Hi, I am Quansheng Chen, My LiveDNA is 86.10368
 
   
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Dr. Quansheng Chen
 
Highest Degree: Ph.D. in Food Science and Engineering from Jiangsu University, China
 
Institute: Jiangsu University, China
 
Area of Interest: Food Science Technology
  •   Analytical Chemistry
  •   Biosensors
  •   Chemometrics
  •   Food Safety
 
URL: http://livedna.org/86.10368
 
My SELECTED Publications
1:   Cai, J., Q. Chen, X. Wan and J. Zhao, 2011. Determination of total volatile basic nitrogen (TVB-N) content and Warner-Bratzler Shear Force (WBSF) in pork using Fourier Transform Near Infrared (FT-NIR) spectroscopy. Food Chem., 126: 1354-1360.
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2:   Cao, Y., C. Zhang, Q. Chen, Y. Li, S. Qi, L. Tian and Y. Ren, 2015. Identification of species and geographical strains of Sitophilus oryzae and Sitophilus zeamais using the visible/near-infrared hyperspectral imaging technique. Pest Manage. Sci., 71: 1113-1121.
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3:   Chen, Q., A. Liu, J. Zhao and Q. Ouyang, 2013. Classification of tea category using a portable electronic nose based on an odor imaging sensor array. J. Pharm. Biomed. Anal., 84: 77-83.
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4:   Chen, Q., A. Liu, J. Zhao, Q. Ouyang, Z. Sun and L. Huang, 2013. Monitoring vinegar acetic fermentation using a colorimetric sensor array. Sens. Actuat. B: Chem., 183: 608-616.
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5:   Chen, Q., C. Sun, Q. Ouyang, A. Liu, H. Li and J. Zhao, 2014. Classification of vinegar with different marked ages using olfactory sensors and gustatory sensors. Anal. Methods, 6: 9783-9790.
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6:   Chen, Q., C. Sun, Q. Ouyang, Y. Wang, A. Liu, H. Li and J. Zhao, 2015. Classification of different varieties of Oolong tea using novel artificial sensing tools and data fusion. LWT-Food Sci. Technol., 60: 781-787.
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7:   Chen, Q., C. Zhang, J. Zhao and Q. Ouyang, 2013. Recent advances in emerging imaging techniques for non-destructive detection of food quality and safety. Trends Anal. Chem., 52: 261-274.
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8:   Chen, Q., D. Zhang, W. Pan, Q. Ouyang, H. Li, K. Urmila and J. Zhao, 2015. Recent developments of green analytical techniques in analysis of teas quality and nutrition. Trends Food Sci. Technol., 43: 63-82.
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9:   Chen, Q., H. Li, Q. Ouyang and J. Zhao, 2014. Identification of spoilage bacteria using a simple colorimetric sensor array. Sens. Actuat. B: Chem., 205: 1-8.
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10:   Chen, Q., J. Cai, X. Wan and J. Zhao, 2011. Application of linear/non-linear classification algorithms in discrimination of pork storage time using Fourier transform near infrared (FT-NIR) spectroscopy. LWT-Food Sci. Technol., 44: 2053-2058.
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11:   Chen, Q., J. Ding, J. Cai and J. Zhao, 2012. Rapid measurement of total acid content (TAC) in vinegar using near infrared spectroscopy based on efficient variables selection algorithm and nonlinear regression tools. Food Chem., 135: 590-595.
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12:   Chen, Q., J. Ding, J. Cai, Z. Sun and J. Zhao, 2012. Simultaneous measurement of total acid content and soluble salt‐free solids content in Chinese vinegar using near‐infrared spectroscopy. J. Food Sci., 77: C222-C227.
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13:   Chen, Q., J. Zhao and H. Lin, 2009. Study on discrimination of Roast green tea (Camellia sinensis L.) according to geographical origin by FT-NIR spectroscopy and supervised pattern recognition. Spectrochim. Acta Part A: Mol. Biomol. Spectrosc., 72: 845-850.
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14:   Chen, Q., J. Zhao and J. Cai, 2008. Identification of tea varieties using computer vision. Trans. ASABE, 51: 623-628.
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15:   Chen, Q., J. Zhao and S. Vittayapadung, 2008. Identification of the green tea grade level using electronic tongue and pattern recognition. Food Res. Int., 41: 500-504.
