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Rapid Characterization of Fatty Acids in Oleaginous Microalgae by Near-Infrared Spectroscopy

机译:近红外光谱法快速表征含油微藻中的脂肪酸

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The key properties of microalgal biodiesel are largely determined by the composition of its fatty acid methyl esters (FAMEs). The gas chromatography (GC) based techniques for fatty acid analysis involve energy-intensive and time-consuming procedures and thus are less suitable for high-throughput screening applications. In the present study, a novel quantification method for microalgal fatty acids was established based on the near-infrared spectroscopy (NIRS) technique. The lyophilized cells of oleaginous Chlorella containing different contents of lipids were scanned by NIRS and their fatty acid profiles were determined by GC-MS. NIRS models were developed based on the chemometric correlation of the near-infrared spectra with fatty acid profiles in algal biomass. The optimized NIRS models showed excellent performances for predicting the contents of total fatty acids, C16:0, C18:0, C18:1 and C18:3, with the coefficient of determination (R2) being 0.998, 0.997, 0.989, 0.991 and 0.997, respectively. Taken together, the NIRS method established here bypasses the procedures of cell disruption, oil extraction and transesterification, is rapid, reliable, and of great potential for high-throughput applications, and will facilitate the screening of microalgal mutants and optimization of their growth conditions for biodiesel production.
机译:微藻生物柴油的关键特性很大程度上取决于其脂肪酸甲酯(FAME)的组成。用于脂肪酸分析的基于气相色谱(GC)的技术涉及耗能且耗时的过程,因此不太适合高通量筛选应用。在本研究中,基于近红外光谱(NIRS)技术建立了一种新的微藻脂肪酸定量方法。用NIRS扫描含有不同脂质含量的油状小球藻的冻干细胞,并通过GC-MS测定其脂肪酸谱。基于近红外光谱与藻类生物质中脂肪酸谱的化学计量相关性,开发了NIRS模型。优化的NIRS模型在预测总脂肪酸C16:0,C18:0,C18:1和C18:3的含量方面表现出优异的性能,测定系数(R 2 )为0.998 ,0.997、0.999、0.991和0.997。综上所述,此处建立的NIRS方法绕过了细胞破坏,油提取和酯交换的过程,具有快速,可靠的特点,并且在高通量应用方面具有巨大潜力,并且将有助于筛选微藻突变体并优化其生长条件,以用于生物柴油生产。

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