Abstract

In the present study, the high-speed quantitative evaluation of glycogen concentration accumulated in bioethanol feedstock Synechocystis sp. PCC6803 was performed using a near-infrared (NIR) imaging system with a hyperspectral NIR spectral camera named Compovision. The NIR imaging system has a feature for high-speed and wide area monitoring and the two-dimensional scanning speed is almost 100 times faster than the general NIR imaging systems for the same pixel size. For the quantitative analysis of glycogen concentration, partial least squares regression (PLSR) and moving window PLSR (MWPLSR) were performed with the information of glycogen concentration measured by high performance liquid chromatography (HPLC) and the calibration curves for the concentration within the Synechocystis sp. PCC6803 cell were constructed. The results had high accuracy for the quantitative estimation of glycogen concentration as the best squared correlation coefficient R2 was bigger than 0.99 and a root mean square error (RMSE) was less than 2.9%. The present results proved not only the potential for the applicability of NIR spectroscopy to the high-speed quantitative evaluation of glycogen concentration in the bioethanol feedstock but also the expansivity of the NIR imaging instrument to in-line or on-line product evaluation on a factory production line of bioethanol in the future.

© 2016 The Author(s)

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