Submitted:
09 May 2023
Posted:
10 May 2023
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Methods and Materials
2.1. Methods
2.1.1. Supply security
2.1.2. Science and technology equipment
2.1.3. Operation system
2.1.4. Industrial resilience
2.1.5. Competitiveness
2.2. Materials
3. Results and Discussion
3.1. Results
3.2. Discussion
4. Issues and challenges of China’s livestock powerhouse construction
4.1. Supply security capacity needs to be strengthened

4.2. Scientific and technological support needs to be improved
| Country | Pig | Beef cattle | Sheep and goat | Broiler | Layeryield | Milk yield | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| Slaughterrate | Carcassweight | Slaughterrate | Carcassweight | Slaughterrate | Carcassweight | Slaughterrate | Carcassweight | |||
| Australia | 212.97 | 78.74 | 27.10 | 291.88 | 37.87 | 24.69 | 608.94 | 1.92 | 16.01 | 6400.40 |
| Brazil | 124.70 | 82.29 | 12.34 | 351.92 | 30.09 | 14.46 | 400.96 | 2.43 | 12.30 | 2280.70 |
| Canada | 166.99 | 102.63 | 30.01 | 417.46 | 94.06 | 22.99 | 439.12 | 1.89 | 17.72 | 9646.70 |
| China | 133.56 | 88.27 | 77.98 | 148.19 | 110.99 | 14.49 | 252.04 | 1.55 | 10.69 | 3026.90 |
| France | 180.15 | 94.53 | 25.73 | 319.48 | 57.87 | 18.14 | 305.50 | 1.89 | - | 7458.90 |
| Germany | 218.31 | 95.83 | 29.60 | 330.61 | 99.05 | 20.41 | - | - | 19.70 | 8481.40 |
| India | 103.64 | 35.00 | 21.08 | 103.00 | 34.88 | 10.59 | 328.87 | 1.34 | 11.98 | 1880.20 |
| Japan | 181.24 | 78.29 | 26.82 | 450.00 | 30.31 | 26.20 | 261.72 | 2.88 | 18.30 | 8939.20 |
| New Zealand | 254.74 | 70.89 | 46.27 | 159.81 | 87.20 | 20.24 | 458.88 | 1.91 | 15.96 | 4555.30 |
| Korea | 163.89 | 76.54 | 24.18 | 321.24 | 39.24 | 15.45 | 583.80 | 0.94 | 10.09 | 10374.30 |
| Russia | 179.23 | 92.90 | 43.43 | 213.75 | 55.13 | 18.04 | 484.88 | 1.89 | 16.70 | 5016.70 |
| United States | 174.06 | 97.32 | 36.64 | 370.59 | 38.08 | 24.92 | 597.13 | 2.43 | 17.08 | 10869.00 |
| Type | 2010 | 2015 | 2020 | 2021 | Average annual growth rate (%) | |
|---|---|---|---|---|---|---|
| Pig (CNY/head) |
Total output | 1341.01 | 1827.19 | 4146.29 | 2586.49 | 6.15 |
| Total Cost | 1250.20 | 1835.35 | 2913.65 | 2709.18 | 7.28 | |
| Feed cost | 696.90 | 870.08 | 960.55 | 1112.67 | 4.35 | |
| Labor Cost | 238.98 | 510.82 | 537.99 | 512.82 | 7.19 | |
| Beef cattle (CNY/head) |
Total output | 6014.92 | 10663.30 | 16713.20 | 17498.70 | 10.19 |
| Total Cost | 4983.38 | 8550.67 | 12641.30 | 13799.30 | 9.70 | |
| Feed cost | 1291.16 | 1709.56 | 2526.98 | 2965.52 | 7.85 | |
| Labor cost | 440.66 | 1010.52 | 1147.56 | 1175.52 | 9.33 | |
| Sheep and goat (CNY/head) |
Total output | 775.41 | 936.08 | 1573.63 | 1614.86 | 6.90 |
| Total Cost | 639.67 | 1002.11 | 1367.84 | 1418.25 | 7.51 | |
| Feed cost | 164.02 | 201.87 | 241.94 | 270.24 | 4.64 | |
| Labor cost | 196.27 | 422.32 | 495.04 | 530.60 | 9.46 | |
