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The Layout of Maize Variety Test Sites Based on the Spatiotemporal Classification of the Planting Environment

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  • Xuli Zan

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China)

  • Zuliang Zhao

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China)

  • Wei Liu

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China)

  • Xiaodong Zhang

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China)

  • Zhe Liu

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China)

  • Shaoming Li

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China)

  • Dehai Zhu

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China)

Abstract

An appropriate layout of crop multi-environment trial (MET) sites is imperative for evaluating new crop varieties’ performance in terms of agronomic traits and stress tolerance, and this information is used to determine the utilization value and suitable promotion region of new varieties. Actually, traditional maize test sites have been selected according to the experience of breeding experts, which leads to the strong subjective and unscientific conclusions regarding sites, as well as test results that are not representative of the target population of environments (TPE). Therefore, in this study, we proposed a new method for MET sites layout. Meteorological data, maize growth period data, and county-level maize planting area data were collected for the spatiotemporal classification of a given maize planting region to analyze change rules in the environmental category of each minimum research unit within the study period. If the occurrence frequency of its final attribution category reaches a certain threshold (50%), this minimum research unit is classified as a typical environment region; otherwise, it is classified as an atypical environment region. Then, the number of test sites in each environmental category is allocated by spatial stratified sampling. At last, we establish the optimal test sites layout and a reliability measurement (test adequacy) methods. The practicability of this method was proved by taking the Three Northeastern Provinces of China as the study area. The result shows that there should be 112 test sites in the study area, the distribution of the test sites is uniform, and the environmental representation is high. Test adequacy analysis of the test sites reveals that most of the environmental categories have a test adequacy that reaches 1 in each test period. The method proposed in this paper provides support for the scientific layout of crop varieties test sites and helps to improve the representative and reliability of variety test results while optimizing resources.

Suggested Citation

  • Xuli Zan & Zuliang Zhao & Wei Liu & Xiaodong Zhang & Zhe Liu & Shaoming Li & Dehai Zhu, 2019. "The Layout of Maize Variety Test Sites Based on the Spatiotemporal Classification of the Planting Environment," Sustainability, MDPI, vol. 11(13), pages 1-15, July.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:13:p:3741-:d:246748
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    References listed on IDEAS

    as
    1. Zuliang Zhao & Liu Zhe & Xiaodong Zhang & Xuli Zan & Xiaochuang Yao & Sijia Wang & Sijing Ye & Shaoming Li & Dehai Zhu, 2018. "Spatial Layout of Multi-Environment Test Sites: A Case Study of Maize in Jilin Province," Sustainability, MDPI, vol. 10(5), pages 1-13, May.
    2. Stevens, Don L. & Olsen, Anthony R., 2004. "Spatially Balanced Sampling of Natural Resources," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 262-278, January.
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    Cited by:

    1. Lin Zhang & Zhe Liu & Diyou Liu & Quan Xiong & Ning Yang & Tianwei Ren & Chao Zhang & Xiaodong Zhang & Shaoming Li, 2019. "Crop Mapping Based on Historical Samples and New Training Samples Generation in Heilongjiang Province, China," Sustainability, MDPI, vol. 11(18), pages 1-17, September.

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