Abstract
The partial least squares combined with near infrared spectroscopy (NIS) was applied to establish analysis models for determine the contents of polysaccharides and ergosterol in Tricholoma matsutake mycelium obtained from submerged fermentation. Near infrared spectrum of 150 subjects of T. matsutake mycelium were collected, and the contents of polysaccharides and ergosterol were detected via anthrone sulfuric acid method and high performance liquid chromatography, respectively. Monte Carlo partial least squares (MCPLS) were applied to identify the abnormal samples and the numbers of calibration set. During models establishment, the best spectral pre-treatment method, the characteristic wavelength range, and the hidden layer node numbers and other parameters of models were optimized by moving window PLS (MWPLS). The correlation coefficients of calibration set (Rc) for both models were 0.99999 and 0.99993. Based on statistical results, PLS predictive models show well fitting quality, predictive effect, and stability for analyzing polysaccharides and ergosterol content in T. matsutake mycelium. Altogether, PLS combined with NIS can be successfully applied to analyze the contents of polysaccharides and ergosterol in T. matsutake mycelium, and even for other fungi.
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Acknowledgements
This work was supported by Science and Technology Development Program of Jilin Province in China (Grant No. 20160520036JH), and Key Scientific and Technological Project of Jilin Province in China (Grant No. 20160204029YY and 20140311072YY).
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The authors have declared that there is no conflict of interest.
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Chu, Q. et al. (2018). Near Infrared Spectroscopic (NIRS) Analysis of Polysaccharides and Ergosterol Contents in Tricholoma matsutake Mycelium by Improved Chemometric Model. In: Liu, H., Song, C., Ram, A. (eds) Advances in Applied Biotechnology. ICAB 2016. Lecture Notes in Electrical Engineering, vol 444. Springer, Singapore. https://doi.org/10.1007/978-981-10-4801-2_30
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