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The 2015 National Award for Science and Technology Progress for Research on Technologies of Spectral Monitoring and Quantitative Diagnosis of Growth Indexes in Rice and Wheat

Source: Date: 2018-09-30 Click:

Grade:The second prize

Winners:Cao Weixing, Zhu Yan, Tian Yongchao, Yao Xia, Ni Jun, Liu Xiaojun, Deng Jianping, Zhang Jaunjuan, Li Yanda, Wang Shaohua, Ma Jifeng, Shen Shengyuan, Ding Feng, Wu Liquan and Xu Zhifu.

Collaborators:Nanjing Agricultural University, Jiangsu Crop Cultivation Technology Guidance Station, Henan Agricultural University, Jiangxi Academy of Agricultural Sciences

  Since 1999, with the support of the state and provincial science and technology plans, this project focused on  the urgent demand for technologies of spectral monitoring and quantitative diagnosis of crop growth. Taking rice and wheat as the subjects of research, the principles of crop physiology and ecology and the method of quantitative spectral monitoring were comprehensively used to establishe an integrative technology system for spectral monitoring and quantitative diagnosis of crop growth based on reflectance spectra by focusing on exploring the specific spectral bands and spectral indexes of major growth indexes of crops, quantitative monitoring models, real-time regulation methods and monitoring and diagnosis devices. Five achievements have been made in the research as follows:

  (1) Establishing characteristic spectral bands and parameters of sensitive spectra in rice and wheat.

  The researchers of this projecthave performed for years field experiments in terms of different ecological sites, crop varieties, and management practices, a library of reflectance spectra at canopy and leaf levels was constructed, and the dynamic models of the reflectance spectra of rice and wheat under different conditions were systematically analyzed. The responses of leaf and canopy reflectance spectra on the leaf area indexes, biomass, nitrogen content, nitrogen accumulation, chlorophyll density, yield quality were identified. The characteristic spectral bands and sensitive spectral parameters indicating the growth index of rice and wheat were established, which provided support for the construction of spectral estimation models and development of monitoring devices.

  (2) Constructing spectral monitoring models of rice and wheat growth indicators at leaf, canopy, and regional dimensions.

  Based on quantitative modeling techniques and by comprehensively employing the ground and spatial remote-sensing information, the quantitative relationships between the above rice and wheat growth indicators and the corresponding sensitive spectral parameters was established. The spectral estimation models of the main growth indicators of rice and wheat at leaf, canopy and regional dimensions were constructed to achieve quick and multi-dimensional monitoring the real-time status of rice and wheat growth.

  (3) Creating real-time diagnosis and quantitative regulating technologies for rice and wheat growth by a multi-route approach.

  Employing the methods of system analysis, the dynamic models of key growth indicators of rice and wheat at different yield levels were quantitatively explored to construct yield-target-based appropriate timing-sequence models. Further coupling real-time seedling information, and  comprehensively using principles of nutrition balance, nitrogen nutrition indexing, real-time indicators and actual indicator difference, multi-route crop-growth detecting and regulating technologies was developed by integration, comprehensively using principles of nutrition balance, nitrogen nutrition indexing, real-time indicators and actual indicator difference, and so on, so that appropriate fertilizer and water regulation plans for the middle stage of growth of rice and wheat can be made.

  (4) Developing multi-platform rice and wheat growth monitoring and diagnosis software and hardware products.

  The researchers have integrated the crop growth monitoring and diagnosis technologies with hardware engineering to develop the portable and machine-mounted equipments for rice and wheat growth monitoring. Further adopting the technology of WSN,  crop growth sensing nodes are developed to construct agricultural sensing network. In combination with the software engineering, they have created the application systems of rice and wheat growth monitoring and diagnosis and platforms of intelligence management, proving practical technological carriers for real-time monitoring, precise diagnosis and intelligence management of rice and wheat growth.

  (5) Carrying out large-scaled application of the crop growth monitoring and diagnosis systems.

  Technical training and experimental demonstration combined to form instructional and practical technology extension systems with the integration of software application with hardware carriers. Since 2009, they have used the major application carriers, such as the crop growth monitoring and diagnosis instrument, the monitoring and diagnosis application system, the platforms of farmland sensing and intelligent management, took the technical forms of the distribution map of crop growth, the prescription map of fertilizer and water regulation, the distribution map of yield quality, have demonstrated the application of their technologies in the major rice or wheat growth areas in the country with significant economic, social and ecological effects and showing a good prospect of applying their research results.

  The researchers of this program have been issued more than 30 national patents for invention, and 5 practical new-type patents, have registered 16 software copyrights, have extended the use of 219 portable devices of crop growth monitoring and diagnosis and 280 sets of farmland sensing nodes, have published over 200papers, have trained 48 graduate students, Ph. D candidates and post-doctoral researchers. The technology developed in this project has been introduced in the 2014-2015 Jiangsu Province Directories of “Four Recommendations” for Major Farm Crops and has been applied by demonstration in the rice or wheat growth areas in Jiangsu, Henan, Jiangxi, Anhui, Zhejiang, Hebei and Hunan Provinces with significant nitrogen saving (by 7.5%), yield increase (by 5%), and a total extended area of 49.2021 million mu and an increase of 2.428 billion RMB for farmers.


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