Soft-Fibres, Other — Import Quantity by country

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
146
Highest
140,737 t
China, mainland
Lowest
0 t
China, Macao SAR
Median
11.5 t
Years covered
53
1961–2013
Data points
8,414

What the numbers show

Soft-Fibres, Other — Import Quantity is currently reported for 146 countries. The highest value is 140,737 t in China, mainland; the lowest is 0 t in China, Macao SAR.

The median across all reporting countries is 11.5 t, and the mean is 3,380 t.

Over the past decade 28 countries rose and 60 fell. The largest increase was in Australia and New Zealand (up 13,550.0%), and the largest decrease in Viet Nam (down 100.0%).

Soft-Fibres, Other — Import Quantity: full country ranking

#Country LatestYear 10-year changeTrend
1 China, mainland 140,737 t 2013 up 34.5% volatile
2 Belgium-Luxembourg 121,275 t 1999 down 6.5% falling
3 Belgium 105,754 t 2013 down 30.1% falling
3 Iran (Islamic Republic of) 55 t 2013 — volatile
4 France 18,064 t 2013 down 57.6% flat
5 Netherlands (Kingdom of the) 13,508 t 2013 up 186.4% volatile
5 Republic of Moldova 7 t 2013 up 600.0% volatile
6 Spain 10,115 t 2013 down 42.6% rising
6 Melanesia 6 t 2013 — volatile
7 Lithuania 9,834 t 2013 down 42.7% volatile
7 Venezuela (Bolivarian Republic of) 4 t 2013 — volatile
8 Czechia 9,467 t 2013 down 5.9% rising
8 Bolivia (Plurinational State of) 3 t 2013 up 200.0% volatile
9 USSR 8,400 t 1991 — volatile
9 United Republic of Tanzania 1 t 2013 — volatile
10 Russian Federation 7,720 t 2013 down 16.5% volatile
10 Polynesia 0 t 2013 — volatile
10 Viet Nam 0 t 2013 down 100.0% volatile
11 Germany 7,491 t 2013 down 32.3% volatile
12 India 7,038 t 2013 up 173.7% volatile
13 Japan 6,972 t 2013 down 52.0% falling
14 Poland 6,470 t 2013 down 23.7% falling
15 Tunisia 2,377 t 2013 up 55.8% volatile
16 T�rkiye 2,216 t 2013 up 47.5% volatile
17 Czechoslovakia 2,150 t 1992 down 73.1% falling
18 Italy 1,996 t 2013 down 87.9% falling
19 Hungary 1,387 t 2013 down 28.4% volatile
20 Romania 1,068 t 2013 down 36.3% volatile
21 Yugoslav SFR 1,000 t 1991 down 68.7% volatile
22 Egypt 802 t 2013 up 854.8% volatile
23 Slovenia 764 t 2013 up 58.5% volatile
24 Brazil 743 t 2013 up 13.3% volatile
25 Latvia 638 t 2013 down 65.1% volatile
26 Switzerland 548 t 2013 up 17.1% volatile
27 Canada 466 t 2013 down 58.9% volatile
27 Caribbean 12 t 2013 up 300.0% volatile
28 South Africa 310 t 2013 down 64.8% volatile
29 China, Taiwan Province of 305 t 2013 down 82.6% volatile
30 Denmark 304 t 2013 up 44.8% volatile
31 Australia and New Zealand 273 t 2013 up 13,550.0% volatile
32 Australia 258 t 2013 up 12,800.0% volatile
33 Belarus 234 t 2013 down 93.7% volatile
34 United Kingdom of Great Britain and Northern Ireland 213 t 2013 down 93.4% volatile
35 United Arab Emirates 195 t 2013 — volatile
36 Portugal 184 t 2013 up 27.8% volatile
37 Thailand 177 t 2013 up 45.1% volatile
38 Greece 154 t 2013 down 44.4% volatile
39 Ethiopia PDR 150 t 1992 — volatile
40 Ukraine 134 t 2013 — volatile
41 Saudi Arabia 122 t 2013 down 81.9% volatile
42 Philippines 90 t 2013 — volatile
43 Malaysia 87 t 2013 down 91.3% volatile
44 Austria 82 t 2013 down 98.2% falling
45 Morocco 78 t 2013 up 25.8% volatile
46 Serbia and Montenegro 70 t 2005 — volatile
47 Pakistan 68 t 2013 up 78.9% volatile
48 C�te d'Ivoire 67 t 2013 up 1,240.0% volatile
49 Argentina 62 t 2013 up 26.5% volatile
50 Israel 61 t 2013 up 60.5% volatile
50 Kazakhstan 61 t 2013 — volatile
52 Chile 56 t 2013 down 72.4% volatile
53 Republic of Korea 42 t 2013 down 93.9% volatile
54 Congo 38 t 2013 — volatile
55 Indonesia 36 t 2013 down 90.7% volatile
56 Sweden 30 t 2013 down 50.0% volatile
