TY - JOUR
T1 - Reflectance spectroscopy of biochemical components as indicators of tea (Camellia sinensis) quality
AU - Bian, Meng
AU - Skidmore, Andrew K.
AU - Schlerf, Martin
AU - Fei, Teng
AU - Liu, Yanfang
AU - Wang, Tiejun
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=80052466800&partnerID=8YFLogxK
U2 - 10.14358/PERS.76.12.1385
DO - 10.14358/PERS.76.12.1385
M3 - Review article
AN - SCOPUS:80052466800
SN - 0099-1112
VL - 76
SP - 1385
EP - 1392
JO - Photogrammetric Engineering and Remote Sensing
JF - Photogrammetric Engineering and Remote Sensing
IS - 12
ER -