Net food imports by crop - Barley, gaps filled by country
Net food imports by crop - Barley with 67 missing years estimated by linear interpolation between the nearest real observations. Only gaps of 4 years or fewer are filled, and never beyond the first or last actual measurement — these are filled holes, not forecasts.
Countries reporting
157
Highest
5.96 million
China
Lowest
-7.08 million
France
Median
95
Years covered
59
1961–2019
Data points
6,843
What the numbers show
Net food imports by crop - Barley, gaps filled is currently reported for 157 countries. The highest value is 5.96 million in China; the lowest is -7.08 million in France.
The median across all reporting countries is 95, and the mean is -21,196.
Over the past decade 70 countries rose and 69 fell. The largest increase was in Ethiopia (up 62,672.0%), and the largest decrease in Bolivia (down 2,190,300.0%).
Net food imports by crop - Barley, gaps filled: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 5.96 million | 2019 | up 233.6% | volatile |
| 2 | Saudi Arabia | 3.91 million | 2019 | down 34.5% | volatile |
| 3 | Iran | 3.29 million | 2019 | up 174.6% | volatile |
| 4 | Netherlands | 2.06 million | 2019 | up 43.8% | volatile |
| 5 | Belgium | 1.80 million | 2019 | up 23.3% | rising |
| 6 | Japan | 1.15 million | 2019 | down 17.5% | rising |
| 7 | Spain | 1.07 million | 2019 | down 28.8% | volatile |
| 8 | Jordan | 853,459 | 2019 | up 62.4% | volatile |
| 9 | Brazil | 671,336 | 2019 | up 47.3% | volatile |
| 10 | Libya | 565,549 | 2019 | down 19.7% | volatile |
| 11 | Tunisia | 542,347 | 2019 | up 727.0% | volatile |
| 12 | Turkey | 521,589 | 2019 | up 348.8% | volatile |
| 13 | Italy | 492,998 | 2019 | down 23.0% | falling |
| 14 | Morocco | 382,072 | 2019 | up 40.5% | volatile |
| 15 | Thailand | 360,713 | 2019 | up 3,488.1% | volatile |
| 16 | Kuwait | 330,398 | 2019 | up 25.1% | volatile |
| 17 | Portugal | 321,628 | 2019 | down 21.7% | volatile |
| 18 | Colombia | 316,592 | 2019 | up 53.4% | rising |
| 19 | Israel | 260,755 | 2019 | down 35.7% | volatile |
| 20 | India | 254,508 | 2019 | up 600.6% | volatile |
| 21 | Belarus | 224,763 | 2019 | up 8,508.3% | volatile |
| 22 | Qatar | 211,087 | 2018 | up 47.4% | volatile |
| 23 | United Arab Emirates | 197,824 | 2019 | up 8.3% | volatile |
| 24 | Oman | 180,662 | 2019 | up 773.8% | volatile |
| 25 | Austria | 173,320 | 2019 | up 61.1% | volatile |
| 26 | Cyprus | 133,575 | 2019 | down 51.7% | volatile |
| 27 | Poland | 132,033 | 2019 | up 58.8% | volatile |
| 28 | Algeria | 122,297 | 2019 | up 16.1% | volatile |
| 29 | Peru | 121,772 | 2019 | up 24.8% | volatile |
| 30 | Vietnam | 121,263 | 2019 | up 144.3% | volatile |
| 31 | Lebanon | 105,279 | 2019 | up 49.9% | volatile |
| 32 | Greece | 92,505 | 2019 | down 42.7% | volatile |
| 33 | Mexico | 87,956 | 2019 | up 8.8% | volatile |
| 34 | Ireland | 85,514 | 2019 | down 57.8% | volatile |
| 35 | South Korea | 67,625 | 2019 | up 158.0% | volatile |
| 36 | Chile | 52,120 | 2019 | down 23.7% | volatile |
| 37 | Palestine | 50,000 | 2019 | down 35.1% | falling |
| 38 | Switzerland | 48,751 | 2019 | up 58.8% | volatile |
| 39 | Slovakia | 46,804 | 2019 | up 198.0% | volatile |
| 40 | Iraq | 45,475 | 2019 | up 23,183.8% | volatile |
| 41 | Norway | 45,020 | 2019 | up 838.7% | volatile |
| 42 | Ecuador | 44,473 | 2019 | up 23.9% | volatile |
| 43 | Taiwan | 31,189 | 2019 | down 50.0% | volatile |
| 44 | Bosnia and Herzegovina | 28,567 | 2019 | up 27.8% | rising |
| 45 | Uganda | 24,843 | 2019 | up 1,792.1% | volatile |
| 46 | United States | 23,346 | 2019 | down 93.4% | volatile |
