实用化商品玉米籽粒的近红外光谱品种判别方法研究  

A New Discrimination Method of Maize Seed Varieties Based onNear-Infrared Spectroscopy

作　　者：郭婷婷[1,2] 王守觉[1] 王红武[3] 胡海晓[4] 安冬[5] 邬文锦[5] 夏维[5] 翟亚锋[6] 

机构地区：[1]中国科学院半导体研究所人工神经网络实验室,北京100083 [2]中国科学院研究生院,北京100049 [3]中国农业科学院作物科学研究所,北京100081 [4]中国农业大学国家玉米改良中心,北京100193 [5]中国农业大学信息与电气工程学院,北京100083 [6]中国农业大学生物学院,北京100193

出　　处：《光谱学与光谱分析》2010年第9期2372-2376,共5页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(60805011;60753001);高等学校博士学科点专项科研基金项目(200800191028)资助

摘　　要：近年来利用近红外光谱进行农作物品种判别成为农产品检测的一个新兴方向。该文提出一种基于近红外光谱的新的实用化商品玉米品种判别系统,此系统既能对系统学习过的品种做出准确判别也能对未学习过的品种做出准确拒识。首先采用一阶导数法对原始光谱进行预处理,光谱数据经主成分分析后,根据仿生模式识别理论建立判别模型。在建立模型时文章使用了基于二维单形的Ψ-3神经元作为覆盖单元,并提出了包含指数的概念以辅助判定样品的唯一归属。测试结果表明,该系统对参与建模的品种有较强的判别能力,即使建模品种达到34个时系统平均正确判别率仍达到91.8%。同时对于未参与建模的品种也有较强的拒识能力,平均正确拒识率达到95%以上。A new discrimination method for the maize seed varieties based on the near-infrared spectroscopy was proposed.The reflectance spectra of maize seeds were obtained by a FT-NIR spectrometer（12 000-4 000 cm-1）.The original spectra data were preprocessed by first derivative method.Then the principal component analysis（PCA） was used to compress the spectra data.The principal components with the cumulate reliabilities more than 80% were used to build the discrimination models.The model was established by Ψ-3 neuron based on biomimetic pattern recognition（BPR）.Especially,the parameter of the covering index was proposed to assist to discriminating the variety of a seed sample.The authors tested the discrimination capability of the model through four groups of experiments.There were 10,18,26 and 34 varieties training the discrimination models in these experiments,respectively.Additionally,another seven maize varieties and nine wheat varieties were used to test the capability of the models to reject the varieties not participating in training the models.Each group of the experiment was repeated three times by selecting different training samples at random.The correct classification rates of the models in the four-group experiments were above 91.8%.The correct rejection rates for the varieties not participating in training the models all attained above 95%.Furthermore,the performance of the discrimination models did not change obviously when using the different training samples.The results showed that this discrimination method can not only effectively recognize the maize seed varieties,but also reject the varieties not participating in training the model.It may be practical in the discrimination of maize seed varieties.

关 键 词：近红外光谱 玉米 品种判别 仿生模式识别 

分 类 号：O657.3[理学—分析化学] S123[理学—化学]