用氨基葡萄糖含量的测定值间接表示红曲菌固态发酵过程中生物量的研究

The study of indirect determination of biomass in solid-state fermentation of Monascus by the measurement of glucosamine content

摘要:

【目的】为准确快速地了解紫色红曲菌固态发酵中生物量的变化，【方法】采用理化方法测定菌体量和氨基葡萄糖含量，研究了不同培养时间、培养基组成、培养方式下菌体量与氨基葡萄糖含量的关系，建立生物量和氨基葡萄糖含量的换算关系式；构建关联该菌固态培养物近红外光谱数据与实测氨基葡萄糖含量的PLS模型。【结果】建立了可通过近红外光谱法测定氨基葡萄糖来快速预测固态发酵生物量的方法，其中最优近红外模型的校正集内部交叉验证均方根误差(RMSECV)为0.209 4，预测集相关系数(Rp)和均方根误差(RMSEP)分别为0.993 4和0.217 3；同时利用所建的换算关系式也大大提高了生物量计算的准确性。【结论】基于所建立的生物量和氨基葡萄糖的换算关系式，利用近红外光谱法可以快速并且较准确地测定紫色红曲菌固态发酵过程中生物量的变化。

Abstract:

[Objective] The objective of this paper was to provide an accurate and rapid determination method for the biomass of Monascus purpureus in solid-state fermentation (SSF). [Methods] The biomass and glucosamine content was measured by physical and chemical methods, then the relation between biomass and glucosamine content under different cultivation time, media and culture methods was investigated and the conversion relation of biomass and glucosamine content was built. Moreover, the PLS model for the relation between near infrared spectra and measured glucosamine content of medium was built. [Results] The rapid method for estimating biomass in SSF was built by measuring glucosamine content with NIR. The root mean square error of cross-validation of calibration set (RMSECV), the prediction correlation coefficient (Rp) and root mean square error of prediction set (RMSEP) of the best model were 0.648 5, 0.993 4 and 0.217 3, respectively. Besides, the accuracy of biomass calculation was enhanced by the conversion correlation. [Conclusion] On the base of the conversion relation of biomass and glucosamine content, the biomass of Monascus purpureus in SSF could be determined more accurately and rapidly by use of NIR method.