| 47 | Armenia | 23,322 | 2019 | up 440.9% | volatile |
| 48 | Ethiopia | 15,643 | 2019 | up 62,672.0% | volatile |
| 49 | Venezuela | 14,676 | 2015 | — | volatile |
| 50 | Iceland | 12,654 | 2019 | up 31.0% | rising |
| 51 | Djibouti | 11,529 | 2016 | up 193.7% | volatile |
| 52 | Slovenia | 9,980 | 2019 | down 51.2% | volatile |
| 53 | South Africa | 9,926 | 2019 | down 60.6% | volatile |
| 54 | Pakistan | 8,478 | 2019 | up 90.9% | volatile |
| 55 | Afghanistan | 8,442 | 2019 | down 62.5% | volatile |
| 56 | Malta | 8,277 | 2019 | down 66.3% | volatile |
| 57 | Philippines | 6,141 | 2019 | up 153.2% | volatile |
| 58 | Albania | 6,040 | 2019 | up 487.5% | volatile |
| 59 | Egypt | 5,495 | 2019 | up 200.2% | volatile |
| 60 | New Zealand | 5,414 | 2019 | up 25,881.0% | volatile |
| 61 | Malaysia | 5,207 | 2019 | up 28.7% | volatile |
| 62 | North Macedonia | 4,353 | 2019 | up 7,036.1% | volatile |
| 63 | Tajikistan | 3,200 | 2019 | down 42.4% | volatile |
| 64 | Nigeria | 2,466 | 2019 | up 331.1% | volatile |
| 65 | Bahrain | 1,702 | 2019 | up 192.4% | volatile |
| 66 | New Caledonia | 1,404 | 2018 | up 1,176.4% | volatile |
| 67 | Montenegro | 1,391 | 2019 | up 135.4% | rising |
| 68 | Nepal | 790 | 2019 | up 15,700.0% | volatile |
| 69 | Papua New Guinea | 499 | 2019 | — | volatile |
| 70 | Kyrgyzstan | 307 | 2019 | down 95.1% | volatile |
| 71 | Cameroon | 221 | 2017 | down 94.2% | volatile |
| 72 | Guatemala | 203 | 2019 | up 6,866.7% | volatile |
| 73 | Bangladesh | 202 | 2019 | — | volatile |
| 74 | Singapore | 196 | 2019 | down 55.0% | volatile |
| 75 | Rwanda | 189 | 2019 | up 800.0% | volatile |
| 76 | Myanmar | 183 | 2019 | down 92.7% | volatile |
| 77 | Namibia | 148 | 2019 | — | volatile |
| 78 | Mozambique | 96 | 2019 | up 100.6% | volatile |
| 79 | French Polynesia | 95 | 2018 | down 46.6% | volatile |
| 80 | Hong Kong | 47 | 2019 | up 27.0% | volatile |
| 81 | Barbados | 29 | 2019 | unchanged | volatile |
| 82 | Guyana | 21 | 2019 | up 162.5% | volatile |
| 83 | Sri Lanka | 7 | 2019 | down 63.2% | volatile |
| 84 | Indonesia | 4 | 2019 | down 84.6% | volatile |
| 85 | Macao | 3 | 2018 | down 86.4% | volatile |
| 86 | Cape Verde | 1 | 2017 | — | volatile |
| 86 | Fiji | 1 | 2019 | up 200.0% | volatile |
| 86 | Somalia | 1 | 2019 | up 104.0% | volatile |
| 86 | Seychelles | 1 | 2018 | up 150.0% | volatile |
| 90 | Bahamas | 0 | 2019 | up 100.0% | volatile |
| 90 | Dominica | 0 | 2013 | — | volatile |
| 90 | Eritrea | 0 | 2013 | up 100.0% | volatile |
| 90 | Saint Lucia | 0 | 2019 | — | volatile |
| 90 | North Korea | 0 | 2017 | down 100.0% | volatile |
| 90 | Vanuatu | 0 | 2013 | — | volatile |
| 97 | Guinea-Bissau | -1 | 2019 | — | volatile |
| 98 | Bhutan | -5 | 2019 | down 200.0% | volatile |
| 99 | Costa Rica | -7 | 2019 | down 170.0% | volatile |
| 100 | South Sudan | -23 | 2015 | — | volatile |
| 101 | Dominican Republic | -35 | 2018 | down 100.9% | volatile |
| 102 | Saint Kitts and Nevis | -45 | 2019 | — | volatile |
| 103 | Mauritius | -50 | 2019 | down 13.6% | volatile |
| 104 | Brunei | -91 | 2019 | down 4,650.0% | volatile |
| 105 | Angola | -136 | 2019 | — | volatile |
| 106 | Jamaica | -188 | 2019 | down 1,466.7% | volatile |
| 107 | Lesotho | -199 | 2019 | down 1,047.6% | volatile |
| 108 | Ghana | -256 | 2019 | down 296.9% | volatile |
| 109 | Sao Tome and Principe | -350 | 2014 | down 34,900.0% | volatile |
| 110 | Eswatini | -424 | 2018 | — | volatile |
| 111 | Togo | -516 | 2013 | up 64.8% | volatile |
| 112 | Trinidad and Tobago | -560 | 2019 | — | volatile |
| 113 | Botswana | -571 | 2019 | down 19,133.3% | volatile |
| 114 | Honduras | -624 | 2019 | — | volatile |