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16:   Chen, Q., J. Zhao, C.H. Fang and D. Wang, 2007. Feasibility study on identification of green, black and Oolong teas using near-infrared reflectance spectroscopy based on Support Vector Machine (SVM). Spectrochim. Acta Part A: Mol. Biomol. Spectrosc., 66: 568-574.
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17:   Chen, Q., J. Zhao, H. Zhang and X. Wang, 2006. Feasibility study on qualitative and quantitative analysis in tea by near infrared spectroscopy with multivariate calibration. Analytica Chimica Acta, 572: 77-84.
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18:   Chen, Q., J. Zhao, H. Zhang, L. Muhua and M. Fang, 2005. Qualitative identification of tea by near infrared spectroscopy based on soft independent modelling of class analogy pattern recognition. J. Near Infrared Spectrosc., 13: 327-332.
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19:   Chen, Q., J. Zhao, M. Liu and J. Cai, 2008. Nondestructive identification of tea (Camellia sinensis L.) varieties using FT-NIR spectroscopy and pattern recognition. Czech J. Food Sci., 26: 360-367.
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20:   Chen, Q., J. Zhao, M. Liu, J. Cai and J. Liu, 2008. Determination of total polyphenols content in green tea using FT-NIR spectroscopy and different PLS algorithms. J. Pharm. Biomed. Anal., 46: 568-573.
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21:   Chen, Q., J. Zhao, S. Chaitep and Z. Guo, 2009. Simultaneous analysis of main catechins contents in green tea (Camellia sinensis (L.)) by Fourier transform near infrared reflectance (FT-NIR) spectroscopy. Food Chem., 113: 1272-1277.
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22:   Chen, Q., J. Zhao, X. Huang, H. Zhang and M. Liu, 2006. Simultaneous determination of total polyphenols and caffeine contents of green tea by near-infrared reflectance spectroscopy. Microchem. J., 83: 42-47.
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23:   Chen, Q., J. Zhao, Z. Chen, H. Lin and D.A. Zhao, 2011. Discrimination of green tea quality using the electronic nose technique and the human panel test, comparison of linear and nonlinear classification tools. Sens. Actuat. B: Chem., 159: 294-300.
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24:   Chen, Q., J. Zhao, Z. Guo and X. Wang, 2010. Determination of caffeine content and main catechins contents in green tea (Camellia sinensis L.) using taste sensor technique and multivariate calibration. J. Food Compos. Anal., 23: 353-358.
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25:   Chen, Q., P. Jiang and J. Zhao, 2010. Measurement of total flavone content in snow lotus (Saussurea involucrate) using near infrared spectroscopy combined with interval PLS and genetic algorithm. Spectrochim. Acta Part A: Mol. Biomol. Spectrosc., 76: 50-55.
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26:   Chen, Q., S. Qi, H. Li, X. Han, Q. Ouyang and J. Zhao, 2014. Determination of rice syrup adulterant concentration in honey using three-dimensional fluorescence spectra and multivariate calibrations. Spectrochim. Acta Part A: Mol. Biomol. Spectrosc., 131: 177-182.
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27:   Chen, Q., Y. Zhang, J. Zhao and Z. Hui, 2013. Nondestructive measurement of total volatile basic nitrogen (TVB-N) content in salted pork in jelly using a hyperspectral imaging technique combined with efficient hypercube processing algorithms. Anal. Methods, 5: 6382-6388.
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28:   Chen, Q., Z. Guo and J. Zhao, 2008. Identification of green tea’s (Camellia sinensis (L.)) quality level according to measurement of main catechins and caffeine contents by HPLC and support vector classification pattern recognition. J. Pharm. Biomed. Anal., 48: 1321-1325.
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29:   Chen, Q., Z. Guo, J. Zhao and Q. Ouyang, 2012. Comparisons of different regressions tools in measurement of antioxidant activity in green tea using near infrared spectroscopy. J. Pharm. Biomed. Anal., 60: 92-97.
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30:   Chen, Q., Z. Hui, J. Zhao and Q. Ouyang, 2014. Evaluation of chicken freshness using a low-cost colorimetric sensor array with AdaBoost-OLDA classification algorithm. LWT-Food Sci. Technol., 57: 502-507.
