基于显微拉曼对氮胁迫下微藻油脂变化的研究

发布时间：2018-01-21 18:07

本文关键词： 蛋白核小球藻氮胁迫显微拉曼主成分分析线性判别分析　出处：《光谱学与光谱分析》2017年10期 　论文类型：期刊论文

【摘要】：利用共聚焦显微拉曼光谱仪获取生长在三种氮营养条件下(氮胁迫、氮正常、氮饱和)培养的蛋白核小球藻(Chlorella pyrenoidosa)的拉曼光谱,通过拉曼散射光谱信息对微藻在不同氮胁迫下生长情况及油脂变化进行研究。对油脂拉曼特征峰值比值作气泡图以直观表达油脂积累量,该气泡图与尼罗红荧光图像具有良好的相关性。光谱信号经预处理后,利用主成分分析(PCA)对全波段进行分析,获得相应的主成分变量,通过线性判别分析(LDA)建立分类模型。利用PCA获取的主成分变量建立的LDA预测模型对三种氮营养条件的预测正确率分别是80%,93.3%,86.7%。基于油脂特征位移(RS)处的比率建立的LDA分类模型对三种氮营养条件的分类正确率最高达到86.7%。研究结果表明,利用拉曼技术对微藻生长的不同氮胁迫条件鉴别是可行的,且随着氮胁迫影响的时间增加,油脂的积累差异就越大。
[Abstract]:Confocal micro-Raman spectrometer was used to obtain the growth under three nitrogen nutrition conditions (nitrogen stress, nitrogen is normal. The Raman spectra of Chlorella pyrenoidosa (Chlorella pyrenoidosa) cultured in nitrogen saturation. The growth and oil changes of microalgae under different nitrogen stress were studied by Raman scattering spectrum information. The bubble image has a good correlation with the fluorescence image of Nile red. After the spectral signal is preprocessed, the principal component analysis (PCA) is used to analyze the whole band, and the corresponding principal component variables are obtained. The classification model was established by linear discriminant analysis (LDA). The prediction accuracy of LDA model based on principal component variables obtained by PCA for the three nitrogen nutrition conditions was 80% 93. 3% respectively. The LDA classification model based on the ratio of oil and fat characteristic displacement RSs has the highest classification accuracy of the three nitrogen nutrition conditions. It is feasible to use Raman technique to identify the different nitrogen stress conditions of microalgae growth, and with the increase of the time of nitrogen stress, the difference of oil accumulation will be greater.
【作者单位】：浙江大学生物系统工程与食品科学学院;深圳信息职业技术学院机电工程学院;
【基金】：国家自然科学基金项目(31402318) 浙江省公益性项目(2016C32055) 深圳市战略新兴产生发展专项(JCYJ20150417094158023)资助
【分类号】：O657.37;TE667
【正文快照】： 引　言　　近年来,由于世界能源危机日益加剧,越来越多的研究发展重心逐渐向可再生能源偏移。其中,生物柴油已经成为当今国际发展最快且应用最广的清洁可再生能源。藻类作为一种重要的可再生资源,具有光合效率高、环境适应能力强、生长周期短等优点[1]。然而研究者对于微藻中

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