| 115 | Madagascar | -652 | 2017 | up 39.1% | rising |
| 115 | Saint Vincent and the Grenadines | -652 | 2019 | up 80.2% | volatile |
| 117 | El Salvador | -1,375 | 2019 | up 43.6% | volatile |
| 118 | Panama | -1,416 | 2019 | down 20,128.6% | volatile |
| 119 | Cambodia | -1,867 | 2019 | down 46,775.0% | volatile |
| 120 | Malawi | -1,953 | 2019 | down 13,120.0% | volatile |
| 121 | Azerbaijan | -1,961 | 2019 | down 122.6% | volatile |
| 122 | Senegal | -2,261 | 2018 | down 99.6% | volatile |
| 123 | Democratic Republic of Congo | -3,645 | 2019 | up 96.0% | volatile |
| 124 | Georgia | -3,879 | 2019 | down 345.8% | volatile |
| 125 | Nicaragua | -4,374 | 2019 | — | volatile |
| 126 | Luxembourg | -8,379 | 2019 | up 20.6% | falling |
| 127 | Cote d'Ivoire | -13,815 | 2019 | down 978.5% | volatile |
| 128 | Bolivia | -21,904 | 2016 | down 2,190,300.0% | volatile |
| 129 | Kenya | -23,879 | 2019 | down 218.5% | volatile |
| 130 | Sudan | -24,433 | 2017 | — | volatile |
| 131 | Croatia | -26,738 | 2019 | down 290.3% | volatile |
| 132 | Uzbekistan | -32,460 | 2019 | down 170.7% | volatile |
| 133 | Syria | -36,563 | 2019 | down 106.2% | volatile |
| 134 | Serbia | -42,488 | 2019 | down 206.8% | volatile |
| 135 | Uruguay | -44,223 | 2019 | down 429.2% | volatile |
| 136 | Moldova | -53,082 | 2019 | up 64.8% | volatile |
| 137 | Czechia | -102,693 | 2019 | up 60.1% | volatile |
| 138 | Sweden | -110,683 | 2019 | up 36.3% | volatile |
| 139 | Finland | -132,591 | 2019 | down 102.6% | volatile |
| 140 | Latvia | -175,215 | 2019 | down 90.5% | volatile |
| 141 | Laos | -179,567 | 2019 | down 223.7% | volatile |
| 142 | Tanzania | -191,837 | 2018 | down 833,974.0% | volatile |
| 143 | Lithuania | -248,870 | 2019 | down 36.0% | volatile |
| 144 | Bulgaria | -265,577 | 2019 | up 36.1% | volatile |
| 145 | Germany | -312,491 | 2019 | down 1,742.4% | volatile |
| 146 | Estonia | -347,814 | 2019 | down 458.4% | volatile |
| 147 | Hungary | -399,553 | 2019 | down 109.7% | volatile |
| 148 | Denmark | -418,662 | 2019 | down 215.3% | volatile |
| 149 | Romania | -975,471 | 2019 | down 96.6% | volatile |
| 150 | Kazakhstan | -1.60 million | 2019 | down 456.5% | volatile |
| 151 | United Kingdom | -1.61 million | 2019 | down 117.8% | volatile |
| 152 | Canada | -2.14 million | 2019 | down 39.5% | volatile |
| 153 | Ukraine | -2.34 million | 2019 | up 57.4% | volatile |
| 154 | Argentina | -2.51 million | 2019 | down 147.6% | volatile |
| 155 | Paraguay | -2.83 million | 2013 | down 251.0% | volatile |
| 156 | Australia | -2.87 million | 2019 | up 11.6% | volatile |
| 157 | Russia | -3.91 million | 2019 | down 13.0% | volatile |
| 158 | France | -7.08 million | 2019 | down 50.8% | falling |
How this figure is calculated
Net food imports by crop - Barley with 67 missing years estimated by linear interpolation between the nearest real observations. Only gaps of 4 years or fewer are filled, and never beyond the first or last actual measurement — these are filled holes, not forecasts.
Computed from
- Net food imports by crop - Barley FAOSTAT. Available at: http://www.fao.org/faostat/en/#data
Statizoid computes this series; the underlying measurements belong to the publishers named above. The arithmetic is applied to every country and year where both inputs report, and nothing is estimated unless the page says so.
About this data
Net food imports by crop - Barley with 67 missing years estimated by linear interpolation between the nearest real observations. Only gaps of 4 years or fewer are filled, and never beyond the first or last actual measurement — these are filled holes, not forecasts.