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31:   Chen, Q.S., Z.M. Guo, J.W. Zhao and Q. Ouyang, 2009. Quantitative analysis of the catechins contents in green tea with near infrared spectroscopy and net analyte preprocessing algorithm. J. Infrared Millimeter Waves, 28: 357-361.
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32:   Guo, Z., Q. Chen, L. Chen, W. Huang, C. Zhang and C. Zhao, 2011. Optimization of informative spectral variables for the quantification of EGCG in green tea using Fourier transform near-infrared (FT-NIR) spectroscopy and multivariate calibration. Applied Spectrosc., 65: 1062-1067.
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33:   Huang, L., J. Zhao, Q. Chen and Y. Zhang, 2013. Rapid detection of Total Viable Count (TVC) in pork meat by hyperspectral imaging. Food Res. Int., 54: 821-828.
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34:   Huang, L., J. Zhao, Q. Chen and Y. Zhang, 2014. Nondestructive measurement of total volatile basic nitrogen (TVB-N) in pork meat by integrating near infrared spectroscopy, computer vision and electronic nose techniques. Food Chem., 145: 228-236.
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35:   Huang, L., J. Zhao, Y. Zhang and Q. Chen, 2012. Simultaneous multi-component analysis of pork meat during bacterial spoiling process by FT-NIR evaluated with a non-linear algorithm. Anal. Methods, 4: 3816-3823.
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36:   Huang, Q., Q. Chen, H. Li, G. Huang, Q. Ouyang and J. Zhao, 2015. Non-destructively sensing porks freshness indicator using near infrared multispectral imaging technique. J. Food Eng., 154: 69-75.
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37:   Jiang, H. and Q. Chen, 2014. Development of electronic nose and near infrared spectroscopy analysis techniques to monitor the critical time in SSF process of feed protein. Sensors, 14: 19441-19456.
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38:   Jiang, H. and Q. Chen, 2015. Chemometric models for the quantitative descriptive sensory properties of green tea (Camellia sinensis L.) using fourier transform near infrared (FT-NIR) spectroscopy. Food Anal. Methods, 8: 954-962.
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39:   Jiang, H., G. Liu, C. Mei and Q. Chen, 2013. Qualitative and quantitative analysis in solid-state fermentation of protein feed by FT-NIR spectroscopy integrated with multivariate data analysis. Anal. Methods, 5: 1872-1880.
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40:   Jiang, H., H. Zhang, Q. Chen, C. Mei and G. Liu, 2015. Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS. Spectrochim. Acta Part A: Mol. Biomol. Spectrosc., 149: 1-7.
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41:   Jiang, H., Q. Chen and G. Liu, 2014. Monitoring of solid-state fermentation of protein feed by electronic nose and chemometric analysis. Process Biochem., 49: 583-588.
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42:   Li, H., Q. Chen, J. Zhao and K. Urmila, 2015. Enhancing the antimicrobial activity of natural extraction using the synthetic ultrasmall metal nanoparticles. Scient. Rep., Vol. 5. 10.1038/srep11033.
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43:   Li, H., Q. Chen, J. Zhao and M. Wu, 2015. Nondestructive detection of total volatile basic nitrogen (TVB-N) content in pork meat by integrating hyperspectral imaging and colorimetric sensor combined with a nonlinear data fusion. LWT-Food Sci. Technol., 63: 268-274.
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44:   Li, H., Q. Chen, J. Zhao and Q. Ouyang, 2014. Non-destructive evaluation of pork freshness using a portable electronic nose (E-nose) based on a colorimetric sensor array. Anal. Methods, 6: 6271-6277.
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45:   Lin, H., J. Zhao and Q. Chen, 2010. Eggshell crack detection based on acoustic impulse response combined with kernel independent component analysis and back propagation neural network. Intel. Automat. Soft Comput., 16: 1043-1050.
46:   Lin, H., J. Zhao, L. Sun, Q. Chen and F. Zhou, 2011. Freshness measurement of eggs using near infrared (NIR) spectroscopy and multivariate data analysis. Innov. Food Sci. Emerg. Technol., 12: 182-186.
