Reflectance spectroscopy of biochemical components as indicators of tea (Camellia sinensis) quality

Photogrammetric Engineering and Remote Sensing

Volumn 76, Issue 12, 2010, Pages 1385-1392

  Bian, Meng ^a   Skidmore, Andrew K ^a,c   Schlerf, Martin ^a   Fei, Teng ^a   Liu, Yanfang ^b   Wang, Tiejun ^a  

^a UNIVERSITY OF TWENTE   (Netherlands)

^b WUHAN UNIVERSITY   (China)

^c WAGENINGEN UNIVERSITY   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACIDS; LEAST SQUARES APPROXIMATIONS; POWDERS; REFLECTION; REMOTE SENSING; SPECTROSCOPY;

ABSORPTION FEATURES; BIO-CHEMICAL COMPOUNDS; BIOCHEMICAL COMPONENTS; HYPERSPECTRAL REMOTE SENSING; PARTIAL LEAST SQUARES REGRESSIONS (PLSR); REFLECTANCE SPECTROSCOPY; ROOT MEAN SQUARE ERRORS; ROUTINE MONITORING;

MEAN SQUARE ERROR;

ABSORPTION; ACCURACY ASSESSMENT; AMINO ACID; BIOCHEMISTRY; CONCENTRATION (COMPOSITION); ERROR ANALYSIS; FOOD QUALITY; LEAST SQUARES METHOD; PHENOLIC COMPOUND; REFLECTANCE; REGRESSION ANALYSIS; REMOTE SENSING; TEA; WAVELENGTH;

CAMELLIA SINENSIS;

EID: 80052466800     PISSN: 00991112     EISSN: None     Source Type: Journal    
DOI: 10.14358/PERS.76.12.1385     Document Type: Review

References (51)

