Moving-window bis-correlation coe±cients method for visible and near-infrared spectral discriminant analysis with applications

Lijun Yao; Weiqun Xu; Tao Pan; Jiemei Chen

doi:doi:10.1142/s1793545818500050

Journal of Innovative Optical Health Sciences, 2018, 11 (2): 1850005, Published Online: Sep. 18, 2018

Moving-window bis-correlation coe±cients method for visible and near-infrared spectral discriminant analysis with applications

论文大纲

Lijun Yao ¹Weiqun Xu ¹Tao Pan ^1,*Jiemei Chen ²

Author Affiliations

¹ Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Department of Optoelectronic Engineering, Jinan University, Guangzhou, China

² Department of Biological Engineering, Jinan University, Guangzhou, China

Visible and near-infrared spectroscopic discrimina transgenic sugarcane leaves β-thalassemia moving-window bis-correlation coe±cients moving-window principal component analysis linear

Abstract

The moving-window bis-correlation coe±cients (MW-BiCC) was proposed and employed for the discriminant analysis of transgenic sugarcane leaves and --thalassemia with visible and nearinfrared (Vis–NIR) spectroscopy. The well-performed moving-window principal component analysis linear discriminant analysis (MW-PCA–LDA) was also conducted for comparison. A total of 306 transgenic (positive) and 150 nontransgenic (negative) leave samples of sugarcane were collected and divided to calibration, prediction, and validation. The diffuse reflection spectra were corrected using Savitzky–Golay (SG) smoothing with first-order derivative (d=1), third-degree polynomial (p=3) and 25 smoothing points (m=25). The selected waveband was 736–1054 nm with MW-BiCC, and the positive and negative validation recognition rates (V REC+, V REC-T were 100%, 98.0%, which achieved the same effect as MW-PCA–LDA. Another example, the 93 --thalassemia (positive) and 148 nonthalassemia (negative) of human hemolytic samples were collected. The transmission spectra were corrected using SG smoothing with d=1, p=3 and m=53. Using MW-BiCC, many best wavebands were selected (e.g., 1116–1146, 1794–1848 and 2284–2342nm). The V REC+ and V REC- were both 100%, which achieved the same effect as MW-PCA–LDA. Importantly, the BiCC only required calculating correlation coe±cients between the spectrum of prediction sample and the average spectra of two types of calibration samples. Thus, BiCC was very simple in algorithm, and expected to obtain more applications. The results first confirmed the feasibility of distinguishing --thalassemia and normal control samples by NIR spectroscopy, and provided a promising simple tool for large population thalassemia screening.

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Lijun Yao, Weiqun Xu, Tao Pan, Jiemei Chen. Moving-window bis-correlation coe±cients method for visible and near-infrared spectral discriminant analysis with applications[J]. Journal of Innovative Optical Health Sciences, 2018, 11(2): 1850005.

Moving-window bis-correlation coe±cients method for visible and near-infrared spectral discriminant analysis with applications

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