IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v11y2021i6p480-d560753.html
   My bibliography  Save this article

Methodology of Analyzing Maize Density Loss in Smallholder’s Fields and Potential Optimize Approach

Author

Listed:
  • Zhichao An

    (National Academy of Agriculture Green Development, Department of Plant Nutrition, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China)

  • Chong Wang

    (National Academy of Agriculture Green Development, Department of Plant Nutrition, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China)

  • Xiaoqiang Jiao

    (National Academy of Agriculture Green Development, Department of Plant Nutrition, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China)

  • Zhongliang Kong

    (National Academy of Agriculture Green Development, Department of Plant Nutrition, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China)

  • Wei Jiang

    (National Academy of Agriculture Green Development, Department of Plant Nutrition, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China)

  • Dong Zhang

    (National Academy of Agriculture Green Development, Department of Plant Nutrition, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China)

  • Wenqi Ma

    (College of Resources and Environmental Science, Hebei Agricultural University, Baoding 071000, China)

  • Fusuo Zhang

    (National Academy of Agriculture Green Development, Department of Plant Nutrition, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China)

Abstract

Increasing plant density is a key measure to close the maize ( Zea mays L.) yield gap and ensure food security. However, there is a large plant density difference in the fields sown by agronomists and smallholders. The primary cause of this phenomenon is the lack of an effective methodology to systematically analyze the density loss. To identify the plant density loss processes from experimental plots to smallholder fields, a research methodology was developed in this study involving a farmer survey and measurements in a smallholder field. The results showed that the sowing density difference caused by farmer decision-making and plant density losses caused by mechanical and agronomic factors explained 15.5%, 5.5% and 6.8% of the plant density difference, respectively. Changing smallholder attitudes toward the value of increasing the plant density could help reduce this density loss and increase farm yields by 12.3%. Therefore, this methodology was effective for analyzing the plant density loss, and to clarify the primary causes of sowing density differences and plant density loss. Additionally, it was beneficial to identify the priorities and stakeholders who share responsibility for reducing the density loss. The methodology has wide applicability to address the sowing density differences and plant density loss in other areas to narrow crop yield gaps and ensure food security.

