Sweet potatoes — 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...

Countries reporting
80
Highest
2,580 1000 t
China
Lowest
0 1000 t
Bolivia (Plurinational State of)
Median
10 1000 t
Years covered
14
2010–2023
Data points
1,878

What the numbers show

Sweet potatoes — Losses is currently reported for 80 countries. The highest value is 2,580 1000 t in China; the lowest is 0 1000 t in Bolivia (Plurinational State of).

The median across all reporting countries is 10 1000 t, and the mean is 110.2 1000 t.

Over the past decade 35 countries rose and 25 fell. The largest increase was in Zimbabwe (up 850.0%), and the largest decrease in Portugal (down 100.0%).

Sweet potatoes — Losses: full country ranking

#Country LatestYear 10-year changeTrend
1 China 2,580 1000 t 2023 down 9.5% falling
2 China, mainland 2,575 1000 t 2023 down 9.5% falling
3 Nigeria 1,113 1000 t 2023 up 9.7% rising
4 Malawi 482 1000 t 2023 — volatile
5 Madagascar 156 1000 t 2023 up 16.4% rising
6 United Republic of Tanzania 146 1000 t 2023 down 44.1% flat
7 Angola 140 1000 t 2023 up 55.6% rising
8 India 99 1000 t 2023 up 16.5% rising
8 Rwanda 99 1000 t 2023 up 22.2% rising
10 Melanesia 98 1000 t 2023 up 8.9% rising
11 Ethiopia 96 1000 t 2023 down 36.8% flat
12 Papua New Guinea 95 1000 t 2023 up 8.0% rising
13 Indonesia 82 1000 t 2023 down 62.0% falling
14 Brazil 70 1000 t 2023 up 84.2% rising
14 Vietnam 70 1000 t 2023 down 31.4% falling
14 Viet Nam 70 1000 t 2023 down 31.4% falling
17 Kenya 67 1000 t 2023 up 21.8% rising
18 Guinea 56 1000 t 2023 up 69.7% rising
19 Democratic People's Republic of Korea 47 1000 t 2018 up 46.9% rising
20 Cameroon 46 1000 t 2023 up 76.9% rising
20 Peru 46 1000 t 2023 up 9.5% rising
20 Uganda 46 1000 t 2023 down 8.0% falling
23 Caribbean 43 1000 t 2023 down 71.3% falling
24 Egypt 40 1000 t 2023 down 4.8% rising
25 Mozambique 36 1000 t 2023 down 68.7% falling
26 Sierra Leone 34 1000 t 2023 down 50.0% falling
27 Democratic Republic of the Congo 30 1000 t 2023 down 14.3% rising
28 Ghana 27 1000 t 2023 up 3.8% rising
29 Bangladesh 23 1000 t 2023 up 15.0% flat
30 Cuba 22 1000 t 2019 up 29.4% rising
31 Republic of Korea 21 1000 t 2023 unchanged rising
32 Haiti 20 1000 t 2023 down 83.5% volatile
33 Zimbabwe 19 1000 t 2023 up 850.0% volatile
34 Senegal 17 1000 t 2023 up 183.3% rising
35 Niger 16 1000 t 2023 up 128.6% rising
36 Zambia 15 1000 t 2023 up 7.1% falling
37 United States 13 1000 t 2023 up 18.2% rising
38 Philippines 11 1000 t 2023 up 10.0% rising
39 Argentina 10 1000 t 2023 down 64.3% falling
39 Burkina Faso 10 1000 t 2023 down 23.1% rising
39 Netherlands (Kingdom of the) 10 1000 t 2023 up 400.0% volatile
42 Cote d'Ivoire 9 1000 t 2023 up 28.6% rising
42 Côte d'Ivoire 9 1000 t 2023 up 28.6% rising
44 Australia and New Zealand 8 1000 t 2023 up 33.3% rising
45 Australia 7 1000 t 2023 up 40.0% rising
45 Laos 7 1000 t 2023 up 40.0% rising
45 Lao People's Democratic Republic 7 1000 t 2023 up 40.0% rising
48 Dominican Republic 6 1000 t 2023 up 50.0% rising
48 Jamaica 6 1000 t 2023 down 14.3% rising
48 Mexico 6 1000 t 2023 up 100.0% rising
48 Uruguay 6 1000 t 2023 unchanged rising
52 China, Taiwan Province of 5 1000 t 2023 unchanged flat
53 South Africa 4 1000 t 2023 up 300.0% volatile
54 Guyana 3 1000 t 2023 — volatile
54 Cambodia 3 1000 t 2023 unchanged falling
54 Sri Lanka 3 1000 t 2023 unchanged falling
54 Myanmar 3 1000 t 2023 unchanged flat
54 Malaysia 3 1000 t 2023 down 25.0% rising
59 Honduras 2 1000 t 2023 up 100.0% rising
59 Israel 2 1000 t 2023 unchanged rising
59 Liberia 2 1000 t 2023 unchanged flat
59 Morocco 2 1000 t 2023 down 50.0% falling
59 Pakistan 2 1000 t 2023 up 100.0% rising
59 Paraguay 2 1000 t 2023 down 33.3% flat
59 Solomon Islands 2 1000 t 2023 unchanged flat
59 Venezuela (Bolivarian Republic of) 2 1000 t 2023 up 100.0% rising
67 Canada 1 1000 t 2023 unchanged flat
67 Chile 1 1000 t 2023 unchanged flat
67 Congo 1 1000 t 2023 unchanged flat
67 Comoros 1 1000 t 2023 unchanged flat
67 Spain 1 1000 t 2023 unchanged volatile
67 Mauritania 1 1000 t 2023 — volatile
67 New Zealand 1 1000 t 2023 unchanged flat
67 Eswatini 1 1000 t 2023 — volatile
67 Thailand 1 1000 t 2023 down 50.0% rising
76 Portugal 0 1000 t 2023 down 100.0% volatile
76 East Timor 0 1000 t 2023 down 100.0% volatile
76 Timor-Leste 0 1000 t 2023 down 100.0% volatile
76 Cabo Verde 0 1000 t 2023 down 100.0% volatile
76 Bolivia (Plurinational State of) 0 1000 t 2023 — volatile

Regions and income groups

Aggregates are excluded from the country ranking above so that a region can never outrank a country.

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Sweet potatoes — Losses by country. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 02 October 2026, from https://agriculture.statizoid.com/stat/sweet-potatoes-losses/

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About this data

Indicator
Sweet potatoes — Losses
Unit
1000 t
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
141 places, 1,878 data points, 2010–2023
Last refreshed

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.