1. Adam, E., O. Mutanga, and D. Rugege, 2010. Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: A review, Wetlands Ecology and Management, 18(3)281-296.
2. Beeri, O., R. Phillips, J. Hendrickson, A.B. Frank, and S. Kronberg, 2007. Estimating forage quantity and quality using aerial hyperspectral imagery for northern mixed-grass prairie, Remote Sensing of Environment, 110(2):216-225. (Pubitemid 47176064)
3. Candolfi, A., R. De Maesschalck, D. Jouan-Rimbaud, P.A. Hailey, and D.L. Massart, 1999. The influence of data pre-processing in the pattern recognition of excipients near-infrared spectra, Journal of Pharmaceutical and Biomedical Analysis, 21(1): 115-132. (Pubitemid 29430148)
4. 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, Microchemical Journal, 83(1):42-47.
5. Chen, Q., J. Zhao, M. Liu, J. Cai, and J. Liu, 2008a. Determination of total polyphenols content in green tea using FT-NIR spectroscopy and different PLS algorithms, Journal of Pharmaceutical and Biomedical Analysis, 46(3):568-573.
6. Chen, Q., J. Zhao, and S. Vittayapadung, 2008b. Identification of the green tea grade level using electronic tongue and pattern recognition, Food Research International, 41(5):500-504.
7. Cho, M.A., A. Skidmore, F. Corsi, S.E. van Wieren, and I. Sobhan, 2007. Estimation of green grass/herb biomass from airborne hyperspectral imagery using spectral indices and partial least squares regression, International Journal of Applied Earth Observation and Geoinformation, 9(4):414-424. (Pubitemid 350124094)
8. Cho, M.A., and A.K. Skidmore, 2006. A new technique for extracting the red edge position from hyperspectral data: The linear extrapolation method, Remote Sensing of Environment, 101(2):181-193. (Pubitemid 43343901)
9. Chu, D.C., T. Okubo, Y. Nagato, and H. Yokogoshi, 1999. L-theanine - A unique amino acid of green tea and its relaxation effect in humans, Trends in Food Science and Technology, 10(6-7):199-204.
10. Curran, P.J., 1989. Remote sensing of foliar chemistry, Remote Sensing of Environment, 30(3):271-278.
11. Curran, P.J., J.L. Dungan, and D.L. Peterson, 2001. Estimating the foliar biochemical concentration of leaves with reflectance spectrometry: Testing the Kokaly and Clark methodologies, Remote Sensing of Environment, 76(3):349-359. (Pubitemid 32532579)
12. Darvishzadeh, R., A. Skidmore, C. Atzberger, and S. van Wieren, 2008a. Estimation of vegetation LAI from hyperspectral reflectance data: Effects of soil type and plant architecture, International Journal of Applied Earth Observation and Geoinformation, 10(3):358-373.
13. Darvishzadeh, R., A. Skidmore, M. Schlerf, C. Atzberger, F. Corsi, and M. Cho, 2008b. LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements, ISPRS Journal of Photogrammetry and Remote Sensing, 63(4):409-426.
14. Demetriades-Shah, T.H., M.D. Steven, and J.A. Clark, 1990. High resolution derivative spectra in remote sensing, Remote Sensing of Environment, 33(1):55-64.
15. Duckworth, J.H., 1998. Spectroscopic Quantitative Analysis, Applied Spectroscopy: A Compact Reference for Parishioners (J. Workman and A.W. Springsteen, editors), Academic Press, San Diego and Chestnut Hill, USA, pp. 166-176.
16. Ferwerda, J.G., and A.K. Skidmore, 2007. Can nutrient status of four woody plant species be predicted using field spectrometry?, ISPRS Journal of Photogrammetry and Remote Sensing, 62(6):406-414. (Pubitemid 350137725)
17. Ferwerda, J.G., A.K. Skidmore, and A. Stein, 2006a. A bootstrap procedure to select hyperspectral wavebands related to tannin content, International Journal of Remote Sensing, 27(7):1413-1424. (Pubitemid 43738938)
18. Ferwerda, J.G., A.K. Skidmore, S.E. Van Wieren, and H.H.T. Prins, 2006b. Soil N and P affected reflectance signatures of individual Colophospermum mopane leaves, Journal of Spatial Science, 51(2):103-113. (Pubitemid 46152327)
19. Gomez, C., P. Lagacherie, and G. Coulouma, 2008. Continuum removal versus PLSR method for clay and calcium carbonate content estimation from laboratory and airborne hyperspectral measurements, Geoderma, 148(2):141-148.
20. Iwasa, K., and H. Torii, 1962. A colorimetric determination of tea tannin with ferrous tartrate, Study of Tea, 26(1):87-91.
21. Kokaly, R.F., G.P. Asner, S.V. Ollinger, M.E. Martin, and C.A. Wessman, 2009. Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies, Remote Sensing of Environment, 113(SUPPL. 1): S78-S91.
22. Lee, K.S., M.J. Kook, J.I. Shin, S.H. Kim, and T.G. Kim, 2007. Spectral characteristics of forest vegetation in moderate drought condition observed by laboratory measurements and spaceborne hyperspectral data, Photogrammetric Engineering & Remote Sensing, 73(10):1121-1127.
23. Liang, Y.R., Q. Ye, J. Jin, H. Liang, J.L. Lu, Y.Y. Du, and J.J. Dong, 2008. Chemical and instrumental assessment of green tea sensory preference, International Journal of Food Properties, 11(2):258-272. (Pubitemid 351585295)
24. Lu, Y., H. Chen, J. Lv, and X. Chen, 2005. Near-infrared determination of catechin in tea Polyphenol, Chinese Journal of Analytical Chemistry, 33(6):835-837. (Pubitemid 41215115)
25. Luypaert, J., M.H. Zhang, and D.L. Massart, 2003. Feasibility study for the use of near-infrared spectroscopy in the qualitative and quantitative analysis of green tea, Camellia sinensis (L.), Analytica Chimica Acta, 478(2):303-312. (Pubitemid 36126452)
