Estimating catechin concentrations of new shoots in the green tea field using ground-based hyperspectral image

C. S. Ryu; M. Suguri; S. B. Park; M. Mikio

doi:10.1117/12.2029380

16 October 2013 Estimating catechin concentrations of new shoots in the green tea field using ground-based hyperspectral image

C. S. Ryu, M. Suguri, S. B. Park, M. Mikio

Author Affiliations +

Proceedings Volume 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV; 88871Q (2013) https://doi.org/10.1117/12.2029380
Event: SPIE Remote Sensing, 2013, Dresden, Germany

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.

Citation Download Citation

C. S. Ryu, M. Suguri, S. B. Park, and M. Mikio "Estimating catechin concentrations of new shoots in the green tea field using ground-based hyperspectral image", Proc. SPIE 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV, 88871Q (16 October 2013); https://doi.org/10.1117/12.2029380

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