毕业论文移动版

摘要：生物量作为指示作物长势状况的重要指标之一，可直接反映作物营养状况及代谢，其大小与作物群体的光能利用、产量和品质密切相关。本文研究了淮安生态点的水稻生物量光谱无损监测技术。以连粳7号、宁粳4号和武运粳24号三个水稻品种为实验材料，设置0kgN/667m2、8kgN/667m2、16kgN/667m2、24kgN/667m2四个氮肥水平，分别使用CGMD302和GreenSeeker光谱仪采集作物的反射光谱信息，并构建了基于光谱数据的反演模型。结果表明，基于CGMD302和GreenSeeker的NDVI随氮含量的增加而不断增加，NDVI随水稻生育期的变化趋势为生育前期呈上升趋势，后期呈下降趋势。基于CGMD302和GreenSeeker的RVI随氮含量的增加而不断增加，RVI随水稻生育期的变化趋势为生育前期呈上升趋势，后期呈下降趋势。水稻叶片、茎蘖、穗和植株生物量均随氮含量的增加而增加，并且随着生育期呈上升趋势。基于CGMD302和GreenSeeker的NDVI以及RVI所构建的水稻叶片、茎蘖、植株生物量反演模型拟合度较高。80044

毕业论文关键词：水稻，生物量，光谱，无损监测，NDVI,RVI

 Abstract: Biomass is one of the important indexes which can indicate crop growing conditions, and it can be directly reflect crop nutrition and metabolism, its size is closely related with light energy utilization, yield and quality of crop group。 This paper studied the huaian ecology rice biomass spectrum condition monitoring technology。 And used lianjing no。7, ningjing no。4  and wuyunjing no。24 three rice varieties as experimental material, set 0kgN/667m2, 8kgN/667m2, 16kgN/667m2 and 24kgN/667m2 four nitrogen levels, respectively, used CGMD302 and GreenSeeker spectrometer acquisition crops of spectral reflectance information, and built the inversion model based on spectral data。 Results showed that the NDVI based on CGMD302 and GreenSeeker along with the increase of nitrogen content increasing, the NDVI trend along with the change of the growth period of rice for days on the rise, the late was on the decline。 Based on CGMD302 and GreenSeeker RVI along with the increase of nitrogen content increasing, RVI trend along with the change of the growth period of rice for days on the rise, the late was on the decline。 Rice leaves, stem tillers, ears and plants biomass increased with the increase of nitrogen content, and the growth period was on the rise。 Based on CGMD302 and GreenSeeker NDVI and RVI constructed of rice leaves, stem tillers, plants biomass inversion model fitting degree was higher。 

Key Words: rice, biomass, spectrum, nondestructive monitoring,NDVI,RVI

目录

1 前言 2

2材料与方法 4

2。1 实验材料与设备 4

2。2 实验设计 4

2。3 农学指标测量 5

2。4 水稻冠层光谱数据的采集 5

2。5数据分析 6

3 水稻生物量光谱监测模型构建 6

3。1 水稻生物量随氮肥处理的变化 6

3。1。1叶片生物量随氮肥处理的变化 6

3。1。2 茎蘖生物量随氮肥处理的变化 7

3。1。3 穗生物量随氮肥处理的变化 8

3。1。4 植株生物量随氮肥处理的变化 9

3。2水稻生物量NDVI反演模型构建 10

3。2。1 水稻NDVI随氮肥处理的变化 10