YANG Dong-feng,ZHU Hong-de.Recognition of Soybean Varieties Based on Near Infrared Transmittance Spectroscopy and BP Neural Network[J].Soybean Science,2013,32(02):249-253.[doi:10.3969/j.issn.1000-9841.2013.02.025]
基于近红外透射光谱分析和BP神经网络的大豆品种识别
- Title:
- Recognition of Soybean Varieties Based on Near Infrared Transmittance Spectroscopy and BP Neural Network
- Keywords:
- Near infrared transmittance spectroscopy; Principal component analysis; Discrete wavelet transform; BP Neural network; Soybean〖ZK)〗
- 文献标志码:
- A
- 摘要:
- 为了实现大豆品种的快速无损鉴别,对16份大豆品种的近红外透射光谱(NITS)进行分析。首先通过平滑和马氏距离的光谱预处理方法消除噪声和去除奇异光谱。然后分别用主成分分析(PCA)和离散多带小波变换(DWT)提取光谱特征,作为BP神经网络的输入,构建PCABP和DWTBP大豆品种识别模型。结果表明:PCABP模型的识别准确率为98.125%,平均识别时间为9.3 ms;DWTBP模型的识别准确率为95.93%,平均识别时间为6.4 ms。研究结果为大豆品种的快速无损鉴别提供了理论依据和实用方法。
- Abstract:
- In order to realize rapid nondestructive recognition of soybean varieties,near infrared transmittance spectrum(NITS)of 16 soybean samples were analyzed.Smoothing treatment and Mahalanobis distance were used to filter noise and wipe off singular spectrum.Principal component analysis(PCA)and discrete wavelet transform(DWT)were respectively used to extract spectral features which act as the input of BP neural network.PCABP and DWTBP identification model were built.The accuracy rate of PCABP model and DWTBP model were 98.125% and 95.93%,in addition,the average recognition time were 9.3 ms and 6.4 ms.The results of the investigation provided the theoretical support and practical method for rapid nondestructive recognition of soybean varieties.
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备注/Memo
?引进国际先进农业科学技术计划“948计划”(2008-Z24)。