IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v15y2025i2p121-d1562082.html

A New Path to Aggregate Area Expansion by Agricultural Mechanization: The Seedling Field Saving Effect of Machinery Rice Transplanting and the Case of China

Author

Listed:
  • Dongyan Ruan

    (College of Law and Economics, Wuhan University of Science and Technology, Wuhan 430065, China)

  • Jinqi Tang

    (College of Economics and Management, Huazhong Agricultural University, Wuhan 430070, China)

  • Juan Wang

    (China Grain Research and Training Center, Beijing 100834, China)

  • Jing Zhou

    (College of Economics and Management, Huazhong Agricultural University, Wuhan 430070, China)

  • Xiaoyong Zeng

    (Agricultural Technology Extension Center of Taihe County, Ji’an 343799, China)

  • Hanjie Liu

    (Agricultural Technology Extension Center of Taihe County, Ji’an 343799, China)

Abstract

Aggregate area expansion is one of the important productivity impacts of agricultural mechanization. This study aims to explore potential new paths to aggregate area expansion through new forms of agricultural mechanization and estimate the relevant effects. Targeting the rapidly developing machinery rice transplanting (MRT) and the attendant centralized rice seedling cultivation (CRSC) in rural China, this article identifies a fresh path for the adoption of machinery technology to increase aggregate crop cultivation area. By analyzing two typical cases from Jiangxi Province, we unmask the mechanism through which MRT and CRSC promote aggregate area. The results indicate that, compared with the traditional method, CRSC makes technological progress in various aspects and significantly improves the supply efficiency of seedlings and the space utilization efficiency of seedling fields. This, in turn, reduces the required seedling area per unit of paddy field and thus substitutes a lot of traditional seedling fields with few modern ones. Under the rotation cropping system, CRSC releases the farming time of the potential previous crops in the saved traditional seedling fields and then increases cropping intensity and aggregate area. In the micro case, the substitution of the traditional method with CRSC can save 0.04 hectares of seedling field by serving 1 hectare of paddy field. The macro simulation results show that CRSC can, at most, increase aggregate crop cultivation area by 1.95 million hectares nationwide, and this is equivalent to an increase of 6.21 million tons of grain and 1.86 million tons of rapeseed.

