) 1,306 1000 t
- Southern Asia 1,056 1000 t
- Western Europe 1,049 1000 t
- Americas 667 1000 t
- Eastern Asia 622 1000 t
- Northern America 608 1000 t
- Eastern Europe 319 1000 t
- Northern Europe 180 1000 t
- Oceania 172 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.