Recognition of Soybean Varieties Based on Near Infrared Transmittance Spectroscopy and BP Neural Network(PDF)
《大豆科学》[ISSN:1000-9841/CN:23-1227/S]
- Issue:
- 2013年02期
- Page:
- 249-253
- Research Field:
- Publishing date:
Info
- Title:
- Recognition of Soybean Varieties Based on Near Infrared Transmittance Spectroscopy and BP Neural Network
- Author(s):
- YANG Dong-feng1; ZHU Hong-de2
- (1.Department of Information Technology,Heilongjiang Bayi Agricultural University,Daqing 163319,China;2.Agronomy College,Heilongjiang Bayi Agricultural University,Daqing 163319,China)
- Keywords:
- Near infrared transmittance spectroscopy; Principal component analysis; Discrete wavelet transform; BP Neural network; Soybean〖ZK)〗
- PACS:
- -
- DOI:
- 10.3969/j.issn.1000-9841.2013.02.025
- 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.
Last Update: 2014-04-03