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Proceedings Paper

Estimating catechin concentrations of new shoots in the green tea field using ground-based hyperspectral image
Author(s): C. S. Ryu; M. Suguri; S. B. Park; M. Mikio
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Paper Abstract

Hyperspectral camera was applied to establish the models of catechin concentration for green tea. The possibility of improvement for the models was checked by the multi-year models and the mutual prediction. ECg, EGCg and the ester catechin (ECg and EGCg) decreased with the growth but EC, EGC and the free catechin (EC and EGC) were changed by the covering. In partial least square regression (PLSR) models for each catechin, R2 (Relative Error for validation) was more than 0.785 (13.4%) for a single year data, 0.723 (13.3%) for two years data, and 0.756 (13.6%) for three years data except several catechins. It was possible to improve the precision and accuracy of models using the combination of catechin (free and ester type) or the combination of multi-year data. When each and each type of catechin model was predicted by the other year data, the accuracy of two years model improved comparing with it of a single year data. It means that the multi-year models might be more accurate than a single year models to predict the unknown data.

Paper Details

Date Published: 16 October 2013
PDF: 8 pages
Proc. SPIE 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV, 88871Q (16 October 2013); doi: 10.1117/12.2029380
Show Author Affiliations
C. S. Ryu, Gyeongsang National Univ. (Korea, Republic of)
M. Suguri, Kyoto Univ. (Japan)
S. B. Park, Kyoto Univ. (Japan)
M. Mikio, Kyoto Univ. (Japan)

Published in SPIE Proceedings Vol. 8887:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XV
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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