CHAN DU 1,2LE LIU 3JUN GUO 1YONGHONG HE 1,*[ ... ]HUI MA 1,2
Author Affiliations
Abstract
1 Shenzhen Key Laboratory for Minimal Invasive Medical Technologies Graduate School at Shenzhen, Tsinghua University Shenzhen 518055, P. R. China
2 Department of Physics, Tsinghua University Beijing 100084, P. R. China
3 Laboratory of Advanced Power Source Graduate School at Shenzhen, Tsinghua University Shenzhen 518055, P. R. China
We developed a biosensor that is capable for simultaneous surface plasmon resonance (SPR) sensing and hyperspectral fluorescence analysis in this paper. A symmetrical metal-dielectric slab scheme is employed for the excitation of coupled plasmon waveguide resonance (CPWR) in the present work. Resonance between surface plasmon mode and the guided waveguide mode generates narrower full width half-maximum of the reflective curves which leads to increased precision for the determination of refractive index over conventional SPR sensors. In addition, CPWR also offers longer surface propagation depths and higher surface electric field strengths that enable the excitation of fluorescence with hyperspectral technique to maintain an appreciable signal-to-noise ratio. The refractive index information obtained from SPR sensing and the chemical properties obtained through hyperspectral fluorescence analysis confirm each other to exclude false-positive or false-negative cases. The sensor provides a comprehensive understanding of the biological events on the sensor chips.
Coupled plasmon waveguide resonance sensing hyperspectral fluorescence 
Journal of Innovative Optical Health Sciences
2014, 7(1): 1450017
作者单位
摘要
浙江大学生物系统工程与食品科学学院, 浙江 杭州 310058
腐烂是发生在柑橘类水果中最普遍、 最严重的病害, 早期腐烂果的自动化检测有助于提高水果加工业的市场竞争力。 然而, 目前没有有效的自动化检测技术。 以脐橙为研究对象, 利用荧光高光谱成像检测早期腐烂果。 最佳指数OIF理论用于识别腐烂果的最优波段组合(498.6和591.4 nm)。 基于最优波长的比图像及双阈值分割算法, 识别率达到100%。 研究表明, 该方法能有效克服梗伤果及果梗在紫外线诱导下所产生的荧光效应对腐烂果识别的影响。 该研究为基于多光谱成像技术对早期腐烂果的在线检测系统的开发奠定了基础。
高光谱荧光图像 波段比算法 OIF理论 脐橙 早期腐烂 梗伤 Hyperspectral fluorescence images Band ratio algorithm OIF method Navel oranges Early rottenness Stem damage 
光谱学与光谱分析
2012, 32(1): 142

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