Statizoid

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
145
Highest
140,737 t
China, mainland
Lowest
0 t
China, Macao SAR
Median
11 t
Years covered
53
1961–2013
Data points
8,414

What the numbers show

Soft-Fibres, Other — Import Quantity is currently reported for 145 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 t, and the mean is 3,401 t.

Over the past decade 28 countries rose and 59 fell. The largest increase was in Australia and New Zealand (up 13,550.0%), and the largest decrease in Barbados (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
4 France 18,064 t 2013 down 57.6% flat
5 Netherlands (Kingdom of the) 13,508 t 2013 up 186.4% volatile
6 Spain 10,115 t 2013 down 42.6% rising
7 Lithuania 9,834 t 2013 down 42.7% volatile
8 Czechia 9,467 t 2013 down 5.9% rising
9 USSR 8,400 t 1991 — volatile
10 Russian Federation 7,720 t 2013 down 16.5% 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
28 China, Taiwan Province of 305 t 2013 down 82.6% volatile
29 Denmark 304 t 2013 up 44.8% volatile
30 Australia and New Zealand 273 t 2013 up 13,550.0% volatile
31 Australia 258 t 2013 up 12,800.0% volatile
32 Belarus 234 t 2013 down 93.7% volatile
33 United Kingdom of Great Britain and Northern Ireland 213 t 2013 down 93.4% volatile
34 United Arab Emirates 195 t 2013 — volatile
35 Portugal 184 t 2013 up 27.8% volatile
36 Thailand 177 t 2013 up 45.1% volatile
37 Greece 154 t 2013 down 44.4% volatile
38 Ethiopia PDR 150 t 1992 — volatile
39 Ukraine 134 t 2013 — volatile
40 Saudi Arabia 122 t 2013 down 81.9% volatile
41 Philippines 90 t 2013 — volatile
42 Malaysia 87 t 2013 down 91.3% volatile
43 Austria 82 t 2013 down 98.2% falling
44 Morocco 78 t 2013 up 25.8% volatile
45 Serbia and Montenegro 70 t 2005 — volatile
46 Pakistan 68 t 2013 up 78.9% volatile
47 C�te d'Ivoire 67 t 2013 up 1,240.0% volatile
48 Argentina 62 t 2013 up 26.5% volatile
49 Israel 61 t 2013 up 60.5% volatile
49 Kazakhstan 61 t 2013 — volatile
51 Chile 56 t 2013 down 72.4% volatile
52 Iran (Islamic Republic of) 55 t 2013 — 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
71 Caribbean 12 t 2013 up 300.0% volatile
73 Algeria 11 t 2013 down 47.6% volatile
73 Gabon 11 t 2013 — volatile
75 Iceland 9 t 2013 up 50.0% volatile
75 Sri Lanka 9 t 2013 up 125.0% volatile
75 Nepal 9 t 2013 down 97.7% volatile
78 Bosnia and Herzegovina 8 t 2013 down 27.3% volatile
78 Peru 8 t 2013 down 20.0% volatile
80 Croatia 7 t 2013 down 82.9% volatile
80 Zambia 7 t 2013 — volatile
80 Republic of Moldova 7 t 2013 up 600.0% volatile
83 New Caledonia 6 t 2013 — volatile
83 Melanesia 6 t 2013 — volatile
85 Cameroon 4 t 2013 up 100.0% volatile
85 Venezuela (Bolivarian Republic of) 4 t 2013 — volatile
87 Albania 3 t 2013 up 200.0% volatile
87 Mexico 3 t 2013 down 96.6% volatile
87 North Macedonia 3 t 2013 unchanged volatile
87 Bolivia (Plurinational State of) 3 t 2013 up 200.0% volatile
91 Georgia 2 t 2013 — volatile
91 Kuwait 2 t 2013 — volatile
91 Luxembourg 2 t 2013 down 60.0% volatile
91 Niger 2 t 2013 — volatile
91 Rwanda 2 t 2013 — volatile
91 Senegal 2 t 2013 down 60.0% volatile
91 Uruguay 2 t 2013 down 84.6% volatile
98 Angola 1 t 2013 — volatile
98 Guatemala 1 t 2013 — volatile
98 Honduras 1 t 2013 unchanged volatile
98 Iraq 1 t 2013 — volatile
98 Madagascar 1 t 2013 — volatile
98 Mongolia 1 t 2013 down 88.9% volatile
98 Mozambique 1 t 2013 — volatile
98 Eswatini 1 t 2013 down 83.3% volatile
98 United Republic of Tanzania 1 t 2013 — volatile
107 Azerbaijan 0 t 2013 — volatile
107 Benin 0 t 2013 — volatile
107 Bangladesh 0 t 2013 — volatile
107 Barbados 0 t 2013 down 100.0% volatile
107 Colombia 0 t 2013 down 100.0% volatile
107 Costa Rica 0 t 2013 — volatile
107 Cyprus 0 t 2013 down 100.0% volatile
107 Djibouti 0 t 2013 — volatile
107 Dominican Republic 0 t 2013 — volatile
107 Ecuador 0 t 2013 — volatile
107 Fiji 0 t 2013 — volatile
107 Ghana 0 t 2013 down 100.0% volatile
107 Gambia 0 t 2013 down 100.0% volatile
107 Grenada 0 t 2013 — volatile
107 Guyana 0 t 2013 — volatile
107 Haiti 0 t 2013 — volatile
107 Kenya 0 t 2013 — volatile
107 Kyrgyzstan 0 t 2013 — volatile
107 Malta 0 t 2013 down 100.0% volatile
107 Myanmar 0 t 2013 — volatile
107 Mauritania 0 t 2013 — volatile
107 Mauritius 0 t 2013 — volatile
107 Namibia 0 t 2013 down 100.0% volatile
107 Nicaragua 0 t 2013 — volatile
107 Panama 0 t 2013 — volatile
107 Paraguay 0 t 2013 — volatile
107 French Polynesia 0 t 2013 — volatile
107 El Salvador 0 t 2013 down 100.0% volatile
107 Suriname 0 t 2013 — volatile
107 Togo 0 t 2013 — volatile
107 Turkmenistan 0 t 2013 — volatile
107 Trinidad and Tobago 0 t 2013 — volatile
107 Uganda 0 t 2013 — volatile
107 Yemen 0 t 2013 down 100.0% volatile
107 Zimbabwe 0 t 2013 — volatile
107 Polynesia 0 t 2013 — volatile
107 China, Hong Kong SAR 0 t 2013 down 100.0% volatile
107 Viet Nam 0 t 2013 down 100.0% volatile
107 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.

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.