57 Nigeria 28 t 2013 — volatile
58 Slovakia 27 t 2013 down 97.4% volatile
59 Botswana 24 t 2013 down 33.3% volatile
59 Ethiopia 24 t 2013 up 100.0% volatile
59 Jordan 24 t 2013 down 33.3% volatile
62 Estonia 23 t 2013 down 99.1% volatile
62 Lebanon 23 t 2013 up 27.8% volatile
64 Serbia 22 t 2013 down 81.2% volatile
65 Finland 18 t 2013 down 96.5% volatile
66 Bulgaria 15 t 2013 down 93.1% volatile
66 Norway 15 t 2013 down 21.1% volatile
66 New Zealand 15 t 2013 — volatile
69 Oman 14 t 2013 unchanged volatile
70 Ireland 13 t 2013 down 27.8% volatile
71 Jamaica 12 t 2013 — volatile
72 Algeria 11 t 2013 down 47.6% volatile
72 Gabon 11 t 2013 — volatile
74 Iceland 9 t 2013 up 50.0% volatile
74 Sri Lanka 9 t 2013 up 125.0% volatile
74 Nepal 9 t 2013 down 97.7% volatile
77 Bosnia and Herzegovina 8 t 2013 down 27.3% volatile
77 Peru 8 t 2013 down 20.0% volatile
79 Croatia 7 t 2013 down 82.9% volatile
79 Zambia 7 t 2013 — volatile
81 New Caledonia 6 t 2013 — volatile
82 Cameroon 4 t 2013 up 100.0% volatile
83 Albania 3 t 2013 up 200.0% volatile
83 Mexico 3 t 2013 down 96.6% volatile
83 North Macedonia 3 t 2013 unchanged volatile
86 Georgia 2 t 2013 — volatile
86 Kuwait 2 t 2013 — volatile
86 Luxembourg 2 t 2013 down 60.0% volatile
86 Niger 2 t 2013 — volatile
86 Rwanda 2 t 2013 — volatile
86 Senegal 2 t 2013 down 60.0% volatile
86 Uruguay 2 t 2013 down 84.6% volatile
93 Angola 1 t 2013 — volatile
93 Guatemala 1 t 2013 — volatile
93 Honduras 1 t 2013 unchanged volatile
93 Iraq 1 t 2013 — volatile
93 Madagascar 1 t 2013 — volatile
93 Mongolia 1 t 2013 down 88.9% volatile
93 Mozambique 1 t 2013 — volatile
93 Eswatini 1 t 2013 down 83.3% volatile
101 Azerbaijan 0 t 2013 — volatile
101 Benin 0 t 2013 — volatile
101 Bangladesh 0 t 2013 — volatile
101 Barbados 0 t 2013 down 100.0% volatile
101 Colombia 0 t 2013 down 100.0% volatile
101 Costa Rica 0 t 2013 — volatile
101 Cyprus 0 t 2013 down 100.0% volatile
101 Djibouti 0 t 2013 — volatile
101 Dominican Republic 0 t 2013 — volatile
101 Ecuador 0 t 2013 — volatile
101 Fiji 0 t 2013 — volatile
101 Ghana 0 t 2013 down 100.0% volatile
101 Gambia 0 t 2013 down 100.0% volatile
101 Grenada 0 t 2013 — volatile
101 Guyana 0 t 2013 — volatile
101 Haiti 0 t 2013 — volatile
101 Kenya 0 t 2013 — volatile
101 Kyrgyzstan 0 t 2013 — volatile
101 Malta 0 t 2013 down 100.0% volatile
101 Myanmar 0 t 2013 — volatile
101 Mauritania 0 t 2013 — volatile
101 Mauritius 0 t 2013 — volatile
101 Namibia 0 t 2013 down 100.0% volatile
101 Nicaragua 0 t 2013 — volatile
101 Panama 0 t 2013 — volatile
101 Paraguay 0 t 2013 — volatile
101 French Polynesia 0 t 2013 — volatile
101 El Salvador 0 t 2013 down 100.0% volatile
101 Suriname 0 t 2013 — volatile
101 Togo 0 t 2013 — volatile
101 Turkmenistan 0 t 2013 — volatile
101 Trinidad and Tobago 0 t 2013 — volatile
101 Uganda 0 t 2013 — volatile
101 Yemen 0 t 2013 down 100.0% volatile
101 Zimbabwe 0 t 2013 — volatile
101 China, Hong Kong SAR 0 t 2013 down 100.0% volatile
101 China, Macao SAR 0 t 2013 — 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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Soft-Fibres, Other — Import Quantity by country. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 05 October 2026, from https://agriculture.statizoid.com/stat/soft-fibres-other-import-quantity/

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About this data

Indicator
Soft-Fibres, Other — Import Quantity
Unit
t
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
176 places, 8,414 data points, 1961–2013
Last refreshed

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 caput 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.