Suggested Citation

  • Dongyan Ruan & Jinqi Tang & Juan Wang & Jing Zhou & Xiaoyong Zeng & Hanjie Liu, 2025. "A New Path to Aggregate Area Expansion by Agricultural Mechanization: The Seedling Field Saving Effect of Machinery Rice Transplanting and the Case of China," Agriculture, MDPI, vol. 15(2), pages 1-18, January.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:2:p:121-:d:1562082
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/15/2/121/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/15/2/121/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Olmstead, Alan L. & Rhode, Paul W., 2001. "Reshaping The Landscape: The Impact And Diffusion Of The Tractor In American Agriculture, 1910–1960," The Journal of Economic History, Cambridge University Press, vol. 61(3), pages 663-698, September.
    2. Yiduo Sun & Ruifa Hu & Chao Zhang, 2021. "Impact of Rural–Urban Migration Experience on Rice Farmers’ Agricultural Machinery Expenditure: Evidence from China," Agriculture, MDPI, vol. 11(8), pages 1-15, August.
    3. Wanglin Ma & Alan Renwick & Quentin Grafton, 2018. "Farm machinery use, off†farm employment and farm performance in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(2), pages 279-298, April.
    4. Weiwei Wang & Zhihai Yang & Xiangqun Gu & Amin Mugera & Ning Yin, 2024. "How Farm Machinery Rental Services and Off-Farm Work Affect Household Income in China," Agriculture, MDPI, vol. 14(10), pages 1-16, September.
    5. Ping Xue & Xinru Han & Yongchun Wang & Xiudong Wang, 2022. "Can Agricultural Machinery Harvesting Services Reduce Cropland Abandonment? Evidence from Rural China," Agriculture, MDPI, vol. 12(7), pages 1-15, June.
    6. Hans P. Binswanger & Sudhir K. Singh, 2018. "Wages, Prices and Agriculture: How Can Indian Agriculture Cope with Rising Wages?," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(2), pages 281-305, June.
    7. Siyu Yang & Wei Li, 2023. "The Impact of Socialized Agricultural Machinery Services on the Labor Transfer of Maize Growers," Agriculture, MDPI, vol. 13(6), pages 1-21, June.
    8. Pedro Bento & Diego Restuccia, 2017. "Misallocation, Establishment Size, and Productivity," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(3), pages 267-303, July.
    9. Chaoran Chen & Diego Restuccia & Raül Santaeulàlia-Llopis, 2023. "Land Misallocation and Productivity," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(2), pages 441-465, April.
    10. Chen, Shuo & Lan, Xiaohuan, 2020. "Tractor vs. animal: Rural reforms and technology adoption in China," Journal of Development Economics, Elsevier, vol. 147(C).
    11. Ma, Wanglin & Renwick, Alan & Grafton, Quentin, 2018. "Farm machinery use, off-farm employment and farm performance in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(2), April.
    12. Xiuhao Quan & Reiner Doluschitz, 2021. "Factors Influencing the Adoption of Agricultural Machinery by Chinese Maize Farmers," Agriculture, MDPI, vol. 11(11), pages 1-11, November.
    13. Meili Huan & Fengxia Dong & Liang Chi, 2022. "Mechanization services, factor allocation, and farm efficiency: Evidence from China," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1618-1639, August.
    14. Zhoufu Yan & Shurui Zhang & Fangwei Wu & Binlei Gong, 2023. "Increasing Wages, Factor Substitution, and Cropping Pattern Changes in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 31(5), pages 190-214, September.
    15. Robert Evenson & Prabhu Pingali (ed.), 2007. "Handbook of Agricultural Economics," Handbook of Agricultural Economics, Elsevier, edition 1, volume 3, number 1.
    16. Manolis Manioudis & Giorgos Meramveliotakis, 2022. "Broad strokes towards a grand theory in the analysis of sustainable development: a return to the classical political economy," New Political Economy, Taylor & Francis Journals, vol. 27(5), pages 866-878, September.
    17. Idelphonse O. Saliou & Afio Zannou & Augustin K. N. Aoudji & Albert N. Honlonkou, 2020. "Drivers of Mechanization in Cotton Production in Benin, West Africa," Agriculture, MDPI, vol. 10(11), pages 1-13, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiang Li & Xiaoqin Guo, 2023. "Can Policy Promote Agricultural Service Outsourcing? Quasi-Natural Experimental Evidence from China," Sustainability, MDPI, vol. 15(2), pages 1-18, January.
    2. Ziqi Zhang & Jingyi Ding & Kuan Zhang & Xin Deng, 2025. "Impact of Aging on Farmland Abandonment: Evidence from Rural China," Land, MDPI, vol. 14(2), pages 1-27, February.
