[Application of near infrared spectroscopy in screening Cordyceps militaris mutation strains and optimizing their...

To fast screen high-yield Cordyceps militaris mutations strains and optimize their fermentation process, near infrared (NIR) spectroscopy technology combined with chemometrics has been applied to establishing models for simultaneous determination of adenosine, protein, polysaccharide and Cordyceps militaris acid contents in Cordyceps militaris powder samples. Fermentations were implemented in Erlenmeyer flask with 468 Cordyceps militaris mutations strains under various fermentation conditions and Cordyceps militaris powder samples were collected. Then their NIR spectra were obtained using UV-VIS-NIR spectrometer and their adenosine, protein, polysaccharide and Cordyceps militaris acid contents were determined using reference methods. Partial least squares (PLS) method was employed to model the relationships between NIR spectra and the above mentioned components' contents in Cordyceps militaris powder samples. Monte Carlo partial least square (MCPLS) was applied to identify the outliers and select suitable number of calibration samples. Moving window partial least square (MWPLS) was applied to select the characteristic wavelength of the components. The degree of the approaching (Da) was employed as criterion for selecting effective pretreatment methods investigated. The optimum models for determination of adenosine, protein, polysaccharide and Cordyceps militaris acid contents in Cordyceps militaris powder samples were obtained with the above mentioned optimization. Their correlation between actual and predictive values of calibration samples (Re) was 0.92943, 0.98479, 0.90785, and 0.85131, respectively. Their root mean square error of prediction set (RMSEP) was 0.66714, 0.02065, 0.01131, and 0.01159, respectively. The obtained results demonstrated that the fitting and the predictive accuracy were satisfactory. It is feasible to apply this method to screen the high yield Cordyceps militaris mutation strains and optimize their fermentation process.