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Application of Visible and Near-Infrared Hyperspectral Imaging to Determine Soluble Protein Content in Oilseed Rape Leaves.

Zhang C, Liu F, Kong W, He Y - Sensors (Basel) (2015)

Bottom Line: SPA-PLS model obtained the best performance with r(p) of 0.9554, RMSEP of 0.1538 mg/g and RPD of 3.25.Distribution of protein content within the rape leaves were visualized and mapped on the basis of the SPA-PLS model.The overall results indicated that hyperspectral imaging could be used to determine and visualize the soluble protein content of rape leaves.

View Article: PubMed Central - PubMed

Affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China. chuzh@zju.edu.cn.

ABSTRACT
Visible and near-infrared hyperspectral imaging covering spectral range of 380-1030 nm as a rapid and non-destructive method was applied to estimate the soluble protein content of oilseed rape leaves. Average spectrum (500-900 nm) of the region of interest (ROI) of each sample was extracted, and four samples out of 128 samples were defined as outliers by Monte Carlo-partial least squares (MCPLS). Partial least squares (PLS) model using full spectra obtained dependable performance with the correlation coefficient (r(p)) of 0.9441, root mean square error of prediction (RMSEP) of 0.1658 mg/g and residual prediction deviation (RPD) of 2.98. The weighted regression coefficient (Bw), successive projections algorithm (SPA) and genetic algorithm-partial least squares (GAPLS) selected 18, 15, and 16 sensitive wavelengths, respectively. SPA-PLS model obtained the best performance with r(p) of 0.9554, RMSEP of 0.1538 mg/g and RPD of 3.25. Distribution of protein content within the rape leaves were visualized and mapped on the basis of the SPA-PLS model. The overall results indicated that hyperspectral imaging could be used to determine and visualize the soluble protein content of rape leaves.

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Prediction results of the calibration set (a) and the prediction set (b) of PLS model using sensitive wavelengths selected by SPA.
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sensors-15-16576-f005: Prediction results of the calibration set (a) and the prediction set (b) of PLS model using sensitive wavelengths selected by SPA.

Mentions: As a consequence of the previous analysis, the wavelength selection methods significantly reduced the number of wavelengths. The selected sensitive wavelengths were then used to establish calibration models instead of the full range spectral data. By using the sensitive wavelengths, the performances of PLS models were shown in Table 3 and Figure 5.


Application of Visible and Near-Infrared Hyperspectral Imaging to Determine Soluble Protein Content in Oilseed Rape Leaves.

Zhang C, Liu F, Kong W, He Y - Sensors (Basel) (2015)

Prediction results of the calibration set (a) and the prediction set (b) of PLS model using sensitive wavelengths selected by SPA.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541894&req=5

sensors-15-16576-f005: Prediction results of the calibration set (a) and the prediction set (b) of PLS model using sensitive wavelengths selected by SPA.
Mentions: As a consequence of the previous analysis, the wavelength selection methods significantly reduced the number of wavelengths. The selected sensitive wavelengths were then used to establish calibration models instead of the full range spectral data. By using the sensitive wavelengths, the performances of PLS models were shown in Table 3 and Figure 5.

Bottom Line: SPA-PLS model obtained the best performance with r(p) of 0.9554, RMSEP of 0.1538 mg/g and RPD of 3.25.Distribution of protein content within the rape leaves were visualized and mapped on the basis of the SPA-PLS model.The overall results indicated that hyperspectral imaging could be used to determine and visualize the soluble protein content of rape leaves.

View Article: PubMed Central - PubMed

Affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China. chuzh@zju.edu.cn.

ABSTRACT
Visible and near-infrared hyperspectral imaging covering spectral range of 380-1030 nm as a rapid and non-destructive method was applied to estimate the soluble protein content of oilseed rape leaves. Average spectrum (500-900 nm) of the region of interest (ROI) of each sample was extracted, and four samples out of 128 samples were defined as outliers by Monte Carlo-partial least squares (MCPLS). Partial least squares (PLS) model using full spectra obtained dependable performance with the correlation coefficient (r(p)) of 0.9441, root mean square error of prediction (RMSEP) of 0.1658 mg/g and residual prediction deviation (RPD) of 2.98. The weighted regression coefficient (Bw), successive projections algorithm (SPA) and genetic algorithm-partial least squares (GAPLS) selected 18, 15, and 16 sensitive wavelengths, respectively. SPA-PLS model obtained the best performance with r(p) of 0.9554, RMSEP of 0.1538 mg/g and RPD of 3.25. Distribution of protein content within the rape leaves were visualized and mapped on the basis of the SPA-PLS model. The overall results indicated that hyperspectral imaging could be used to determine and visualize the soluble protein content of rape leaves.

Show MeSH
Related in: MedlinePlus