Treenuts — 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
Treenuts — Losses is currently reported for 92 countries. The highest value is 237 1000 t in United States; the lowest is 0 1000 t in Netherlands (Kingdom of the).
The median across all reporting countries is 3 1000 t, and the mean is 14.03 1000 t.
Over the past decade 35 countries rose and 20 fell. The largest increase was in Spain (up 800.0%), and the largest decrease in Switzerland (down 100.0%).
Treenuts — Losses: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | United States | 237 1000 t | 2023 | down 6.3% | falling |
| 2 | China | 178 1000 t | 2023 | up 1.7% | flat |
| 3 | China, mainland | 167 1000 t | 2023 | down 2.9% | falling |
| 4 | India | 66 1000 t | 2023 | up 53.5% | rising |
| 5 | Turkey | 52 1000 t | 2023 | up 40.5% | rising |
| 5 | Türkiye | 52 1000 t | 2023 | up 40.5% | rising |
| 7 | Iran (Islamic Republic of) | 41 1000 t | 2023 | up 20.6% | rising |
| 8 | Cote d'Ivoire | 37 1000 t | 2023 | up 94.7% | rising |
| 8 | Côte d'Ivoire | 37 1000 t | 2023 | up 94.7% | rising |
| 10 | Spain | 27 1000 t | 2023 | up 800.0% | volatile |
| 11 | Indonesia | 25 1000 t | 2023 | down 7.4% | falling |
| 12 | Bangladesh | 19 1000 t | 2023 | down 17.4% | rising |
| 13 | Burkina Faso | 16 1000 t | 2023 | up 166.7% | volatile |
| 13 | Guinea-Bissau | 16 1000 t | 2023 | up 14.3% | rising |
| 13 | Mexico | 16 1000 t | 2023 | up 33.3% | rising |
| 16 | Italy | 14 1000 t | 2023 | up 180.0% | rising |
| 17 | Nigeria | 13 1000 t | 2023 | down 23.5% | volatile |
| 17 | Vietnam | 13 1000 t | 2023 | down 7.1% | flat |
| 17 | Viet Nam | 13 1000 t | 2023 | down 7.1% | flat |
| 20 | Chile | 12 1000 t | 2023 | up 200.0% | rising |
| 21 | United Republic of Tanzania | 11 1000 t | 2023 | up 57.1% | rising |
| 21 | China, Taiwan Province of | 11 1000 t | 2023 | down 15.4% | falling |
| 23 | Syria | 10 1000 t | 2023 | up 25.0% | flat |
| 23 | Syrian Arab Republic | 10 1000 t | 2023 | up 25.0% | flat |
| 25 | Brazil | 9 1000 t | 2023 | — | volatile |
| 25 | Sri Lanka | 9 1000 t | 2023 | up 80.0% | rising |
| 25 | Morocco | 9 1000 t | 2023 | up 50.0% | rising |
| 28 | Australia | 8 1000 t | 2023 | down 27.3% | rising |
| 28 | Myanmar | 8 1000 t | 2023 | up 100.0% | rising |
| 28 | Australia and New Zealand | 8 1000 t | 2023 | down 27.3% | rising |
| 31 | Greece | 7 1000 t | 2023 | up 133.3% | rising |
| 31 | Mozambique | 7 1000 t | 2023 | up 75.0% | rising |
| 31 | Philippines | 7 1000 t | 2023 | down 12.5% | rising |
| 31 | Thailand | 7 1000 t | 2023 | up 16.7% | rising |
| 35 | Portugal | 6 1000 t | 2023 | up 200.0% | rising |
| 35 | Ukraine | 6 1000 t | 2023 | unchanged | rising |
| 35 | Bolivia (Plurinational State of) | 6 1000 t | 2023 | unchanged | rising |
| 38 | Afghanistan | 5 1000 t | 2023 | up 66.7% | rising |
| 38 | Azerbaijan | 5 1000 t | 2023 | up 150.0% | rising |
| 38 | Cameroon | 5 1000 t | 2023 | up 25.0% | rising |
| 38 | Uzbekistan | 5 1000 t | 2023 | up 25.0% | rising |
| 42 | Algeria | 4 1000 t | 2023 | up 33.3% | rising |
| 42 | Poland | 4 1000 t | 2023 | up 100.0% | rising |
| 42 | Tunisia | 4 1000 t | 2023 | up 33.3% | rising |
| 42 | Republic of Korea | 4 1000 t | 2023 | unchanged | falling |
| 46 | Colombia | 3 1000 t | 2023 | — | volatile |
| 46 | Ethiopia | 3 1000 t | 2023 | unchanged | falling |
| 46 | France | 3 1000 t | 2023 | unchanged | rising |
| 46 | Pakistan | 3 1000 t | 2023 | up 50.0% | rising |
