摘要：对农作物长势的动态监测可实时了解农作物的生长状况和营养状况，便于采取相应管理措施，对于获得作物的高产具有重要意义。本文研究了适合淮安地区的小麦生物量快速、无损的光谱监测技术。以宁麦13号、扬辐麦4号和淮麦20号三个小麦品种为实验材料，设置0kgN/667m2、8kgN/667m2、15kgN/667m2、22kgN/667m2四个氮肥水平，分别使用GreenSeeker和CGMD302光谱仪采集作物反射光谱信息，并构建了光谱的生物量反演模型。结果表明，基于GreenSeeker和CGMD302的NDVI均随施氮量的增加而不断增加，NDVI在小麦生育前期呈上升趋势，在生育后期呈下降趋势。基于CGMD302的RVI随施氮量的增加而不断增加，且RVI随小麦生育期呈现先上升后下降的趋势。小麦叶片、茎蘖、麦穗和植株的生物量均随施氮量的增加呈现上升趋势，且生物量随小麦发育期呈现上升趋势。基于GreenSeeker和CGMD302的NDVI以及RVI所构建的小麦叶片、茎蘖、植株生物量反演模型拟合程度较高。78556

毕业论文关键词：冬小麦，生物量，植被指数，光谱，无损监测，NDVI,RVI

Abstract: Dynamic monitoring of crop growth could keep abreast of the growing crop conditions and crop nutrition, it was easy to take appropriate administrative measures in order to obtain high-yield crops。 In this paper, a rapid and nondestructive technique for monitoring the biomass of wheat in Huaian area was studied。 There were Ningmai no。13, Yangfumai no。4 and Huaimai no。20 of three wheat varieties as experimental material, and 0 kgN / 667m2, 8 kgN / 667m2, 15 kgN / 667m2, 22 kgN / 667m2 of four nitrogen levels were disposed。 Respectively, GreenSeeker and CGMD302 were used to collect spectral data and construct a spectral inversion model of biomass。 The results show that, the NDVI which was based on GreenSeeker and CGMD302 increased with the increase of the amount of nitrogen application and showed an upward trend in the early stage of wheat, then decreased at the later stage of growth。 The RVI which was based on CGMD302 increased with the increase of the amount of nitrogen application and showed a trend of first increasing and then decreasing with the growing period of wheat。 The biomass of wheat leaves, stems and plants was increased with applied nitrogen amount of increased and biomass with wheat growth period presented a rising trend。 The inversion model which was constructed by NDVI and RVI which were based on GreenSeeker and CGMD302 fitted well with the biomass of wheat leaves, stems and plants。

Keywords: wheat, biomass, vegetation index, spectrum, nondestructive monitoring，NDVI,RVI

目录

1 前言 3

2 材料与方法 4

2。1 实验材料 4

2。2 实验设备 4

2。3 实验设计 5

2。4 农学指标测量 6

2。5 小麦冠层光谱数据的采集 6

2。6 数据分析 7

3 冬小麦生物量光谱监测模型构建 7

3。1 冬小麦生物量随氮肥处理的变化 7

3。1。1 叶片生物量随氮肥处理的变化 7

3。1。2 茎蘖生物量随氮肥处理的变化 8

3。1。3 穗生物量随氮肥处理的变化 9

3。1。4 植株生物量随氮肥处理的变化 10

3。2 冬小麦生物量NDVI反演模型的构建