IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i2p299-d753967.html
   My bibliography  Save this article

Effects of Solar Radiation on Dry Matter Distribution and Root Morphology of High Yielding Maize Cultivars

Author

Listed:
  • Xiaoxia Guo

    (The Key Laboratory of Oasis Eco-Agriculture, Xinjiang Production and Construction Corps, College of Agronomy, Shihezi University, Shihezi 832000, China
    Key Laboratory of Crop Physiology and Ecology, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Ministry of Agriculture and Rural Affairs, Beijing 100081, China)

  • Yunshan Yang

    (The Key Laboratory of Oasis Eco-Agriculture, Xinjiang Production and Construction Corps, College of Agronomy, Shihezi University, Shihezi 832000, China)

  • Huifang Liu

    (College of Agronomy, Ningxia University, Yinchuan 750021, China)

  • Guangzhou Liu

    (Key Laboratory of Crop Physiology and Ecology, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Ministry of Agriculture and Rural Affairs, Beijing 100081, China)

  • Wanmao Liu

    (College of Agronomy, Ningxia University, Yinchuan 750021, China)

  • Yonghong Wang

    (Institute of Crop Sciences, Ningxia Academy of Agricultural and Forestry Sciences, Yongning, Yinchuan 750105, China)

  • Rulang Zhao

    (Institute of Crop Sciences, Ningxia Academy of Agricultural and Forestry Sciences, Yongning, Yinchuan 750105, China)

  • Bo Ming

    (Key Laboratory of Crop Physiology and Ecology, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Ministry of Agriculture and Rural Affairs, Beijing 100081, China)

  • Ruizhi Xie

    (Key Laboratory of Crop Physiology and Ecology, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Ministry of Agriculture and Rural Affairs, Beijing 100081, China)

  • Keru Wang

    (Key Laboratory of Crop Physiology and Ecology, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Ministry of Agriculture and Rural Affairs, Beijing 100081, China)

  • Shaokun Li

    (The Key Laboratory of Oasis Eco-Agriculture, Xinjiang Production and Construction Corps, College of Agronomy, Shihezi University, Shihezi 832000, China)

  • Peng Hou

    (Key Laboratory of Crop Physiology and Ecology, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Ministry of Agriculture and Rural Affairs, Beijing 100081, China)

Abstract

The root system connects the plant with the soil, which is a key factor in determining the utilization of soil resources and plant growth potential. Solar radiation can change maize shoot and root growth and affect grain formation. In this study, the effects of different solar radiation conditions on root morphology of three maize cultivars XY335, ZD958 and DH618 and their quantitative relationships were studied by conducting shading experiments. This study was conducted in maize high yield region of Qitai and Yinchuan, China, in 2018 and 2019. The planting densities were 7.5 × 10 4 (D1) and 12 × 10 4 (D2) plants ha −1 . The shading levels were natural light (CK), shading 15% (S1), 30% (S2) and 50% (S3). The results showed that maize responded to the decreased solar radiation through the increase in ratio of shoot dry weight (SWR) to whole plant dry weight and the decrease in ratio of root dry weight (RWR) to whole plant dry weight. As the solar radiation decreased, the root length density (RLD), root surface area (RSA), average root diameter (ARD) and root length ratio (RLR) decreased, while the specific root length (SRL) increased. With 100 MJ m −2 decrease in solar radiation, the RWR, RLD, RSA and RLR each decreased by 1.47%, 0.5 mm cm −3 ,0.4 m m −2 and 0. 19 m g −1 , respectively. Among the cultivars, the changes of DH618 were the fastest followed by XY335 and ZD958 but DH618 maintained the largest root system under any solar radiation condition. After the decrease of solar radiation, RWR, RLD and RLR were significantly positively correlated with the yield. This indicated that large root systems were conducive to the rapid response to decreased solar radiation and important for achieving stable and high yield. Maize cultivars with these type of root systems should be recommended to better adapt low solar radiation induced by regional variation or climate change.

Suggested Citation

  • Xiaoxia Guo & Yunshan Yang & Huifang Liu & Guangzhou Liu & Wanmao Liu & Yonghong Wang & Rulang Zhao & Bo Ming & Ruizhi Xie & Keru Wang & Shaokun Li & Peng Hou, 2022. "Effects of Solar Radiation on Dry Matter Distribution and Root Morphology of High Yielding Maize Cultivars," Agriculture, MDPI, vol. 12(2), pages 1-18, February.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:2:p:299-:d:753967
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/2/299/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/12/2/299/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Qi Hu & Xueqing Ma & Huayun He & Feifei Pan & Qijin He & Binxiang Huang & Xuebiao Pan, 2019. "Warming and Dimming: Interactive Impacts on Potential Summer Maize Yield in North China Plain," Sustainability, MDPI, vol. 11(9), pages 1-15, May.
    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. Bruna de Villa & Mirta Teresinha Petry & Maicon Sérgio Nascimento dos Santos & Juliano Dalcin Martins & Isabel Lago & Murilo Brum de Moura & Henrique Schaf Eggers & Giane Lavarda Melo & Felipe Tonett, 2024. "Effects of Minimum and Maximum Limits of Solar Radiation and Its Temporal and Geographic Interactions," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 14(8), pages 173-173, April.
    2. Long Zhang & Guangzhou Liu & Yunshan Yang & Xiaoxia Guo & Shuai Jin & Ruizhi Xie & Bo Ming & Jun Xue & Keru Wang & Shaokun Li & Peng Hou, 2023. "Root Characteristics for Maize with the Highest Grain Yield Potential of 22.5 Mg ha −1 in China," Agriculture, MDPI, vol. 13(4), pages 1-12, March.
    3. Ayse Yavuz Ozalp & Halil Akinci, 2023. "Evaluation of Land Suitability for Olive ( Olea europaea L.) Cultivation Using the Random Forest Algorithm," Agriculture, MDPI, vol. 13(6), pages 1-22, June.

    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. Dongrui Han & Hongyan Cai & Xiaohuan Yang & Xinliang Xu, 2020. "Multi-Source Data Modeling of the Spatial Distribution of Winter Wheat Yield in China from 2000 to 2015," Sustainability, MDPI, vol. 12(13), pages 1-16, July.

    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:12:y:2022:i:2:p:299-:d:753967. 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.