| 46 | Romania | 3 1000 t | 2023 | up 50.0% | rising |
| 46 | Zimbabwe | 3 1000 t | 2023 | — | volatile |
| 52 | Germany | 2 1000 t | 2023 | down 94.9% | volatile |
| 52 | Egypt | 2 1000 t | 2023 | unchanged | falling |
| 52 | Guinea | 2 1000 t | 2023 | — | volatile |
| 52 | Gambia | 2 1000 t | 2023 | — | volatile |
| 52 | Guatemala | 2 1000 t | 2023 | unchanged | flat |
| 52 | Kenya | 2 1000 t | 2023 | unchanged | falling |
| 52 | Kyrgyzstan | 2 1000 t | 2023 | up 100.0% | rising |
| 52 | Lebanon | 2 1000 t | 2023 | unchanged | flat |
| 52 | Libya | 2 1000 t | 2023 | unchanged | flat |
| 52 | Madagascar | 2 1000 t | 2023 | up 100.0% | rising |
| 52 | Nepal | 2 1000 t | 2023 | down 71.4% | volatile |
| 52 | South Africa | 2 1000 t | 2023 | unchanged | rising |
| 52 | Democratic People's Republic of Korea | 2 1000 t | 2018 | up 100.0% | rising |
| 65 | Albania | 1 1000 t | 2023 | unchanged | flat |
| 65 | United Arab Emirates | 1 1000 t | 2023 | — | volatile |
| 65 | Argentina | 1 1000 t | 2023 | unchanged | flat |
| 65 | Belgium | 1 1000 t | 2023 | unchanged | rising |
| 65 | Bosnia and Herzegovina | 1 1000 t | 2023 | — | volatile |
| 65 | Belarus | 1 1000 t | 2023 | unchanged | flat |
| 65 | Bhutan | 1 1000 t | 2023 | — | falling |
| 65 | Georgia | 1 1000 t | 2023 | unchanged | volatile |
| 65 | Ghana | 1 1000 t | 2023 | down 50.0% | falling |
| 65 | Hungary | 1 1000 t | 2023 | — | volatile |
| 65 | Iraq | 1 1000 t | 2023 | — | volatile |
| 65 | Israel | 1 1000 t | 2023 | unchanged | rising |
| 65 | Moldova | 1 1000 t | 2023 | unchanged | flat |
| 65 | Malaysia | 1 1000 t | 2023 | unchanged | volatile |
| 65 | Peru | 1 1000 t | 2023 | unchanged | flat |
| 65 | Russia | 1 1000 t | 2023 | unchanged | rising |
| 65 | Senegal | 1 1000 t | 2023 | unchanged | rising |
| 65 | Sierra Leone | 1 1000 t | 2023 | unchanged | flat |
| 65 | Serbia | 1 1000 t | 2023 | unchanged | flat |
| 65 | Republic of Moldova | 1 1000 t | 2023 | unchanged | flat |
| 65 | Russian Federation | 1 1000 t | 2023 | unchanged | rising |
| 86 | Austria | 0 1000 t | 2023 | — | volatile |
| 86 | Switzerland | 0 1000 t | 2023 | down 100.0% | volatile |
| 86 | Luxembourg | 0 1000 t | 2023 | down 100.0% | volatile |
| 86 | Slovenia | 0 1000 t | 2023 | down 100.0% | volatile |
| 86 | Sweden | 0 1000 t | 2023 | down 100.0% | volatile |
| 86 | China, Hong Kong SAR | 0 1000 t | 2023 | down 100.0% | volatile |
| 86 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | down 100.0% | falling |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 1,026 1000 t
- Asia 474 1000 t
- Americas 287 1000 t
- Northern America 237 1000 t
- United States of America 237 1000 t
- Net Food Importing Developing Countries (NFIDCs) 193 1000 t
- Eastern Asia 186 1000 t
- Africa 175 1000 t
- Southern Asia 146 1000 t
- Low Income Food Deficit Countries (LIFDCs) 128 1000 t
- Least Developed Countries (LDCs) 126 1000 t
- Western Africa 120 1000 t
- Europe 83 1000 t
- Western Asia 74 1000 t
- European Union (27) 70 1000 t
- South-Eastern Asia 60 1000 t
- Southern Europe 57 1000 t
- Land Locked Developing Countries (LLDCs) 56 1000 t
- South America 32 1000 t
- Eastern Africa 28 1000 t
- Northern Africa 20 1000 t
- Eastern Europe 18 1000 t
- Central America 18 1000 t
- Small island developing States (SIDS) 17 1000 t
- Oceania 8 1000 t
- Central Asia 8 1000 t
- Western Europe 7 1000 t
- Middle Africa 5 1000 t
- Southern Africa 2 1000 t
- Northern Europe 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.