Grapes and products (excl wine) — 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
Grapes and products (excl wine) — Stock Variation is currently reported for 96 countries. The highest value is 30 1000 t in Iran (Islamic Republic of); the lowest is -56 1000 t in Afghanistan.
The median across all reporting countries is 0 1000 t, and the mean is 0.3438 1000 t.
Over the past decade 27 countries rose and 20 fell. The largest increase was in Vietnam (up 700.0%), and the largest decrease in Afghanistan (down 530.8%).
Grapes and products (excl wine) — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Iran (Islamic Republic of) | 30 1000 t | 2023 | up 500.0% | volatile |
| 2 | South Africa | 16 1000 t | 2023 | up 245.5% | volatile |
| 3 | Algeria | 13 1000 t | 2023 | up 533.3% | volatile |
| 4 | Vietnam | 8 1000 t | 2023 | up 700.0% | volatile |
| 4 | Viet Nam | 8 1000 t | 2023 | up 700.0% | volatile |
| 6 | Saudi Arabia | 7 1000 t | 2023 | up 40.0% | rising |
| 7 | Pakistan | 5 1000 t | 2023 | up 400.0% | volatile |
| 7 | Netherlands (Kingdom of the) | 5 1000 t | 2023 | up 200.0% | volatile |
| 9 | Brazil | 3 1000 t | 2023 | down 66.7% | volatile |
| 10 | Indonesia | 2 1000 t | 2023 | up 300.0% | volatile |
| 10 | Namibia | 2 1000 t | 2023 | — | volatile |
| 10 | Thailand | 2 1000 t | 2023 | — | volatile |
| 13 | Argentina | 1 1000 t | 2023 | up 125.0% | volatile |
| 13 | Bangladesh | 1 1000 t | 2023 | up 125.0% | volatile |
| 13 | Nepal | 1 1000 t | 2023 | — | volatile |
| 13 | Senegal | 1 1000 t | 2023 | — | volatile |
| 17 | Armenia | 0 1000 t | 2023 | — | volatile |
| 17 | Austria | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Belgium | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Bulgaria | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Canada | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Switzerland | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | China | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Cameroon | 0 1000 t | 2023 | up 100.0% | flat |
| 17 | Congo | 0 1000 t | 2023 | — | volatile |
| 17 | Colombia | 0 1000 t | 2023 | — | flat |
| 17 | Cyprus | 0 1000 t | 2023 | — | flat |
| 17 | Germany | 0 1000 t | 2023 | — | volatile |
| 17 | Egypt | 0 1000 t | 2023 | — | volatile |
| 17 | Spain | 0 1000 t | 2023 | — | volatile |
| 17 | Ethiopia | 0 1000 t | 2023 | — | volatile |
| 17 | Finland | 0 1000 t | 2023 | — | volatile |
| 17 | United Kingdom | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Georgia | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Ghana | 0 1000 t | 2023 | — | volatile |
| 17 | Greece | 0 1000 t | 2023 | — | volatile |
| 17 | Guatemala | 0 1000 t | 2023 | — | volatile |
| 17 | Hungary | 0 1000 t | 2023 | — | flat |
| 17 | India | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Israel | 0 1000 t | 2023 | up 100.0% | flat |
| 17 | Italy | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Jamaica | 0 1000 t | 2023 | — | volatile |
| 17 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Kenya | 0 1000 t | 2023 | — | volatile |
| 17 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 17 | Kuwait | 0 1000 t | 2023 | — | volatile |
| 17 | Libya | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 17 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 17 | Moldova | 0 1000 t | 2023 | — | volatile |
| 17 | Mexico | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 17 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 17 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 17 | Nigeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Norway | 0 1000 t | 2023 | — | volatile |
| 17 | New Zealand | 0 1000 t | 2023 | up 100.0% | flat |
| 17 | Panama | 0 1000 t | 2023 | — | volatile |
| 17 | Peru | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Philippines | 0 1000 t | 2023 | — | flat |
| 17 | Poland | 0 1000 t | 2023 | — | volatile |
| 17 | Portugal | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Qatar | 0 1000 t | 2023 | — | volatile |
| 17 | Romania | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Russia | 0 1000 t | 2023 | — | volatile |
| 17 | Serbia | 0 1000 t | 2023 | — | volatile |
| 17 | Slovakia | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 17 | Eswatini | 0 1000 t | 2023 | — | volatile |
| 17 | Syria | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 17 | Turkey | 0 1000 t | 2023 | — | volatile |
| 17 | Ukraine | 0 1000 t | 2023 | down 100.0% | flat |
| 17 | United States | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Uzbekistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Yemen | 0 1000 t | 2023 | — | volatile |
| 17 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 17 | Caribbean | 0 1000 t | 2023 | — | volatile |
| 17 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 17 | Republic of Korea | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Republic of Moldova | 0 1000 t | 2023 | — | volatile |
| 17 | Russian Federation | 0 1000 t | 2023 | — | volatile |
| 17 | Syrian Arab Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 17 | Türkiye | 0 1000 t | 2023 | — | volatile |
| 17 | China, mainland | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | United Republic of Tanzania | 0 1000 t | 2023 | — | volatile |
| 17 | China, Taiwan Province of | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | up 100.0% | volatile |
| 180 | Zambia | -1 1000 t | 2023 | — | flat |
| 181 | United Arab Emirates | -5 1000 t | 2023 | up 72.2% | volatile |
| 181 | Australia | -5 1000 t | 2023 | — | flat |
| 181 | Australia and New Zealand | -5 1000 t | 2023 | down 400.0% | flat |
| 184 | Afghanistan | -56 1000 t | 2023 | down 530.8% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Africa 32 1000 t
- World 30 1000 t
- Southern Africa 18 1000 t
- Northern Africa 13 1000 t
- South-Eastern Asia 12 1000 t
- European Union (27) 6 1000 t
- Europe 6 1000 t
- Western Europe 5 1000 t
- South America 4 1000 t
- Americas 4 1000 t
- Western Africa 1 1000 t
- Western Asia 1 1000 t
- Northern America 0 1000 t
- Small island developing States (SIDS) 0 1000 t
- Central Asia 0 1000 t
- Eastern Europe 0 1000 t
- Central America 0 1000 t
- Northern Europe 0 1000 t
- Southern Europe 0 1000 t
- Middle Africa 0 1000 t
- Eastern Asia 0 1000 t
- United States of America 0 1000 t
- Eastern Africa -1 1000 t
- Oceania -5 1000 t
- Asia -7 1000 t
- Southern Asia -20 1000 t
- Net Food Importing Developing Countries (NFIDCs) -47 1000 t
- Least Developed Countries (LDCs) -54 1000 t
- Low Income Food Deficit Countries (LIFDCs) -54 1000 t
- Land Locked Developing Countries (LLDCs) -56 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.