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摘 要：叶绿素是作物营养胁迫、生长状况以及病虫害胁迫情况的重要指标，基于多光谱技术密切监测作物色素含量，能反映作物长势，对实施快速诊断、精准作业、判断作物产量具有重要意义。本课题以中国淮安市为研究区域，研究了在四个施氮水平0、8、15、22kgN/667m2下，宁麦13、扬辐麦4号、淮麦20三种冬小麦品种的田间光谱变化和叶绿素含量的变化。光谱数据采用CGMD302作物生长监测诊断仪和GreenSeeker手持NDVI测量仪采集，研究了小麦冠层叶绿素含量与归一化植被指数、比值植被指数和差值植被指数的关系，旨在构建适于淮安地区的基于多光谱反射率的小麦冠层叶绿素含量的反演模型。结果表明，宁麦13、扬辐麦4号和淮麦20在不同的氮肥水平条件下，倒一叶位、倒二叶位、倒三叶位和倒四叶位的叶绿素含量，自上而下，呈递减趋势；归一化植被指数、比值植被指数和差值植被指数随着氮肥水平的增高而增高；基于NDVI的小麦叶层不同叶位叶绿素含量反演模型受NDVI饱和性的影响，拟合度不高。在此基础上构建的基于RVI和DVI的小麦冠层叶绿素含量的反演模型，数据拟合度有所提高，但R2值依然很低，效果不理想，无法满足实际应用需要。58465
毕业论文关键词：小麦，多光谱无损监测，植被指数，叶绿素含量
Abstract: Chlorophyll is an important indicator of the crop nutrient stress, growth conditions and pest stress situations, based on multi-spectral technology closely monitor crop pigment content that can reflect the crop growth.It is of great importance to the implementation of rapid diagnosis, precise operation to determine crop yield. The issue in China Huai'an City as a case study, studied under four nitrogen levels 0,8,15,22kgN/667m2, three kinds of winter wheat including Ningmai 13, Yangfumai on the 4th and Huaimai 20 of changes in chlorophyll content and spectral data using CGMD crop growth monitoring and diagnostic GreenSeeker handheld NDVI measuring instrument collection. It studied the relationship between the canopy chlorophyll content and normalized relations vegetation index, ratio vegetation index and Difference Vegetation Index, aiming to construct inversion model suitable for canopy chlorophyll content based on multi-spectral reflectance in Huai'an region. The results showed that Ningmai 13, Yangfumai on the 4th and Huaimai 20 at different levels of nitrogen conditions, the chlorophyll content of leaf inverted position, the second leaf position, third leaf bits and down four leaf position showed a decreasing trend; the value of vegetation index, ratio vegetation index and difference vegetation index is along with the nitrogen levels higher and higher; NDVI of wheat leaf layers of different leaf chlorophyll content retrieval model based on NDVI effected by saturation effects of NDVI, so fitting is not high. Canopy Chlorophyll content based on RVI and DVI-inversion model constructed on this basis improved data fitting degree, but the value of R2 is still low, so it can not meet the actual needs.
Keywords：wheat,multispectral nondestructive monitoring,vegetation index, chlorophyll content
1 前言 3
2 材料与方法 4
2.1 材料与实验设计 4
2.2 实验方法 5
2.2.1 叶绿素含量测定方法 5
2.2.2 叶绿素最佳提取时间 5
2.2.3 不同叶位叶绿素含量的测定 6
2.2.4 数据分析 6
2.2.5 光谱数据采集 6
3 结果与分析