Abstract
An approach for identification of terahertz (THz) spectral of genetically modified organisms (GMOs) based on active learning affinity propagation clustering algorithm (ALAP) combined with support vector machine (SVM) in this paper, and THz transmittance spectra of some typical genetically modified (GM) cotton samples are investigated to prove its feasibility. Firstly, principal component analysis is applied to extract features of the spectrum data. Secondly, instead of the original spectrum data, the feature signals are fed into the ALAP–SVM pattern recognition, where an improved active learning ALAP is applied to SVM. The experimental results show that THz spectroscopy combined with ALAP–SVM can be effectively utilized for identification of different GM cottons. The proposed approach provides a new effective method for detection and identification of different GMOs by using THz spectroscopy.
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References
Ahmed, F.E.: Detection of genetically modified organisms in foods. Trends Biotechnol. 20(5), 215–223 (2002)
Alishahi, A., Farahmand, H., Prieto, N., Cozzolino, D.: Identification of transgenic foods using NIR spectroscopy: a review. Spectrochim. Acta A Mol. Biomol. Spectrosc. 75(1), 1–7 (2010)
Chen, T., Li, Z., Mo, W.: Identification of terahertz absorption spectra of explosives based on fuzzy pattern recognition. Chin. J. Instrum. 33, 2480–2486 (2012)
Chen, T., Li, Z., Mo, W.: Identification of biomolecules by terahertz spectroscopy and fuzzy pattern recognition. Spectrochim. Acta A Mol. Bimol. Spectrosc. 106, 48–53 (2013)
Chen, T., Li, Z., Mo, W.: Simultaneous quantitative determination of multicomponents in tablets based on terahertz time-domain spectroscopy. Spectrosc. Spectr. Anal. 33, 1220–1225 (2013)
Fiehn, O., Kopka, J., Trethewey, N., et al.: Identification of uncommon plant metabolites based on calculation of elemental compositions using gas chromatography and quadrupole mass spectrometry. Anal. Chem. 72(15), 3573–3580 (2000)
Frey, B.J., Dueck, D.: Clustering by passing messages between data points. Science 315, 972–976 (2007)
Liu, Y., Lyon, B.G., Windham, W.R., Lyon, C.E., Savage, E.M.: Prediction of physical, color, and sensory characteristics of broiler breasts by visible/near infrared reflectance spectroscopy. Poult. Sci. 83, 1467–1474 (2004)
Margarit, E., Reggiardo, M.I., et al.: Detection of BT transgenic maize in foodstuffs. Food Res. Int. 39(2), 250–255 (2006)
Markelz, A.G., Roitberg, A., Heilweil, E.J.: Pulsed terahertz spectroscopy of DNA, bovine serum albumin and collagen between 0.1 and 2.0 THz. Chem. Phys. Lett. 320(1–2), 42–48 (2000)
Milcamps, A., Rabe, S., Cade, R., et al.: Validity assessment of the detection method of maize event Bt10 through investigation of its molecular structure. J. Agric. Food Chem. 57(8), 3156–3163 (2009)
Moreira, I., Scarminio, I.S.: Chemometric discrimination of genetically modified Coffea arabica cultivars using spectroscopic and chromatographic fingerprints. Talanta 107, 245–254 (2013)
Munck, L., Moller, B., Jacobsen, S., Sondergaard, S.: Near infrared spectra indicate specific mutant endosperm genes and reveal a new mechanism for substituting starch with (1/3, 1/4)-b-glucan in barley. J. Cereal Sci. 40, 213–222 (2004)
Nakamura, K., Akiyama, H., Kawano, N., et al.: Evaluation of real-time PCR detection methods for detecting rice products contaminated by rice genetically modified with a CpTI-KDEL-T-nos transgenic construct. Food Chem. 141(3), 2618–2624 (2013)
Raamsdonk, L.W.D., Holst, C., Baeten, V., Berben, G., Boix, A., Jong, J.: New developments in the detection and identification of processed animal proteins in feeds. Anim. Feed Sci. Technol. 133(1–2), 63–83 (2007)
Rong, C.H.E.N., Yong-Feng, C.A.O., Hong, S.U.N.: Multi-class image classification with active learning and semi-supervised learning. Acta Autom. Sinic. 37, 954–962 (2011)
Small, G.W.: Chemometrics and near-infrared spectroscopy: avoiding the pitfalls. Trends Anal. Chem. 25(11), 1057–1066 (2006)
Upadhya, P.C., Shen, Y.C., Davies, A.G., Linfield, E.H.: Far-infrared vibrational modes of polycrystalline saccharides. Vib. Spectrosc. 35(1–2), 139–143 (2004)
Walther, M., Fischer, B.M., Jepsen, P.U.: Noncovalent intermolecular forces in polycrystalline and amorphous saccharides in the far infrared. Chem. Phys. 288(2–3), 261–268 (2003)
Xie, L.-J., Ying, Y.-B., Ying, T.-J., et al.: Application of Vis/NIR diffuse reflectance spectroscopy to the detection and identification of transgenic tomato leaf. Spectrosc. Spectr. Anal. 28, 1062–1066 (2008)
Yin, X.X., Ng, B.W.-H., Fischer, B.M., Ferguson, B., Abbott, D.: Support vector machine applications in terahertz pulsed signals feature sets. IEEE Sens. 7(12), 1597–1608 (2007)
Zhang, X.R., Liu, F.: A patten classification method based on GA and SVM. In: 6th International Conference on Signal Processing. vol. 1, pp. 110–113 (2002).
Zhang, T.J.: Research on measurement technology of bio-molecules based on terahertz time-domain spectroscopy. Zhejiang Univ. Hangzhou 23, 45–71 (2007)
Zhu, D., Liu, J.F., Tang, Y.B., et al.: A reusable DNA biosensor for the detection of genetically modified organism using magnetic bead-based electrochemiluminescence. Sens. Actuators B 149(1), 221–225 (2010)
Acknowledgments
This research is partly supported by the National Natural Science Foundation of China (No. 61265005); partly supported by Nation Science Foundation of Fujian (No. 2013J01246); partly supported by the foundation from Guangxi Experiment Center of Information Science Guilin University of Electronic Technology (No. 20130101) and the program for innovation research team of Guilin University of Electronic Technology.
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Liu, J., Li, Z., Hu, F. et al. Identification of GMOs by terahertz spectroscopy and ALAP–SVM. Opt Quant Electron 47, 685–695 (2015). https://doi.org/10.1007/s11082-014-9944-9
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DOI: https://doi.org/10.1007/s11082-014-9944-9