Suggested Citation

  • Zhichao An & Chong Wang & Xiaoqiang Jiao & Zhongliang Kong & Wei Jiang & Dong Zhang & Wenqi Ma & Fusuo Zhang, 2021. "Methodology of Analyzing Maize Density Loss in Smallholder’s Fields and Potential Optimize Approach," Agriculture, MDPI, vol. 11(6), pages 1-15, May.
  • Handle: RePEc:gam:jagris:v:11:y:2021:i:6:p:480-:d:560753
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/11/6/480/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/11/6/480/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Deepak K. Ray & Navin Ramankutty & Nathaniel D. Mueller & Paul C. West & Jonathan A. Foley, 2012. "Recent patterns of crop yield growth and stagnation," Nature Communications, Nature, vol. 3(1), pages 1-7, January.
    2. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    3. Banchayehu Tessema Assefa & Jordan Chamberlin & Pytrik Reidsma & João Vasco Silva & Martin K. Ittersum, 2020. "Unravelling the variability and causes of smallholder maize yield gaps in Ethiopia," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 12(1), pages 83-103, February.
    4. Guangfeng Chen & Hongzhu Cao & Jun Liang & Wenqi Ma & Lufang Guo & Shuhua Zhang & Rongfeng Jiang & Hongyan Zhang & Keith W. T. Goulding & Fusuo Zhang, 2018. "Factors Affecting Nitrogen Use Efficiency and Grain Yield of Summer Maize on Smallholder Farms in the North China Plain," Sustainability, MDPI, vol. 10(2), pages 1-18, January.
    5. Deepak K. Ray & James S. Gerber & Graham K. MacDonald & Paul C. West, 2015. "Climate variation explains a third of global crop yield variability," Nature Communications, Nature, vol. 6(1), pages 1-9, May.
    6. Qun Wang & Jun Xue & Guoqiang Zhang & Jianglu Chen & Ruizhi Xie & Bo Ming & Peng Hou & Keru Wang & Shaokun Li, 2020. "Nitrogen Split Application Can Improve the Stalk Lodging Resistance of Maize Planted at High Density," Agriculture, MDPI, vol. 10(8), pages 1-13, August.
    7. Nathaniel D. Mueller & James S. Gerber & Matt Johnston & Deepak K. Ray & Navin Ramankutty & Jonathan A. Foley, 2012. "Closing yield gaps through nutrient and water management," Nature, Nature, vol. 490(7419), pages 254-257, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shilei Cui & Yajuan Li & Xiaoqiang Jiao & Dong Zhang, 2022. "Hierarchical Linkage between the Basic Characteristics of Smallholders and Technology Awareness Determines Small-Holders’ Willingness to Adopt Green Production Technology," Agriculture, MDPI, vol. 12(8), pages 1-17, August.
    2. Wang, Hongzhang & Ren, Hao & Zhang, Lihua & Zhao, Yali & Liu, Yuee & He, Qijin & Li, Geng & Han, Kun & Zhang, Jiwang & Zhao, Bin & Ren, Baizhao & Liu, Peng, 2023. "A sustainable approach to narrowing the summer maize yield gap experienced by smallholders in the North China Plain," Agricultural Systems, Elsevier, vol. 204(C).
    3. Wang, Hongzhang & Ren, Hao & Han, Kun & Li, Geng & Zhang, Lihua & Zhao, Yali & Liu, Yuee & He, Qijin & Zhang, Jiwang & Zhao, Bin & Ren, Baizhao & Liu, Peng, 2023. "Improving the net energy and energy utilization efficiency of maize production systems in the North China Plain," Energy, Elsevier, vol. 274(C).