| Broiler (CNY/hundred) |
Total output | 2489.48 | 2627.07 | 2753.70 | 3061.84 | 1.90 |
| Total Cost | 2219.53 | 2700.31 | 2902.79 | 3164.02 | 3.28 | |
| Feed cost | 1615.85 | 1911.85 | 1916.43 | 2194.70 | 2.82 | |
| Labor cost | 179.80 | 354.20 | 414.16 | 409.20 | 7.76 | |
| Layer (CNY/hundred) |
Total output | 13772.50 | 15617.00 | 13980.70 | 17955.40 | 2.44 |
| Total Cost | 12871.90 | 14643.80 | 15865.10 | 17655.80 | 2.91 | |
| Feed cost | 9558.24 | 10082.83 | 10732.30 | 12412.90 | 2.40 | |
| Labor cost | 731.92 | 1599.62 | 1855.82 | 1802.76 | 8.54 | |
| Dairy cattle (CNY/head) |
Total output | 16361.70 | 21337.70 | 24609.60 | 26217.30 | 4.38 |
| Total Cost | 12190.90 | 16331.20 | 17300.20 | 18462.00 | 3.85 | |
| Feed cost | 8516.76 | 10165.34 | 10258.62 | 11327.12 | 2.63 | |
| Labor Cost | 1651.84 | 3695.35 | 4200.20 | 4186.45 | 8.82 | |
4.3. Modern operation system needed to be sound

| Enterprise | 2018 | 2019 | 2020 | 2021 | 2022 |
|---|---|---|---|---|---|
| Muyuan Foods Co., Ltd. | 1101 | 1025 | 1812 | 4026 | 6120 |
| Wens Foodstuff Group Co., Ltd. | 2230 | 1852 | 955 | 1322 | 1791 |
| New Hope Group | 255 | 355 | 829 | 998 | 1461 |
| Zhengbang Group | 554 | 578 | 955 | 1493 | 845 |
| Aonong Group | 42 | 66 | 135 | 325 | 519 |
| Da Bei Nong Group | 168 | 164 | 185 | 431 | 443 |
| Tech-bank Food Co., Ltd. | 217 | 244 | 308 | 428 | 442 |
| COFCO Joycome Foods Limited | 255 | 199 | 205 | 343 | 410 |
| Tangrenshen Group Co., Ltd. | 68 | 84 | 102 | 154 | 216 |
| Tecon Biology Co., Ltd. | 65 | 84 | 135 | 160 | 203 |
| Total | 4955 | 4651 | 5621 | 9680 | 12450 |
| National | 69382 | 54419 | 52704 | 67128 | 69995 |
| Percentage of | 7.14 | 8.55 | 10.67 | 14.42 | 17.79 |
4.4. The industry chain and supply chain were not highly resilient
| Year | China | United States | ||||||
|---|---|---|---|---|---|---|---|---|
| New outbreaks | Cases | Killed and disposed | Deaths | New outbreaks | Cases | Killed and disposed | Deaths | |
| 2010 | 20434 | 496.56 | 18.36 | 70.08 | 53 | 0.07 | 0.13 | 0.00 |
| 2011 | 30466 | 417.93 | 31.35 | 43.56 | 40 | 0.03 | 1.55 | 0.00 |
| 2012 | 24107 | 269.08 | 184.50 | 32.05 | 50 | 0.09 | 0.02 | 0.00 |
| 2013 | 24884 | 267.04 | 61.17 | 33.27 | 55 | 0.68 | 1.06 | 0.00 |
| 2014 | 22640 | 265.21 | 217.17 | 22.54 | 454 | 0.07 | 11.65 | 0.01 |
| 2015 | 27142 | 293.35 | 62.34 | 34.97 | 253 | 2.53 | 1607.14 | 5.92 |
| 2016 | 23266 | 281.64 | 100.21 | 48.78 | 25 | 0.07 | 23.67 | 0.10 |
| 2017 | 8381 | 100.82 | 77.23 | 28.96 | 25 | 0.06 | 19.59 | 0.07 |
| 2018 | 8560 | 85.91 | 63.65 | 20.52 | 35 | 0.06 | 22.19 | 0.02 |
| 2019 | 3946 | 31.84 | 20.27 | 5.30 | 52 | 0.09 | 171.46 | 0.02 |
| 2020 | 124 | 0.90 | 1.76 | 0.87 | 245 | 0.09 | 33.95 | 2.22 |
| 2021 | 120 | 0.59 | 0.43 | 0.58 | 82 | 0.04 | 0.04 | 0.03 |
| 2022 | 18 | 0.03 | 0.06 | 0.03 | 994 | 0.02 | 5691.43 | 144.44 |
4.5. International trade risks were increasing