    3. Qian, Long & Lu, Hua & Gao, Qiang & Lu, Hualiang, 2022. "Household-owned farm machinery vs. outsourced machinery services: The impact of agricultural mechanization on the land leasing behavior of relatively large-scale farmers in China," Land Use Policy, Elsevier, vol. 115(C).
    4. Ma, Wanglin & Zhou, Xiaoshi & Boansi, David & Horlu, Godwin Seyram Agbemavor & Owusu, Victor, 2024. "Adoption and intensity of agricultural mechanization and their impact on non-farm employment of rural women," World Development, Elsevier, vol. 173(C).
    5. Zhou, Xiaoshi & Ma, Wanglin, 2021. "Effects of Agricultural Mechanization on Land Productivity: Evidence from China," 2021 Conference, August 17-31, 2021, Virtual 315143, International Association of Agricultural Economists.
    6. Marijn Bolhuis & Swapnika Rachapalli & Diego Restuccia, 2026. "Misallocation in Indian Agriculture," American Economic Journal: Macroeconomics, American Economic Association, vol. 18(2), pages 378-408, April.
    7. Hang Thi Thuy Nguyen & Thi Quynh Anh Le & Pham Xuan Hung & Nguyen Thai Phan, 2026. "Non-farm employment and agricultural mechanisation adoption: A reciprocal relationship," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 72(1), pages 37-55.
    8. Bhattarai, Madhusudan & Joshi, Pramod Kumar & Shekhawa, R. S. & Takeshima, Hiroyuki, 2017. "The evolution of tractorization in India’s low-wage economy: Key patterns and implications," IFPRI discussion papers 1675, International Food Policy Research Institute (IFPRI).
    9. Britos, Braulio & Hernandez, Manuel A. & Robles, Miguel & Trupkin, Danilo R., 2022. "Land market distortions and aggregate agricultural productivity: Evidence from Guatemala," Journal of Development Economics, Elsevier, vol. 155(C).
    10. Ping Xue & Xinru Han & Yongchun Wang & Xiudong Wang, 2022. "Can Agricultural Machinery Harvesting Services Reduce Cropland Abandonment? Evidence from Rural China," Agriculture, MDPI, vol. 12(7), pages 1-15, June.
    11. Xiuhao Quan & Reiner Doluschitz, 2021. "Factors Influencing the Adoption of Agricultural Machinery by Chinese Maize Farmers," Agriculture, MDPI, vol. 11(11), pages 1-11, November.
    12. Xin Ma & Tao Huang, 2023. "China's Rural Industrialization and Agricultural Mechanization," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 31(3), pages 27-58, May.
    13. repec:ags:aaea22:335478 is not listed on IDEAS
    14. Xin Deng & Zhongcheng Yan & Dingde Xu & Yanbin Qi, 2020. "Land Registration, Adjustment Experience, and Agricultural Machinery Adoption: Empirical Analysis from Rural China," Land, MDPI, vol. 9(3), pages 1-14, March.
    15. Lei Niu & Lulu Yuan & Zhongmin Ding & Yifu Zhao, 2023. "How Do Support Pressure and Urban Housing Purchase Affect the Homecoming Decisions of Rural Migrant Workers? Evidence from Rural China," Agriculture, MDPI, vol. 13(8), pages 1-28, July.
    16. Zheng, Linyi, 2023. "Impact of off-farm employment on cooking fuel choices: Implications for rural-urban transformation in advancing sustainable energy transformation," Energy Economics, Elsevier, vol. 118(C).
    17. Hernandez, M. & Britos, B. & Robles, M. & Trupkin, D., 2018. "Land market distortions: Theory and evidence from Guatemala," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277031, International Association of Agricultural Economists.
    18. Bouchakour, Radhia & Saad, Mohammed, . "Farm and farmer characteristics and off-farm work: evidence from Algeria," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(2).
    19. Su, Min & Heerink, Nico & Oosterveer, Peter & Feng, Shuyi, 2025. "Land leasing-in, farm machinery, and pesticide use: A plot-analysis for Jiangsu Province, China," Economic Analysis and Policy, Elsevier, vol. 87(C), pages 2470-2487.
    20. Qian Chang & Congying Zhang & Hsiaoping Chien & Wenchao Wu & Minjuan Zhao, 2024. "Impact of outsourcing agricultural production on the frequency and intensity of agrochemical inputs: evidence from a field survey of 1211 farmers in major food-producing areas in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(4), pages 9577-9602, April.
    21. Xin Deng & Miao Zeng & Dingde Xu & Yanbin Qi, 2022. "Why do landslides impact farmland abandonment? Evidence from hilly and mountainous areas of rural China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(1), pages 699-718, August.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:15:y:2025:i:2:p:121-:d:1562082. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.