• ISSN 1008-505X
  • CN 11-3996/S
王磊, 白由路. 基于光谱理论的作物营养诊断研究进展[J]. 植物营养与肥料学报, 2006, 12(6): 902-912. DOI: 10.11674/zwyf.2006.0624
引用本文: 王磊, 白由路. 基于光谱理论的作物营养诊断研究进展[J]. 植物营养与肥料学报, 2006, 12(6): 902-912. DOI: 10.11674/zwyf.2006.0624
WANG Lei, BAI You-lu. Research advance on plant nutrition diagnosis based on spectral theory[J]. Journal of Plant Nutrition and Fertilizers, 2006, 12(6): 902-912. DOI: 10.11674/zwyf.2006.0624
Citation: WANG Lei, BAI You-lu. Research advance on plant nutrition diagnosis based on spectral theory[J]. Journal of Plant Nutrition and Fertilizers, 2006, 12(6): 902-912. DOI: 10.11674/zwyf.2006.0624

基于光谱理论的作物营养诊断研究进展

Research advance on plant nutrition diagnosis based on spectral theory

  • 摘要: 随着光谱技术的发展及其自身的优点,应用光谱技术在作物营养诊断和养分估测方面的研究也越来越多。本文概要地介绍了植物光谱诊断的原理和生理基础,总结了高光谱数据的提取和处理方法;着重评述了光谱技术在作物氮、磷、钾和其它营养元素的营养诊断和养分含量估测的国内外研究状况和进展。文章指出,氮素营养的光谱诊断研究较多,提取出一些敏感波段,建立了光谱指数,并初步得到验证;磷钾营养的光谱诊断研究相对较少,并且结论也不统一;其它营养元素的光谱诊断只是略有涉及,需要进一步研究。本文还就当前作物营养光谱诊断研究的重点以及光谱数据采集和建立养分预测模型中存在的问题进行了分析讨论,并提出了今后的研究方向和应用前景。

     

    Abstract: With the development of spectral technology and its inherent advantage,more and more researches were carried out to investigate the application of spectral technology on plant nutrition diagnosis and nutrients contents prediction.In the article,firstly,the principle and physiological basis for plant spectral diagnosis was briefly introduced.Then the methods of hyperspectral data extraction and analysis were summarized focusing on the crops nitrogen,phosphorus,potassium and other nutrients nutrition diagnosis and nutrients contents prediction.A big research progress has made in the research concerning N nutritional spectral diagnosis,in which sensitive wave bands were put forward and spectral indices were constructed and validated.However,the research concerning P and K nutritional spectral diagnosis was much less comprehensive and the result were inconsistent;other nutrients spectral diagnosis were touched upon in some sort and much research should be continued further.In addition,a detail analysis for the existing difficulties about spectrum data collection and nutrients prediction models was performed.Finally,the future advance trends and the prospect of application were brought up.

     

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