4.6. Policy support system needed to be improved
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
References
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| Indicators | Unit | Calculation method | |
|---|---|---|---|
| Supply security | Global share | % | Domestic livestock production/Global livestock production |
| Per capita possession | kg | Livestock production/Total population | |
| Self-sufficiency rate | % | Livestock domestic production/(Domestic production + Net imports) | |
| Scientific and technological support | Slaughter rate | % | Slaughter/Inventory |
| Carcass weight (yield) | kg/head | Livestock production/Slaughter (livestock production/Inventory) | |
| Agricultural labor productivity | USD/person | Value added in agriculture/Employment in agriculture | |
| Industrial resilience | Comparative benefits | - | Producer price of livestock products/Producer price of feed grain |
| Resource carrying capacity | Head/ha | Livestock inventory/Agricultural land | |
| Feed grain self-sufficiency rate | % | Domestic production of feed grain/(Domestic production + Net imports) | |
| International trade | International market share | % | Domestic exports of livestock products/World exports of livestock products |
| Trade competitiveness index | - | (Exports of livestock products - Imports of livestock products)/(Exports of livestock products + Imports of livestock products) | |
| Revealed comparative advantage index | - | (Domestic exports of livestock products/World exports of livestock products)/(Domestic exports of agricultural products/World exports of agricultural products) | |
| Livestock | Pig | Beef cattle | Sheep and goat | Broiler | Layer | Dairy | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Country | Index | Country | Index | Country | Index | Country | Index | Country | Index | Country | Index | Country | Index |
| United States | 0.4521 | Spain | 0.6049 | United States | 0.4727 | New Zealand | 0.7489 | Brazil | 0.6646 | China | 0.5045 | New Zealand | 0.7619 |
| Brazil | 0.3556 | United States | 0.4431 | Brazil | 0.4703 | Australia | 0.5163 | United States | 0.5592 | United States | 0.4680 | United States | 0.3678 |
| New Zealand | 0.3439 | Netherlands | 0.4175 | Uruguay | 0.4320 | Ethiopia | 0.2048 | Poland | 0.4271 | Turkey | 0.4088 | India | 0.3210 |
| Netherlands | 0.2635 | Germany | 0.3964 | Australia | 0.4031 | Uruguay | 0.2002 | Hungary | 0.3137 | Panama | 0.2841 | Netherlands | 0.2938 |
| China | 0.2462 | Canada | 0.3430 | New Zealand | 0.3694 | China | 0.2002 | Belarus | 0.2998 | Malaysia | 0.2720 | Ireland | 0.2926 |
| Belarus | 0.2438 | China | 0.3396 | Paraguay | 0.3136 | Kenya | 0.1689 | Netherlands | 0.2983 | Belarus | 0.2479 | Belarus | 0.2901 |
| Poland | 0.2338 | Belgium | 0.3331 | Ireland | 0.3096 | North Macedonia | 0.1686 | China | 0.2730 | Germany | 0.2475 | Germany | 0.2653 |