26. Majeke, B., J.A.N. Van Aardt, and M.A. Cho, 2008. Imaging spectroscopy of foliar biochemistry in forestry environments, Southern Forests, 70(3):275-285.
27. Marcoulides, G.A., and C. Saunders, 2006. PLS: A silver bullet?, MIS Quarterly: Management Information Systems, 30(2):III-IV.
28. Mutanga, O., and A.K. Skidmore, 2004. Hyperspectral band depth analysis for a better estimation of grass biomass (Cenchrus ciliaris) measured under controlled laboratory conditions, International Journal of Applied Earth Observation and Geoinformation, 5(2):87-96. (Pubitemid 38503290)
29. Mutanga, O., A.K. Skidmore, and H.H.T. Prins, 2004a. Discriminating sodium concentration in a mixed grass species environment of the Kruger National Park using field spectrometry, International Journal of Remote Sensing, 25(20):4191-4201. (Pubitemid 39403746)
30. Mutanga, O., A.K. Skidmore, and H.H.T. Prins, 2004b. Predicting in situ pasture quality in the Kruger National Park, South Africa, using continuum-removed absorption features, Remote Sensing of Environment, 89(3):393-408. (Pubitemid 38178910)
31. Norris, K.H., R.F. Barnes, J.E. Moore, and J.S. Shenk, 1976. Predicting forage quality by infrared reflectance spectroscopy, Journal of Animal Science, 43(4):839-878.
32. Obanda, M., P.O. Owuor, and S.J. Taylor, 1997. Flavanol composition and caffeine content of green leaf as quality potential indicators of Kenyan black teas, Journal of the Science of Food and Agriculture, 74(2):209-215. (Pubitemid 27347397)
33. Osborne, B., and T. Fearn, 1986. Near-infrared Spectroscopy in Food Analysis, Longman Scientific and Technical, London, 200 p.
34. Peng, Y., W. Wang, H. Huang, X. Wang, and X. Gao, 2009, Prediction of chlorophyll content of winter wheat using leaf-level hyperspectral imaging data, Proceedings of the American Society of Agricultural and Biological Engineers Annual International Meeting 2009, pp. 3756-3766.
35. Ravichandran, R., and R. Parthiban, 2000. Lipid occurrence, distribution and degradation to flavour volatiles during tea processing, Food Chemistry, 68(1):7-13. (Pubitemid 29488671)
36. Rossel, R.A.V., 2008. ParLeS: Software for chemometric analysis of spectroscopic data, Chemometrics and Intelligent Laboratory Systems, 90(1):72-83.
37. Savitzky, A., and M.J.E. Golay, 1964. Smoothing and differentiation of data by simplified least squares procedures, Analytical Chemistry, 36(8):1627-1639.
38. Schlerf, M., C. Atzberger, and J. Hill, 2005. Remote sensing of forest biophysical variables using HyMap imaging spectrometer data, Remote Sensing of Environment, 95(2):177-194. (Pubitemid 40328612)
39. Schlerf, M., C. Atzberger, J. Hill, H. Buddenbaum, W. Werner, and G. Schüler, 2010. Retrieval of chlorophyll and nitrogen in Norway spruce (Picea abies L. Karst.) using imaging spectroscopy. International Journal of Applied Earth Observation and Geoinformation, 12(1):17-26.
40. Schulz, H., U.H. Engelhardt, A. Wegent, H.H. Drews, and S. Lapczynski, 1999. Application of near-infrared reflectance spectroscopy to the simultaneous prediction of alkaloids and phenolic substances in green tea leaves, Journal of Agricultural and Food Chemistry, 47(12):5064-5067. (Pubitemid 30016939)
41. Sharangi, A.B., 2009. Medicinal and therapeutic potentialities of tea (Camellia sinensis L.) - A Review, Food Research International, 42(5-6):529-535.
42. Skidmore, A.K., J.G. Ferwerda, O. Mutanga, S.E. Van Wieren, M. Peel, R.C. Grant, H.H.T. Prins, F.B. Balcik, and V. Venus, 2010. Forage quality of savannas - Simultaneously mapping foliar protein and polyphenols for trees and grass using hyperspectral imagery, Remote Sensing of Environment, 114(1):64-72.
43. Soukupova, J., 2002. Spectral characteristics of lignin and soluble phenolics in the near-infrared-a comparative study, International Journal of Remote Sensing, 23(15):3039-3055. (Pubitemid 34834596)
44. Stagakis, S., N. Markos, O. Sykioti, and A. Kyparissis, 2010. Monitoring canopy biophysical and biochemical parameters in ecosystem scale using satellite hyperspectral imagery: An application on a Phlomis fruticosa Mediterranean ecosystem using multiangular CHRIS/PROBA observations, Remote Sensing of Environment, 114(5):977-994.
45. Thomas, J., A.K.A. Mandal, R.R. Kumar, and A. Chordia, 2009. Role of biologically active amino acid formulations on quality and crop productivity of tea (Camellia sp.), International Journal of Agricultural Research, 4(7):228-236.
46. Wang, Y., F. Wang, J. Huang, X. Wang, and Z. Liu, 2009. Validation of artificial neural network techniques in the estimation of nitrogen concentration in rape using canopy hyperspectral reflectance data, International Journal of Remote Sensing, 30(17):4493-4505.
47. Wessman, C.A., J.D. Aber, and D.L. Peterson, 1989. An evaluation of imaging spectrometry for estimating forest canopy chemistry, International Journal of Remote Sensing, 10(8):1293-1316.
48. Williams, P., and K. Norris, 1987. Near-infrared Technology in the Agricultural and Food Industries, American Association of Cereal Chemists, St. Paul, Minnesota, 330 p.
49. Willson, K.C., and M.N. Clifford, 1992. Tea: Cultivation to Consumption, Chapman & Hall, 769 p.
50. Yamamoto, T., L.R. Juneja, D.C. Chu, and M. Kim, 1997. Chemistry and Applications of Green Tea, CRC Press, 176 p.
51. Yan, S.H., 2007. NIR evaluation of the quality of tea and its market price, Spectroscopy Europe, 19(2):16-19.