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累积量信息，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3个水稻品种和4个不同施氮水平的田间试验为基础，使用CGMD302和GreenSeeker光谱仪采集作物的反射光谱数据，并构建基于光谱数据的氮累积量反演模型。结果表明，基于CGMD302和GreenSeeker的NDVI均随施氮量的增加而不断增加。基于CGMD302和GreenSeeker的RVI在水稻生育前期呈上升趋势，在生育后期呈下降趋势。使用CGMD302和GreenSeeker光谱仪测量水稻叶层的NDVI和RVI，NDVI与水稻叶层氮累积量所构建的模型拟合度较高，R2分别为0。85617、0。88998。而基于CGMD302和GreenSeeker的RVI与水稻叶层氮累积量则呈现较好的线性关系，R2分别为0。85699、0。91589。80042

毕业论文关键词：水稻，氮累积量，NDVI，RVI，光谱，无损监测

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, three rice varieties and four different nitrogen levels in field experiments as the foundation, using CGMD302 crop growth monitoring and diagnosis instrument and GreenSeeker spectral reflectance of plant to study the relationship between vegetation index and leaf nitrogen content, build the nitrogen accumulation quantity inversion model based on spectral data。 The results showed that both the NDVI based on CGMD302 and GreenSeeker along with the increase of nitrogen application rate increased, but the sample of the same breed different experimental treatment gap between vegetation index is small。 Based on CGMD302 and GreenSeeker RVI is on the rise at the early stage of the rice family, a downward trend in the late childbearing。 Based on CGMD302 and GreenSeeker NDVI and rice leaf nitrogen cumulant matching degree is higher, R2 are 0。85617and0。88998。Based on CGMD302 and GreenSeeker RVI and rice leaf layer the nitrogen accumulation quantity are good linear relationship, R2 are 0。85699 and 0。91589。

Keywords：rice, Nitrogen accumulation , NDVI,RVI, spectrum, nondestructive monitoring

目录

1  前言 2

2  材料与方法 2

2。1 实验材料与实验设备 2

2。2 实验设计 2

2。3 农学指标测量 2

2。4 水稻冠层光谱数据的采集 2

2。5 数据分析 2

3  水稻叶层氮累积量光谱监测模型的构建 2

3。1 水稻叶层农学指标随氮肥处理的变化 2

3。1。1 水稻叶层氮含量随氮肥处理的变化 2

3。1。2 水稻叶层生物量随氮肥处理的变化 2

3。1。3 水稻叶层氮累积量随氮肥处理的变化 2

3。2 基于NDVI水稻叶层氮累积量反演模型的构建 2

3。2。1 水稻叶层NDVI随氮肥处理的变化 2