    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. Cao, Juan & Zhang, Zhao & Tao, Fulu & Chen, Yi & Luo, Xiangzhong & Xie, Jun, 2023. "Forecasting global crop yields based on El Nino Southern Oscillation early signals," Agricultural Systems, Elsevier, vol. 205(C).
    2. Arata, Linda & Fabrizi, Enrico & Sckokai, Paolo, 2020. "A worldwide analysis of trend in crop yields and yield variability: Evidence from FAO data," Economic Modelling, Elsevier, vol. 90(C), pages 190-208.
    3. Zhang, Bangbang & Li, Xian & Chen, Haibin & Niu, Wenhao & Kong, Xiangbin & Yu, Qiang & Zhao, Minjuan & Xia, Xianli, 2022. "Identifying opportunities to close yield gaps in China by use of certificated cultivars to estimate potential productivity," Land Use Policy, Elsevier, vol. 117(C).
    4. Kamini Yadav & Hatim M. E. Geli, 2021. "Prediction of Crop Yield for New Mexico Based on Climate and Remote Sensing Data for the 1920–2019 Period," Land, MDPI, vol. 10(12), pages 1-27, December.
    5. Fritz, Steffen & See, Linda & Bayas, Juan Carlos Laso & Waldner, François & Jacques, Damien & Becker-Reshef, Inbal & Whitcraft, Alyssa & Baruth, Bettina & Bonifacio, Rogerio & Crutchfield, Jim & Rembo, 2019. "A comparison of global agricultural monitoring systems and current gaps," Agricultural Systems, Elsevier, vol. 168(C), pages 258-272.
    6. Anika Reetsch & Kai Schwärzel & Christina Dornack & Shadrack Stephene & Karl-Heinz Feger, 2020. "Optimising Nutrient Cycles to Improve Food Security in Smallholder Farming Families—A Case Study from Banana-Coffee-Based Farming in the Kagera Region, NW Tanzania," Sustainability, MDPI, vol. 12(21), pages 1-34, November.
    7. Larson,Donald F. & Muraoka,Rie & Otsuka,Keijiro, 2016. "On the central role of small farms in African rural development strategies," Policy Research Working Paper Series 7710, The World Bank.
    8. Dazhuan Ge & Hualou Long & Li Ma & Yingnan Zhang & Shuangshuang Tu, 2017. "Analysis Framework of China’s Grain Production System: A Spatial Resilience Perspective," Sustainability, MDPI, vol. 9(12), pages 1-21, December.
    9. Anna Florence & Andrew Revill & Stephen Hoad & Robert Rees & Mathew Williams, 2021. "The Effect of Antecedence on Empirical Model Forecasts of Crop Yield from Observations of Canopy Properties," Agriculture, MDPI, vol. 11(3), pages 1-16, March.
    10. Gao, Yukun & Zhao, Hongfang & Zhao, Chuang & Hu, Guohua & Zhang, Han & Liu, Xue & Li, Nan & Hou, Haiyan & Li, Xia, 2022. "Spatial and temporal variations of maize and wheat yield gaps and their relationships with climate in China," Agricultural Water Management, Elsevier, vol. 270(C).
    11. Markhof,Yannick Valentin & Ponzini,Giulia & Wollburg,Philip Randolph, 2022. "Measuring Disaster Crop Production Losses Using Survey Microdata : Evidence from Sub-Saharan Africa," Policy Research Working Paper Series 9968, The World Bank.
    12. Pinki Mondal & Meha Jain & Andrew Robertson & Gillian Galford & Christopher Small & Ruth DeFries, 2014. "Winter crop sensitivity to inter-annual climate variability in central India," Climatic Change, Springer, vol. 126(1), pages 61-76, September.
    13. Oskar Marko & Sanja Brdar & Marko Panić & Isidora Šašić & Danica Despotović & Milivoje Knežević & Vladimir Crnojević, 2017. "Portfolio optimization for seed selection in diverse weather scenarios," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-27, September.
    14. Mary Ollenburger & Page Kyle & Xin Zhang, 2022. "Uncertainties in estimating global potential yields and their impacts for long-term modeling," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 14(5), pages 1177-1190, October.
    15. Shalander Kumar & Abhishek Das & Michael Hauser & Geoffrey Muricho & Tulu Degefu & Asnake Fikre & Chris Ojiewo & Setotaw Ferede & Rajeev K. Varshney, 2022. "Estimating the potential to close yield gaps through increased efficiency of chickpea production in Ethiopia," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 14(5), pages 1241-1258, October.
    16. Qiao, Shengchao & Harrison, Sandy P. & Prentice, I. Colin & Wang, Han, 2023. "Optimality-based modelling of wheat sowing dates globally," Agricultural Systems, Elsevier, vol. 206(C).
    17. von der Goltz, Jan & Dar, Aaditya & Fishman, Ram & Mueller, Nathaniel D. & Barnwal, Prabhat & McCord, Gordon C., 2020. "Health Impacts of the Green Revolution: Evidence from 600,000 births across the Developing World," Journal of Health Economics, Elsevier, vol. 74(C).
    18. Jing Hou & Bo Hou, 2019. "Farmers’ Adoption of Low-Carbon Agriculture in China: An Extended Theory of the Planned Behavior Model," Sustainability, MDPI, vol. 11(5), pages 1-20, March.
    19. Dong-Gill Kim & Elisa Grieco & Antonio Bombelli & Jonathan E. Hickman & Alberto Sanz-Cobena, 2021. "Challenges and opportunities for enhancing food security and greenhouse gas mitigation in smallholder farming in sub-Saharan Africa. A review," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(2), pages 457-476, April.
    20. Sellers, Samuel & Gray, Clark, 2019. "Climate shocks constrain human fertility in Indonesia," World Development, Elsevier, vol. 117(C), pages 357-369.

    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:11:y:2021:i:6:p:480-:d:560753. 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.