摘要
作物在遭受各种胁迫下的长势及健康诊断是精细农业操作的重要环节。高光谱成像技术具有图谱合一的优势,已成为近年来国内外研究的热点。本文以叶片尺度的小麦为研究对象,利用自主研发的成像光谱仪,采集遭受养分、病虫害胁迫的小麦叶片高光谱图像,利用逐像素平均法增强光谱特征,根据反射率差异进行分析研究。结果表明,提取的高光谱能够反映不同叶位叶片的养分差异,还能利用成像图直观地进行作物养分胁迫程度判断;利用成像光谱仪2 nm的光谱分辨率和毫米级的空间分辨率,在作物感染病害时,既可定量每个叶片的病斑个数,又能定性地分析感染面积对叶片造成的影响;在作物遭受虫害时,可对蚜虫群体甚至单个蚜虫的光谱信息进行提取,这为定量研究蚜虫对小麦叶片的危害提供了新的手段。上述结果充分说明成像高光谱在作物长势定量定性分析研究中具有独特的优势。
The diagnosis of growing status and vigor of crops under various stresses is an important step in precision agriculture.Hyperspectral imaging technology has the advantage of providing both spectral and spatial information simultaneously,and has become a research hot spot.In the present study,auto-development of the pushbroom imaging spectrometer(PIS) was utilized to collect hyperspectral images of wheat leaves which suffer from shortage of nutrient,pest and disease stress.The hyperspectral cube was processed by the method of pixel average step by step to highlight the spectral characteristics, which facilitate the analysis based on the differences of leaves reflectance.The results showed that the hyperspectra of leaves from different layers can display nutrient differences,and recognize intuitively different stress extent by imaging figures.With the 2 nanometer spectral resolution and millimeter level spatial resolution of PIS,the number of disease spot can be qualitatively calculated when crop is infected with diseases,and,the area of plant disease could also be quantitatively analyzed;when crop suffered from pest and insect,the spectral information of leaves with single aphid and aphids can be detected by PIS,which provides a new means to quantitatively detect the aphid destroying of wheat leaf.The present study demonstrated that hyperspecral imaging has a great potential in quantitative and qualitative analysis of crop growth.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2011年第4期1101-1105,共5页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金项目(41071276
41071228)
国家高新技术研究发展计划(863计划)项目(2010AA10Z201)
农业部行业科技项目(200903010)资助
关键词
高光谱成像
特征分析
胁迫
小麦叶片
Hyperspectral imaging
Characteristic analysis
Stress
Wheat leaf