Cassava and products — 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
Cassava and products — Stock Variation is currently reported for 61 countries. The highest value is 1,600 1000 t in United Republic of Tanzania; the lowest is -119 1000 t in Malawi.
The median across all reporting countries is 0 1000 t, and the mean is 49.26 1000 t.
The gap between the highest and lowest reporting country is a factor of about 13.
Over the past decade 9 countries rose and 7 fell. The largest increase was in Lao People's Democratic Republic (up 4,060.0%), and the largest decrease in Malawi (down 540.7%).
Cassava and products — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | United Republic of Tanzania | 1,600 1000 t | 2023 | up 717.8% | volatile |
| 2 | Lao People's Democratic Republic | 1,386 1000 t | 2023 | up 4,060.0% | volatile |
| 3 | Sierra Leone | 200 1000 t | 2023 | up 1,918.2% | volatile |
| 4 | Viet Nam | 78 1000 t | 2023 | — | volatile |
| 5 | Cameroon | 5 1000 t | 2023 | up 66.7% | volatile |
| 6 | Honduras | 1 1000 t | 2023 | unchanged | volatile |
| 7 | Suriname | 0 1000 t | 2023 | — | flat |
| 7 | Zimbabwe | 0 1000 t | 2023 | — | flat |
| 7 | Zambia | 0 1000 t | 2023 | — | flat |
| 7 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 7 | Thailand | 0 1000 t | 2023 | up 100.0% | volatile |
| 7 | Eswatini | 0 1000 t | 2023 | — | flat |
| 7 | Qatar | 0 1000 t | 2023 | — | volatile |
| 7 | Senegal | 0 1000 t | 2023 | — | flat |
| 7 | Rwanda | 0 1000 t | 2023 | up 100.0% | volatile |
| 7 | Uganda | 0 1000 t | 2023 | — | flat |
| 7 | Micronesia | 0 1000 t | 2023 | — | flat |
| 7 | Polynesia | 0 1000 t | 2023 | — | flat |
| 7 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 7 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 7 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 7 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | flat |
| 7 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 7 | China, mainland | 0 1000 t | 2023 | — | flat |
| 7 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 7 | China, Taiwan Province of | 0 1000 t | 2023 | — | flat |
| 7 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | volatile |
| 7 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | flat |
| 7 | Costa Rica | 0 1000 t | 2023 | up 100.0% | volatile |
| 7 | Kenya | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | India | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | Paraguay | 0 1000 t | 2023 | — | flat |
| 7 | Guatemala | 0 1000 t | 2023 | — | flat |
| 7 | Guinea | 0 1000 t | 2023 | — | flat |
| 7 | Ethiopia | 0 1000 t | 2023 | — | flat |
| 7 | Egypt | 0 1000 t | 2023 | — | flat |
| 7 | Ecuador | 0 1000 t | 2023 | — | volatile |
| 7 | Denmark | 0 1000 t | 2023 | — | flat |
| 7 | Indonesia | 0 1000 t | 2023 | — | volatile |
| 7 | Colombia | 0 1000 t | 2023 | — | volatile |
| 7 | Congo | 0 1000 t | 2023 | — | flat |
| 7 | China | 0 1000 t | 2023 | — | flat |
| 7 | Bahrain | 0 1000 t | 2023 | — | flat |
| 7 | Bulgaria | 0 1000 t | 2023 | — | flat |
| 7 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 7 | Belgium | 0 1000 t | 2023 | — | flat |
| 7 | Angola | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | Philippines | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 7 | Sri Lanka | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | Liberia | 0 1000 t | 2023 | down 100.0% | volatile |
| 7 | Niger | 0 1000 t | 2023 | — | flat |
| 7 | Nigeria | 0 1000 t | 2023 | — | flat |
| 7 | Nepal | 0 1000 t | 2023 | — | flat |
| 7 | Pakistan | 0 1000 t | 2023 | — | flat |
| 7 | Peru | 0 1000 t | 2023 | — | flat |
| 57 | Mexico | -2 1000 t | 2023 | up 33.3% | volatile |
| 58 | Mozambique | -7 1000 t | 2023 | up 87.7% | volatile |
| 59 | Cambodia | -57 1000 t | 2023 | — | volatile |
| 60 | Madagascar | -80 1000 t | 2023 | — | volatile |
| 61 | Malawi | -119 1000 t | 2023 | down 540.7% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 3,004 1000 t
- Net Food Importing Developing Countries (NFIDCs) 2,924 1000 t
- Least Developed Countries (LDCs) 2,923 1000 t
- Low Income Food Deficit Countries (LIFDCs) 1,599 1000 t
- Africa 1,599 1000 t
- Asia 1,406 1000 t
- South-Eastern Asia 1,406 1000 t
- Eastern Africa 1,394 1000 t
- Land Locked Developing Countries (LLDCs) 1,267 1000 t
- Western Africa 200 1000 t
- Middle Africa 5 1000 t
- Western Asia 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.