Detection of the Protein Content of Ningxia Tan Sheep Using Hyperspectral Reflectance Imaging

Song Lei Wang; Gui Shan Liu; Xue Fu Li; Rui Ming Luo

doi:10.4028/www.scientific.net/AMM.513-517.4235

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517Detection of the Protein Content of Ningxia Tan...

Detection of the Protein Content of Ningxia Tan Sheep Using Hyperspectral Reflectance Imaging

Abstract:

Near-infrared (NIR) hyperspectral imaging technique (900-1700nm) was evaluated to predict the protein content of Tan sheep. This research adopted NIR hyperspectral imaging to get imaging information of 72 mutton samples, multiplicative scatter correction was used to spectral data preprocessing. The optimal wavelengths were obtained through linear-regression analysis, BP neural network combined with actual measured values were established the prediction model and verified this model. The results showed that the prediction effect of model was very well. Correlation coefficient (Rp) and root mean squared error of prediction (RMSEP) of the protein were 0.87 and 1.19. The results indicated that it is feasible to predict the protein content of Tan sheep for NIR hyperspectral imaging technique.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

4235-4238

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.4235

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Online since:

February 2014

Authors:

Song Lei Wang, Gui Shan Liu, Xue Fu Li, Rui Ming Luo*

Keywords:

Detection, Near-Infrared Hyperspectral Imaging, Protein, Tan Sheep

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* - Corresponding Author

References

[1] Peipei Wang, Dequan Zhang, Li Chen. Prediction of mutton chemical composition by near infrared reflectance spectroscopy[J]. Journal of nuclear agricultural sciences, 2012 26(3) 500-504.

Google Scholar

[2] Wei Li, Ruiming Luo, Yalei Li, BoYang. Analysis of Characteristic Aroma Compounds of Ningxia Tan Mutton [J]. Modern Food Science and Technology, 2013 29(5) 1173-1177.

Google Scholar

[3] Gamal ElMasry, Dawen Sun. Hyperspectral Imaging for Food Quality Analysis and Control, (2000).

Google Scholar

[4] Mohammed Kamruzzaman, Gamal ElMasry, Dawen Sun. Application of NIR hyperspectral imaging for discrimination of lamb muscles [J]. Journal of Food Engineering, 2011 104(3) 332-340.

DOI: 10.1016/j.jfoodeng.2010.12.024

Google Scholar

[5] Mohammed Kamruzzaman, Gamal ElMasry, Dawen Sun. Non-destructive prediction and visualization of chemical composition in lamb meat using NIR hyperspectral imaging and multivariate regression[J]. Innovative Food Science and Emerging Technologies, 2012 16 218-226.

DOI: 10.1016/j.ifset.2012.06.003

Google Scholar

[6] Gamal ElMasry, Dawen Sun. Near-infrared hyperspectral imaging for predicting colour, pH and tenderness of fresh beef[J]. Journal of Food Engineering, 2012 110(1) 127-140.

DOI: 10.1016/j.jfoodeng.2011.11.028

Google Scholar