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47:   Lin, H., J. Zhao, Q. Chen, F. Zhou and L. Sun, 2011. Discrimination of Radix Pseudostellariae according to geographical origins using NIR spectroscopy and support vector data description. Spectrochim. Acta Part A: Mol. Biomol. Spectrosc., 79: 1381-1385.
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48:   Lin, H., J.W. Zhao, L. Sun, Q.S. Chen, Z. Sun and F. Zhou, 2011. Stiffness measurement of eggshell by acoustic resonance and PLS models. J. Food Eng., 103: 351-356.
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49:   Lin, H., J.W. Zhao, Q.S. Chen, J.R. Cai and P. Zhou, 2009. Eggshell crack detection based on acoustic impulse response and supervised pattern recognition. Czech J. Food Sci., 27: 393-402.
50:   Lin, H., J.W. Zhao, Q.S. Chen, J.R. Cai and P. Zhou, 2009. Eggshell crack detection based on acoustic response and support vector data description algorithm. Eur. Food Res. Technol., 230: 95-100.
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51:   Lin, H., J.W. Zhao, Q.S. Chen, J.R. Cai and P. Zhou, 2010. Identification of egg freshness using near infrared spectroscopy and one class support vector machine algorithm. Spectrosc. Spectral Anal., 30: 929-932.
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52:   Lin, H., Q. Chen, J. Zhao and P. Zhou, 2009. Determination of free amino acid content in Radix Pseudostellariae using near infrared (NIR) spectroscopy and different multivariate calibrations. J. Pharm. Biomed. Anal., 50: 803-808.
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53:   Lue, Q., M.J. Tang, J.W. Zhao, J.R. Cai and Q.S. Chen, 2009. Study of simplification of prediction model for kiwifruit firmness using near infrared spectroscopy. Spectrosc. Spectral Anal., 29: 1768-1771.
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54:   Ou‐Yang, Q., J.W. Zhao, Q.S. Chen, H. Lin and X.Y. Huang, 2011. Study on classification of soy sauce by electronic tongue technique combined with artificial neural network. J. Food Sci., 76: S523-S527.
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55:   Ouyang, Q., J. Zhao and Q. Chen, 2013. Classification of rice wine according to different marked ages using a portable multi-electrode electronic tongue coupled with multivariate analysis. Food Res. Int., 51: 633-640.
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56:   Ouyang, Q., J. Zhao and Q. Chen, 2014. Instrumental intelligent test of food sensory quality as mimic of human panel test combining multiple cross-perception sensors and data fusion. Anal. Chim. Acta, 841: 68-76.
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57:   Ouyang, Q., J. Zhao and Q. Chen, 2015. Measurement of non-sugar solids content in Chinese rice wine using near infrared spectroscopy combined with an efficient characteristic variables selection algorithm. Spectrochim. Acta Part A: Mol. Biomol. Spectrosc., 151: 280-285.
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58:   Ouyang, Q., J. Zhao, Q. Chen and H. Lin, 2013. Classification of rice wine according to different marked ages using a novel artificial olfactory technique based on colorimetric sensor array. Food Chem., 138: 1320-1324.
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59:   Ouyang, Q., J. Zhao, Q. Chen, H. Lin and Z. Sun, 2012. Rapid measurement of antioxidant activity in dark soy sauce by NIR spectroscopy combined with spectral intervals selection and nonlinear regression tools. Anal. Methods, 4: 940-946.
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60:   Ouyang, Q., J. Zhao, W. Pan and Q. Chen, 2016. Real-time monitoring of process parameters in rice wine fermentation by a portable spectral analytical system combined with multivariate analysis. Food Chem., 190: 135-141.
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61:   Ouyang, Q., Q. Chen, J. Zhao and H. Lin, 2013. Determination of amino acid nitrogen in soy sauce using near infrared spectroscopy combined with characteristic variables selection and extreme learning machine. Food Bioprocess Technol., 6: 2486-2493.
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62:   Pan, W., J. Zhao and Q. Chen, 2015. Classification of foodborne pathogens using near infrared (NIR) laser scatter imaging system with multivariate calibration. Scient. Rep., Vol. 5. 10.1038/srep09524.
