Peas — 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
Peas — Losses is currently reported for 62 countries. The highest value is 240 1000 t in Russia; the lowest is 0 1000 t in Tunisia.
The median across all reporting countries is 2 1000 t, and the mean is 16.77 1000 t.
Over the past decade 21 countries rose and 12 fell. The largest increase was in United Kingdom (up 300.0%), and the largest decrease in Malawi (down 100.0%).
Peas — Losses: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Russia | 240 1000 t | 2023 | up 172.7% | rising |
| 1 | Russian Federation | 240 1000 t | 2023 | up 172.7% | rising |
| 3 | China | 113 1000 t | 2023 | up 79.4% | rising |
| 3 | China, mainland | 113 1000 t | 2023 | up 79.4% | rising |
| 5 | Canada | 55 1000 t | 2023 | down 33.7% | flat |
| 6 | United States | 41 1000 t | 2023 | up 10.8% | falling |
| 7 | Spain | 30 1000 t | 2023 | up 100.0% | rising |
| 8 | India | 27 1000 t | 2023 | down 32.5% | falling |
| 9 | Ethiopia | 20 1000 t | 2023 | up 5.3% | rising |
| 10 | Australia and New Zealand | 16 1000 t | 2023 | down 5.9% | falling |
| 11 | Australia | 15 1000 t | 2023 | down 6.2% | falling |
| 12 | France | 12 1000 t | 2023 | down 20.0% | falling |
| 13 | Latvia | 8 1000 t | 2023 | — | volatile |
| 13 | United Kingdom | 8 1000 t | 2023 | up 300.0% | rising |
| 13 | United Kingdom of Great Britain and Northern Ireland | 8 1000 t | 2023 | up 300.0% | rising |
| 16 | Ukraine | 7 1000 t | 2023 | down 46.2% | volatile |
| 17 | Lithuania | 6 1000 t | 2023 | up 200.0% | volatile |
| 17 | Germany | 6 1000 t | 2023 | up 50.0% | rising |
| 17 | Romania | 6 1000 t | 2023 | up 200.0% | volatile |
| 20 | Czechia | 5 1000 t | 2023 | up 150.0% | rising |
| 20 | Kazakhstan | 5 1000 t | 2023 | up 150.0% | volatile |
| 22 | Finland | 4 1000 t | 2023 | — | volatile |
| 22 | Estonia | 4 1000 t | 2023 | up 100.0% | rising |
| 24 | Poland | 3 1000 t | 2023 | up 200.0% | rising |
| 24 | Uganda | 3 1000 t | 2023 | up 50.0% | rising |
| 24 | Belarus | 3 1000 t | 2023 | unchanged | rising |
| 24 | Sweden | 3 1000 t | 2023 | up 200.0% | rising |
| 24 | Colombia | 3 1000 t | 2023 | unchanged | volatile |
| 24 | Peru | 3 1000 t | 2023 | up 50.0% | rising |
| 24 | Italy | 3 1000 t | 2023 | up 50.0% | rising |
| 31 | Slovakia | 2 1000 t | 2023 | — | volatile |
| 31 | Denmark | 2 1000 t | 2023 | up 100.0% | rising |
| 31 | Hungary | 2 1000 t | 2023 | — | volatile |
| 31 | Morocco | 2 1000 t | 2023 | unchanged | falling |
| 31 | Myanmar | 2 1000 t | 2023 | down 33.3% | falling |
| 36 | Türkiye | 1 1000 t | 2023 | — | volatile |
| 36 | Argentina | 1 1000 t | 2023 | down 66.7% | falling |
| 36 | Austria | 1 1000 t | 2023 | unchanged | volatile |
| 36 | Bangladesh | 1 1000 t | 2023 | unchanged | falling |
| 36 | Bulgaria | 1 1000 t | 2023 | — | volatile |
| 36 | Switzerland | 1 1000 t | 2023 | — | volatile |
| 36 | Algeria | 1 1000 t | 2023 | — | volatile |
| 36 | United Republic of Tanzania | 1 1000 t | 2023 | down 83.3% | volatile |
| 36 | Sri Lanka | 1 1000 t | 2023 | unchanged | rising |
| 36 | Moldova | 1 1000 t | 2023 | — | volatile |
| 36 | Madagascar | 1 1000 t | 2023 | unchanged | flat |
| 36 | Venezuela (Bolivarian Republic of) | 1 1000 t | 2023 | unchanged | volatile |
| 36 | Republic of Moldova | 1 1000 t | 2023 | — | volatile |
| 36 | New Zealand | 1 1000 t | 2023 | unchanged | falling |
| 36 | Pakistan | 1 1000 t | 2023 | unchanged | volatile |
| 36 | Portugal | 1 1000 t | 2023 | — | volatile |
| 36 | Rwanda | 1 1000 t | 2023 | unchanged | falling |
| 36 | Tajikistan | 1 1000 t | 2023 | — | volatile |
| 36 | Turkmenistan | 1 1000 t | 2023 | unchanged | flat |
| 36 | Turkey | 1 1000 t | 2023 | — | volatile |
| 56 | Yemen | 0 1000 t | 2023 | — | volatile |
| 56 | Mauritania | 0 1000 t | 2023 | — | volatile |
| 56 | Malawi | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 56 | Sierra Leone | 0 1000 t | 2023 | down 100.0% | volatile |
| 56 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 56 | Tunisia | 0 1000 t | 2023 | down 100.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 664 1000 t
- Europe 359 1000 t
- Eastern Europe 270 1000 t
- Asia 154 1000 t
- Eastern Asia 113 1000 t
- Americas 105 1000 t
- European Union (27) 98 1000 t
- Northern America 96 1000 t
- United States of America 41 1000 t
- Net Food Importing Developing Countries (NFIDCs) 38 1000 t
- Northern Europe 35 1000 t
- Southern Europe 34 1000 t
- Land Locked Developing Countries (LLDCs) 33 1000 t
- Africa 30 1000 t
- Least Developed Countries (LDCs) 30 1000 t
- Southern Asia 30 1000 t
- Low Income Food Deficit Countries (LIFDCs) 29 1000 t
- Eastern Africa 26 1000 t
- Western Europe 20 1000 t
- Oceania 16 1000 t
- South America 8 1000 t
- Central Asia 7 1000 t
- Northern Africa 3 1000 t
- South-Eastern Asia 3 1000 t
- Western Asia 2 1000 t
- Western Africa 1 1000 t
- Middle Africa 1 1000 t
- Small island developing States (SIDS) 0 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.