| Argentina | 0.2138 | Brazil | 0.2758 | Argentina | 0.3011 | Pakistan | 0.1633 | Brunei | 0.2678 | Japan | 0.2412 | Luxembourg | 0.2356 |
| Australia | 0.2075 | Austria | 0.2463 | Nicaragua | 0.2764 | India | 0.1495 | Turkey | 0.2647 | India | 0.2239 | France | 0.2342 |
| India | 0.1969 | Ireland | 0.2202 | Canada | 0.2341 | Moldova | 0.1429 | Ukraine | 0.2575 | Portugal | 0.2164 | Argentina | 0.2223 |
| Germany | 0.1863 | Hungary | 0.2143 | Brunei | 0.2139 | Spain | 0.1398 | Argentina | 0.2551 | Ukraine | 0.1929 | Uruguay | 0.2119 |
| Canada | 0.1855 | Italy | 0.2087 | Netherlands | 0.2057 | Kazakhstan | 0.1377 | Thailand | 0.2439 | Brazil | 0.1833 | Belgium | 0.2102 |
| Turkey | 0.1855 | Chile | 0.1921 | Poland | 0.2047 | Greece | 0.1373 | Chile | 0.2236 | Brunei | 0.1832 | Poland | 0.2008 |
| Hungary | 0.1769 | France | 0.1913 | Belarus | 0.2028 | Kyrgyzstan | 0.1361 | Australia | 0.2057 | Argentina | 0.1829 | Australia | 0.1931 |
| Ukraine | 0.1690 | Russia | 0.1866 | Mexico | 0.1890 | Serbia | 0.1344 | New Zealand | 0.1901 | Morocco | 0.1825 | Czech Republic | 0.1855 |
| Spain | 0.1667 | Poland | 0.1851 | India | 0.1798 | Myanmar | 0.1290 | Russia | 0.1857 | Fiji | 0.1774 | Turkey | 0.1805 |
| France | 0.1608 | Belarus | 0.1591 | Pakistan | 0.1769 | Armenia | 0.1290 | Slovenia | 0.1852 | Thailand | 0.1744 | Kyrgyzstan | 0.1699 |
| Uruguay | 0.1602 | Korea | 0.1562 | Namibia | 0.1660 | Georgia | 0.1278 | France | 0.1612 | Pakistan | 0.1627 | Saudi Arabia | 0.1659 |
| Ireland | 0.1562 | Thailand | 0.1465 | Bolivia | 0.1535 | Argentina | 0.1182 | India | 0.1554 | Barbados | 0.1616 | Austria | 0.1649 |
| Paraguay | 0.1521 | Fiji | 0.1389 | South Africa | 0.1530 | South Africa | 0.1181 | Israel | 0.1516 | Bosnia and Herzegovina | 0.1512 | Slovenia | 0.1633 |
| Country | Livestock | Pig | Beef cattle | Sheep and goat | Broiler | Layer | Dairy |
|---|---|---|---|---|---|---|---|
| Australia | 0.2075 | 0.0863 | 0.4031 | 0.5163 | 0.2057 | 0.1118 | 0.1931 |
| Brazil | 0.3556 | 0.2758 | 0.4703 | 0.0339 | 0.6646 | 0.1833 | 0.1199 |
| Germany | 0.1863 | 0.3964 | 0.1264 | 0.0480 | - | 0.2475 | 0.2653 |
| Russia | 0.1443 | 0.1866 | 0.0837 | 0.0575 | 0.1857 | 0.1271 | 0.1206 |
| France | 0.1608 | 0.1913 | 0.1455 | 0.0926 | 0.1612 | - | 0.2342 |
| Korea | 0.0957 | 0.1562 | 0.0651 | 0.0198 | 0.0870 | 0.1152 | 0.0786 |
| Canada | 0.1855 | 0.3430 | 0.2341 | 0.0402 | 0.1387 | 0.1484 | 0.1302 |
| United States | 0.4521 | 0.4431 | 0.4727 | 0.0368 | 0.5592 | 0.4680 | 0.3678 |
| Japan | 0.1022 | 0.0714 | 0.0974 | 0.0210 | 0.0834 | 0.2412 | 0.0906 |
| New Zealand | 0.3439 | 0.0589 | 0.3694 | 0.7489 | 0.1901 | 0.1461 | 0.7619 |
| India | 0.1969 | 0.0964 | 0.1798 | 0.1495 | 0.1554 | 0.2239 | 0.3210 |
| China | 0.2462 | 0.3396 | 0.1174 | 0.2002 | 0.2730 | 0.5045 | 0.1011 |
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