Statizoid

Soft-Fibres, Other — Other uses (non-food) 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
137
Highest
343,990 t
USSR
Lowest
0 t
China, Macao SAR
Median
13 t
Years covered
53
1961–2013
Data points
8,520

What the numbers show

Soft-Fibres, Other — Other uses (non-food) is currently reported for 137 countries. The highest value is 343,990 t in USSR; the lowest is 0 t in China, Macao SAR.

The median across all reporting countries is 13 t, and the mean is 7,527 t.

Over the past decade 22 countries rose and 65 fell. The largest increase was in Australia and New Zealand (up 11,950.0%), and the largest decrease in Barbados (down 100.0%).

Soft-Fibres, Other — Other uses: full country ranking

#Country LatestYear 10-year changeTrend
1 USSR 343,990 t 1991 up 21.9% falling
2 China, mainland 293,874 t 2013 down 64.8% volatile
3 Indonesia 66,309 t 2013 down 26.8% rising
4 Russian Federation 47,868 t 2013 down 26.6% falling
5 Belgium 39,264 t 2013 down 20.5% falling
6 Belgium-Luxembourg 37,110 t 1999 down 44.1% volatile
7 Thailand 33,776 t 2013 down 22.0% rising
8 Netherlands (Kingdom of the) 26,084 t 2013 down 21.7% volatile
9 Belarus 23,751 t 2013 down 26.2% falling
10 United Kingdom of Great Britain and Northern Ireland 14,799 t 2013 down 62.5% volatile
11 Czechoslovakia 10,636 t 1992 down 59.7% falling
12 Czechia 10,248 t 2013 down 51.5% volatile
13 Spain 10,057 t 2013 down 49.2% volatile
14 Chile 7,256 t 2013 up 6.8% rising
15 Japan 6,958 t 2013 down 52.0% falling
16 Germany 6,930 t 2013 down 32.4% volatile
17 India 6,767 t 2013 up 175.5% volatile
18 Poland 5,710 t 2013 down 4.9% volatile
19 Egypt 5,111 t 2013 down 11.6% volatile
20 Romania 4,078 t 2013 down 8.7% volatile
21 Italy 3,496 t 2013 down 77.7% falling
22 Argentina 2,762 t 2013 up 64.8% falling
23 Tunisia 2,377 t 2013 up 55.8% volatile
24 Lithuania 2,336 t 2013 down 78.7% volatile
25 Austria 2,166 t 2013 down 68.2% falling
26 T�rkiye 2,165 t 2013 up 16.4% volatile
27 Yugoslav SFR 2,158 t 1991 down 68.6% volatile
28 Hungary 1,774 t 2013 down 12.7% volatile
29 Philippines 1,563 t 2013 up 9.0% volatile
30 Ukraine 1,512 t 2013 down 87.3% volatile
31 Brazil 1,420 t 2013 down 26.8% volatile
31 France 1,420 t 2013 down 42.4% volatile
33 Latvia 1,018 t 2013 down 53.5% rising
34 Slovenia 754 t 2013 up 58.4% volatile
35 Switzerland 512 t 2013 up 21.0% volatile
36 China, Taiwan Province of 382 t 2013 down 83.9% volatile
37 South Africa 308 t 2013 down 65.0% volatile
38 Australia and New Zealand 241 t 2013 up 11,950.0% volatile
39 Australia 226 t 2013 up 11,200.0% volatile
40 Denmark 185 t 2013 up 39.1% volatile
41 Portugal 173 t 2013 up 31.1% volatile
42 Greece 152 t 2013 down 45.1% volatile
43 Ethiopia PDR 150 t 1992 — volatile
44 Saudi Arabia 122 t 2013 down 80.5% volatile
45 Bulgaria 113 t 2013 down 77.5% volatile
46 Canada 99 t 2013 down 90.1% volatile
47 Serbia and Montenegro 90 t 2005 down 85.4% falling
48 Malaysia 87 t 2013 down 91.2% volatile
49 United Arab Emirates 85 t 2013 — volatile
50 Morocco 78 t 2013 up 25.8% volatile
51 C�te d'Ivoire 67 t 2013 up 1,240.0% volatile
52 Israel 61 t 2013 up 60.5% volatile
52 Kazakhstan 61 t 2013 — volatile
52 Republic of Korea 61 t 2013 down 91.4% volatile
55 Pakistan 42 t 2013 up 35.5% volatile
56 Congo 38 t 2013 — volatile
57 Nigeria 28 t 2013 — volatile
58 Botswana 24 t 2013 down 33.3% volatile
58 Ethiopia 24 t 2013 up 100.0% volatile
58 Jordan 24 t 2013 down 33.3% volatile
61 Estonia 23 t 2013 down 99.1% volatile
61 Lebanon 23 t 2013 up 27.8% volatile
63 Sweden 22 t 2013 down 62.7% volatile
64 Finland 18 t 2013 down 96.3% volatile
64 Serbia 18 t 2013 down 81.4% volatile
64 Slovakia 18 t 2013 down 98.6% volatile
67 New Zealand 15 t 2013 — volatile
68 Oman 14 t 2013 unchanged volatile
69 Ireland 13 t 2013 down 31.6% volatile
70 Jamaica 12 t 2013 — volatile
71 Algeria 11 t 2013 down 47.6% volatile
71 Gabon 11 t 2013 — volatile
73 Norway 10 t 2013 down 9.1% volatile
74 Iceland 9 t 2013 up 50.0% volatile
74 Sri Lanka 9 t 2013 up 50.0% volatile
74 Nepal 9 t 2013 down 97.4% volatile
77 Peru 8 t 2013 down 20.0% volatile
78 Zambia 7 t 2013 — volatile
79 Croatia 6 t 2013 down 85.4% volatile
79 New Caledonia 6 t 2013 — volatile
81 Cameroon 4 t 2013 — volatile
82 Albania 3 t 2013 up 200.0% volatile
82 Bosnia and Herzegovina 3 t 2013 down 72.7% volatile
82 Mexico 3 t 2013 down 95.2% volatile
82 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 50.0% 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 — Other uses by country. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 25 August 2026, from https://agriculture.statizoid.com/stat/soft-fibres-other-other-uses-non-food/

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About this data

Indicator
Soft-Fibres, Other — Other uses (non-food)
Unit
t
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
178 places, 8,520 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.