毕业论文移动版

摘要：叶片是植物进行光合作用的主要器官，叶片的氮素浓度是诊断作物氮素营养、评价作物生长状况的重要参考指标。多光谱分析技术可以大面积、无破坏和实时获取水稻叶层氮含量信息，这对于指导水稻氮素营养的精确管理及产量的预测具有十分重要的意义。本实验以4个水稻品种和3个不同施氮水平的田间试验为基础，使用CGMD302作物生长监测诊断仪和GreenSeeker植物冠层光谱仪来研究植被指数与水稻叶层氮含量之间的关系，分析了水稻冠层光谱的归一化植被指数(NDVI)、比值植被指数(RVI)和差值植被指数(DVI)与不同时期水稻叶片氮含量的相关性。结果表明：（1）使用CGMD302测量的NDVI、RVI和DVI的数值随着水稻叶层氮含量的增加而增加，叶片氮含量与NDVI、RVI和DVI有较好的线性关系，并构建了反演模型，模型的拟合度较高；（2）使用GreenSeeker测量的NDVI的数值与水稻叶片氮含量没有较好的线性关系。66503

毕业论文关键词：水稻，叶层，氮含量，归一化植被指数，比值植被指数，差值植被指数

Abstract: Leaves were the main organs of the plant for photosynthesis, leaf nitrogen concentration of crop nitrogen nutrition diagnosis, evaluation of crop conditions in important reference. Multi-spectral analysis technology could large area, no destruction and the real-time acquisition of the rice leaf nitrogen content information, which for the guidance of nitrogen nutrition of rice precise management and yield prediction had very important significance. In this experiment, four rice varieties and three different nitrogen levels in field experiments as the foundation, using crop CGMD302 growth monitoring and diagnosis instrument and GreenSeeker spectral reflectance of plant to study the relationship between vegetation index and leaf nitrogen content, analysis of the correlation between rice canopy reflectance and Normalized Difference Vegetation Index , Ratio Vegetation Index and Difference Vegetation Index and different period of rice leaf nitrogen content. Results showed that: (1) using CGMD302 measurement of the NDVI, RVI and DVI numerical increased with the increasing of the nitrogen content of rice leaf, the leaf nitrogen content and NDVI, RVI and DVI had good linear relationship, and the inversion model was constructed and the fitting degree of the model was high; (2) using green seeker measurement of NDVI value and leaf nitrogen content in rice no good linear relationship.

Keywords：Rice, Foliation, Nitrogen Content, Normalized Difference Vegetation Index, Ratio Vegetation Index, Difference Vegetation Index

目录

1  前言 3

2  材料与方法 4

2.1材料与实验设计 4

2.2光谱数据的采集 5

2.3氮含量的测定 6

2.4数据分析 6

3  结果与分析 6

3.1不同时期水稻叶片氮含量的变化 6

3.2不同时期水稻叶层植被指数的变化 7

3.2.1 CGMD302测量的不同时期水稻叶层NDVI的变化 7

3.2.2 CGMD302测量的不同时期水稻叶层RVI的变化 8

3.2.3 CGMD302测量的不同时期水稻叶层DVI的变化 9

3.2.4 GreenSeeker测量的不同时期水稻叶层NDVI的变化 10

3.3水稻叶层氮含量反演模型的构建 11