Palm kernels — 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
Palm kernels — Stock Variation is currently reported for 58 countries. The highest value is 518 1000 t in Brazil; the lowest is -6,703 1000 t in Indonesia.
The median across all reporting countries is 0 1000 t, and the mean is -84.29 1000 t.
Over the past decade 23 countries rose and 6 fell. The largest increase was in Peru (up 6,900.0%), and the largest decrease in Mexico (down 7,737.5%).
Palm kernels — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Brazil | 518 1000 t | 2023 | — | volatile |
| 2 | Cameroon | 276 1000 t | 2023 | up 1,085.7% | volatile |
| 3 | Malaysia | 235 1000 t | 2023 | up 115.5% | volatile |
| 4 | Côte d'Ivoire | 233 1000 t | 2023 | up 308.8% | volatile |
| 5 | Democratic Republic of the Congo | 218 1000 t | 2023 | up 220.4% | volatile |
| 6 | Nigeria | 201 1000 t | 2023 | up 260.8% | volatile |
| 7 | Colombia | 177 1000 t | 2023 | up 447.1% | volatile |
| 8 | Guatemala | 137 1000 t | 2023 | up 374.0% | volatile |
| 9 | Peru | 136 1000 t | 2023 | up 6,900.0% | volatile |
| 10 | Cambodia | 108 1000 t | 2023 | — | volatile |
| 11 | Melanesia | 96 1000 t | 2023 | up 172.7% | volatile |
| 12 | Papua New Guinea | 81 1000 t | 2023 | up 162.8% | volatile |
| 13 | Sierra Leone | 55 1000 t | 2023 | up 214.6% | volatile |
| 14 | Caribbean | 37 1000 t | 2023 | — | volatile |
| 14 | Dominican Republic | 37 1000 t | 2023 | — | volatile |
| 16 | Philippines | 33 1000 t | 2023 | up 571.4% | volatile |
| 17 | Solomon Islands | 14 1000 t | 2023 | up 566.7% | volatile |
| 18 | Ghana | 10 1000 t | 2023 | up 102.2% | volatile |
| 19 | Gabon | 5 1000 t | 2023 | up 225.0% | volatile |
| 20 | Sao Tome and Principe | 4 1000 t | 2023 | — | volatile |
| 21 | Liberia | 2 1000 t | 2023 | up 140.0% | volatile |
| 22 | Guinea | 1 1000 t | 2023 | up 101.9% | volatile |
| 23 | Senegal | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Zimbabwe | 0 1000 t | 2023 | — | flat |
| 23 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 23 | Syrian Arab Republic | 0 1000 t | 2023 | — | flat |
| 23 | Viet Nam | 0 1000 t | 2023 | — | flat |
| 23 | United Republic of Tanzania | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Yemen | 0 1000 t | 2023 | — | flat |
| 23 | Bangladesh | 0 1000 t | 2023 | — | flat |
| 23 | Ecuador | 0 1000 t | 2023 | up 100.0% | volatile |
| 23 | Ethiopia | 0 1000 t | 2023 | — | flat |
| 23 | Gambia | 0 1000 t | 2023 | — | flat |
| 23 | Guinea-Bissau | 0 1000 t | 2023 | — | volatile |
| 23 | Honduras | 0 1000 t | 2023 | down 100.0% | volatile |
| 23 | India | 0 1000 t | 2023 | — | flat |
| 23 | Kenya | 0 1000 t | 2023 | — | flat |
| 23 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 23 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 23 | Malawi | 0 1000 t | 2023 | — | flat |
| 23 | Niger | 0 1000 t | 2023 | — | flat |
| 23 | Zambia | 0 1000 t | 2023 | — | flat |
| 23 | Nepal | 0 1000 t | 2023 | — | flat |
| 23 | Pakistan | 0 1000 t | 2023 | — | flat |
| 23 | Suriname | 0 1000 t | 2023 | — | flat |
| 23 | Uganda | 0 1000 t | 2023 | — | flat |
| 47 | China | -1 1000 t | 2023 | — | volatile |
| 47 | China, mainland | -1 1000 t | 2023 | — | volatile |
| 47 | Paraguay | -1 1000 t | 2023 | — | volatile |
| 47 | Congo | -1 1000 t | 2023 | up 50.0% | rising |
| 51 | Thailand | -5 1000 t | 2023 | up 99.9% | volatile |
| 52 | Costa Rica | -6 1000 t | 2023 | — | volatile |
| 53 | Panama | -13 1000 t | 2023 | down 218.2% | volatile |
| 54 | Venezuela (Bolivarian Republic of) | -16 1000 t | 2023 | down 104.7% | volatile |
| 55 | Angola | -59 1000 t | 2023 | down 1,375.0% | volatile |
| 56 | Nicaragua | -70 1000 t | 2023 | up 30.0% | volatile |
| 57 | Mexico | -627 1000 t | 2023 | down 7,737.5% | volatile |
| 58 | Indonesia | -6,703 1000 t | 2023 | down 127.9% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Africa 857 1000 t
- South America 813 1000 t
- Net Food Importing Developing Countries (NFIDCs) 650 1000 t
- Middle Africa 444 1000 t
- Western Africa 413 1000 t
- Low Income Food Deficit Countries (LIFDCs) 398 1000 t
- Americas 271 1000 t
- Least Developed Countries (LDCs) 255 1000 t
- Small Island Developing States (SIDS) 136 1000 t
- Oceania 96 1000 t
- Western Asia 0 1000 t
- Eastern Africa 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.