Raman Spectroscopic Detection On Microbial Fermentation In Biomass Energy

Along with the depletion of fossil fuels and the environmental problem is becoming increasingly serious, the development of clean and renewable resources has become a pressing issue. There are some microorganisms can be used to synthesize or convert some special material if cultured in the right condition, such as the microbial oil which can substitute for fossil fuels to produce biodiesel, the carotenoid can be used as food and drug additives, and ethanol can be used as fuel after purification, This means that these products all have relatively high economic value. This work, combined with the previous research, and the laser tweezers Raman spectroscopy system was used, trying to further explore the dynamic development of the products and the substrates of fermentation liquor and the material of intracellular during the process of fermentation, then we can provide a theoretical and an important reference parameters for the ferment industrial production, At the same time, we trying to carve from a selected group of yeast cells with the production capacity of some special products of the target cells. For that reason, the main research was carried out the following:1. This work is an attempt to study about fermentation detection of ethanol which is important to the laboratory research and industrial production. A high-throughput method used in our study is based on Raman Spectroscopy in the inverted microscope and 96-well plates. Base on the Raman signal ratio of standard ethanol solution and the internal, I establish a regression equation by the least squares fitting. And then the equation was used to calculate the content of ethanol, it was stem from the strains with cassava starch as a fermentation substrate, flask fermentation and the 500 liters of ethanol fermentation tank separately. At the same time the gas chromatography was used to detect the foregoing item. The t-test indicate that the results of Raman and gas chromatography have good reproducibility (p=0.05), this means that Raman test has a good accuracy. On the basis of Raman spectroscopy and 96-well plate, the linear regression, multiple linear regression, principal component regression and partial least squares (PLS) were employed to measure the concentration of ethanol and glucose aqueous mixtures simultaneously. A group of standard concentration of ethanol and glucose mixtures are was detected and fermentation broth of cassava starch was used to validate. The results show that this method could be applied to the real-time monitoring of ethanol fermentation.2. The structure, transformation, and bioactivity of single living cells at the molecular level have been studied by Raman spectroscopy. In this study, I explore the biochemical information about their biological macromolecules and the metabolic product from the Raman spectra of Saccharomyces cerevisiae, which was cultured by cassava starch with the 500 L fermentor. At first, in order to measure the ethanol and glucose concentration of the fermentation broth, we track the 880 cm-1 and 1127 cm-1 spectra band, and the results were compared with that of gas chromatography and the DNS colorimetry. In addition, several approaches such as the study of mean spectra, the difference spectra, the usage of histogram of characteristic absorption peak area and the application of principal component analysis were applied. These methods were applied on a data set containing Raman spectra of yeast in three stages of its growth, aiming to extract information about the evolution of cell components during growth. The result show that the laser tweezers Raman spectroscopy approach has the potential to open a new frontier to study microorganisms, which were used to optimize the fermentation parameters, and direct practical production of ethanol.3. Extensive research has been carried out in an effort to screen the microorganisms. Here, Raman Spectroscopy and laser tweezers were used to sort yeast from mixed yeast cells. The preprocessing of subtracted background,17 points S-G smoothing filter, polynomial fitting baseline correction and vector normalization were performed and the main features information of intracellular substances from the Raman Spectroscopy of yeast cells were extracted by combining principal component analysis. Basing on the distinguished composition of the traget yeast and the other yeast, a sorting model was established. The test yeast cell in optical trapping was distinguished real-time by the model referring to its Raman spectra. The cells distinguished as target yeast was collected by means of optical manipulation. The sorted traget yeast cells were verified by microbial culture and Sudan black B test etc. The result illustrates that Raman spectroscopy combining with optical manipulation is an effective technique for sorting yeast and other economic microorganisms.