Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 413336
Title Reflectance spectroscopy of biochemical components as indicators of tea, Camellia Sinensis, quality
Author(s) Bian, B.M.; Skidmore, A.K.; Schlerf, M.; Fei, T.; Liu, Y.F.; Wang, T.
Source Photogrammetric Engineering and Remote Sensing 76 (2010)12. - ISSN 0099-1112 - p. 1385 - 1392.
Department(s) Resource Ecology
Publication type Refereed Article in a scientific journal
Publication year 2010
Keyword(s) kruger-national-park - green tea - hyperspectral measurements - spectral characteristics - pattern-recognition - field spectrometry - total polyphenols - vegetation - chemistry - imagery
Abstract The potential of reflectance spectroscopy to estimate the concentration of biochemical compounds related to tea (Camellia sinensis (L.)) quality (total tea polyphenols and free amino acids) is demonstrated. Partial least squares regression (PLSR) was performed to establish the relationship between reflectance and biochemicals for leaf powders as well as fresh leaves. Highest accuracy was found for tea powders with a cross-validated r2 of 0.97 for tea polyphenols and 0.99 for free amino acids, and the root mean square error of cross validations (RMSECVS) are 8.36 mg g-1 and 1.01 mg g-1 for the two chemicals. The accuracy achieved at leaf level was slightly lower, with results yielding cross-validated r2 of 0.91 and 0.93 with RMSECVS of 13.74 mg g-1 and 2.32 mg g-1 for tea polyphenols and free amino acids, respectively. Important wavelengths for prediction of the two biochemicals from powder and leaf spectra were identified using the PLSR bcoefficients as indicators. Wavelengths of 1,131 nm, 1,654 nm, 1,666 nm, 1,738 nm and 1,752 nm were identified as bands related to absorption by total tea polyphenols, while 1,492 nm represented the absorption feature of free amino acids. The results obtained using fresh leaves indicate that hyperspectral remote sensing may be useful for routine monitoring of tea chemistry at landscape scale.
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