中国农业气象 ›› 2012, Vol. 33 ›› Issue (01): 124-128.doi: 10.3969/j.issn.1000-6362.2012.01.020

• 论文 • 上一篇    下一篇

小麦叶片水分及绿度特征的光谱法诊断

金林雪,李映雪,徐德福,郭建茂,张碧辉   

  1. 南京信息工程大学江苏省农业气象重点实验室/南京信息工程大学应用气象学院,南京 210044
  • 收稿日期:2011-07-27 出版日期:2012-02-20 发布日期:2012-02-09
  • 作者简介:金林雪(1986-),女,内蒙古鄂尔多斯人,硕士生,主要从事应用气象及农业遥感方面的研究。 Email:Jinlinxue324@126.com
  • 基金资助:

    苏省农业气象重点实验室开放课题(JKLAM201201);江苏高校优势学科建设工程资助项目;国家自然科学基金(41071282)

Spectroscopy Diagnostics of Water Content and Greenness Features in Wheat Leaf

 JIN  Lin-Xue, LI  Ying-Xue, XU  De-Fu, GUO  Jian-Mao, ZHANG  Bi-Hui   

  1. Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology/College〖JP〗〖JP+1〗〖JP〗of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044,China
  • Received:2011-07-27 Online:2012-02-20 Published:2012-02-09

摘要: 通过ASD FieldSpec光谱仪测定2个小麦品种3个氮肥处理、3个水分处理下的叶片反射光谱,用SPAD-502仪测定叶片的SPAD(绿度指数)值,并称取叶重。用ViewSpec Pro与Matlab软件处理光谱数据,分析光谱参数与叶片含水量及SPAD值的相关关系,从而明确叶片水分及绿度特征的最佳波段或光谱指数。结果表明,水分指数(WI)、水分胁迫指数(MSI)及中红外植被指数(MSVI1)与叶片含水量的相关关系密切且表现稳定,均通过了0.05水平的显著性检验;〖JP〗Fd664(664nm附近处一阶导数光谱值)、SDr/SDb(红边区域一阶微分总和与蓝边区域一阶微分总和的比值)与小麦叶片SPAD值的相关性达到极显著水平,因而利用光谱法诊断和监测小麦叶片水分及绿度特征具有良好的可行性,可为遥感技术应用于精准农业提供依据。

关键词: 小麦, 水分, SPAD值(绿度指数), 高光谱

Abstract: The leaf spectral reflectance of three nitrogen levels of the two wheat varieties, and three water content treatments was investigated by using of ASD FieldSpec 3 spectra, the SPAD value was determined then to weight the different leaves by using of SPAD-502, the correlation relationship among the spectrum parameters, water content and SPAD value was analyzed by using of ViewSpec Pro and Matlab softwares, in order to define the sensitive bands or spectral index for water content and greenness features of wheat leaves. The results showed that there was close and stable relationship among water index (WI),water stress index (MSI) and midinfrared simple vegetation index one (MSVI1)(P<0.05).There was significant relationship between Fd664, SDr/SDb and SPAD value, which indicated that spectral parameters could be used to monitor wheat leaf water content and greenness features.

Key words: Wheat, Water, SPAD value (leaf green index), Hyperspectral