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63:   Pan, W., J. Zhao, Q. Chen and D. Zhang, 2015. Simultaneous and rapid measurement of main compositions in black tea infusion using a developed spectroscopy system combined with multivariate calibration. Food Anal. Methods, 8: 749-757.
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64:   Pan, W., J. Zhao, Q. Chen and L. Yuan, 2015. In situ monitoring of total polyphenols content during tea extract oxidation using a portable spectroscopy system with variables selection algorithms. RSC Adv., 5: 60876-60883.
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65:   Qi, S., Q. Ouyang, Q. Chen and J. Zhao, 2014. Real-time monitoring of total polyphenols content in tea using a developed optical sensors system. J. Pharm. Biomed. Anal., 97: 116-122.
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66:   Teye, E., X. Huang, H. Dai and Q. Chen, 2013. Rapid differentiation of Ghana cocoa beans by FT-NIR spectroscopy coupled with multivariate classification. Spectrochim. Acta Part A: Mol. Biomol. Spectrosc., 114: 183-189.
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67:   Urmila, K., H. Li, Q. Chen, Z. Hui and J. Zhao, 2015. Quantifying of total volatile basic nitrogen (TVB-N) content in chicken using a colorimetric sensor array and nonlinear regression tool. Anal. Methods, 7: 5682-5688.
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68:   Vittayapadung, S., J. Zhao, Q. Chen and R. Chuaviroj, 2008. Application of FT-NIR spectroscopy to the measurement of fruit firmness of Fuji apples. Maejo Int. J. Sci. Technol., 2: 13-23.
69:   Wu, R.M., J.W. Zhao, Q.S. Chen and X.Y. Huang, 2011. Determination of taste quality of green tea using FT-NIR spectroscopy and variable selection methods. Spectrosc. Spectral Anal., 31: 1782-1785.
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70:   Xu, Y., H. Li, Q. Chen, J. Zhao and Q. Ouyang, 2015. Rapid detection of adulteration in extra-virgin olive oil using three-dimensional fluorescence spectra technology with selected multivariate calibrations. Int. J. Food Properties, 18: 2085-2098.
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71:   Zhao, J., H. Lin, Q. Chen, X. Huang, Z. Sun and F. Zhou, 2010. Identification of egg’s freshness using NIR and support vector data description. J. Food Eng., 98: 408-414.
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72:   Zhao, J., Q. Chen, J. Cai and Q. Ouyang, 2009. Automated tea quality classification by hyperspectral imaging. Applied Optics, 48: 3557-3564.
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73:   Zhao, J., Q. Chen, X. Huang and C.H. Fang, 2006. Qualitative identification of tea categories by near infrared spectroscopy and support vector machine. J. Pharm. Biomed. Anal., 41: 1198-1204.
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74:   Zhao, J., Q. Ouyang, Q. Chen and H. Lin, 2013. Simultaneous determination of amino acid nitrogen and total acid in soy sauce using near infrared spectroscopy combined with characteristic variables selection. Food Sci. Technol. Int., 19: 305-314.
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75:   Zhao, J., Q. Ouyang, Q. Chen and J. Wang, 2010. Detection of bruise on pear by hyperspectral imaging sensor with different classification algorithms. Sens. Lett., 8: 570-576.
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76:   Zhao, J., S. Vittayapadung, Q. Chen, S. Chaitep and R. Chuaviroj, 2009. Nondestructive measurement of sugar content of apple using hyperspectral imaging technique. Maejo Int. J. Sci. Technol., 3: 130-142.
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77:   Zhao, J.W., K.L. Wang, Q. Ouyang and Q.S. Chen, 2011. Measurement of chlorophyll content and distribution in tea plants leaf using hyperspectral imaging technique. Spectrosc. Spectral Anal., 31: 512-515.
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78:   Zhao, J.W., Q.S. Chen, H.D. Mang and M.H. Liu, 2006. [Study on the identification of tea using near infrared reflectance spectroscopy]. Spectrosc. Spectral Anal., 26: 1601-1604, (In Chinese).
PubMed  |  
79:   Zhao, J.W., X.Y. Han, Q.S. Chen and Q. Ouyang, 2013. Identification of adulterated honey based on three-dimensional fluorescence spectra technology. Spectrosc. Spectral Anal., 3: 1626-1630.
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