微藻种类的鉴别和分类是研究微藻生理生化特性的基础和前提.微藻细胞中主要包含五种生物分子,包括蛋白质、糖类、油脂、核酸和色素,在不同藻种会有不同的比例含量,常常作为藻种鉴别的一种依据.文章探讨了采用激光共聚焦显微拉曼技术快速鉴别普通小球藻(Chlorella sp.)、莱茵衣藻(Chlamydomonas sp.)两种不同藻种的可行性.通过在相同光照时间、强度和相同培养基的条件下培养的两种微藻,利用琼脂固定法固定微藻细胞,在514.5 nm的激光下采集了不同藻种及其不同生长时期的拉曼光谱曲线,并通过rolling circle filter(RCF)算法去除荧光背景,然后采用去基线、卷积平滑等预处理方法得到两种藻种各40个样本的曲线.从80个样本中随机抽取50个样本训练建模,剩下的30个样本作为独立的验证集.对光谱数据采取不同的预处理方法,采用偏最小二乘(partial least squares,PLS)全波段建模建立光谱响应特征与普通小球藻、莱茵衣藻的关系模型,比较了不同预处理程度的效果.结果表明:利用激光共聚焦显微拉曼技术,基于不同藻种色素含量比的差异,同时结合化学计量学方法,可以快速、有效地将两种藻种鉴别出来.所提出的最大谱峰比值标准化法处理样本,当阈值为±0.5时,预测正确率达到100%,当阈值为±0.2时,预测正确率达到86.67%,表明所提出的新方法能在藻种鉴别和分类领域具有较高的可行性.

Identification and classification of microalgae are basis and premise in the study of physiological and biochemical characteristics for microalgae.Microalgae cells mainly consist of five kinds of biological molecules,including proteins,carbonhydrates,lipids,nucleic acids and pigments.These five kinds of biological molecules contents with different ratio in microalgae cells can be utilized to identify microalgae species as a supplement method.This paper investigated the application of Raman microspectroscopy technology in the field of rapid identification on different algae species such as aschlorella sp.and chlamydomonas sp..Cultivated in the same conditions of culture medium,illumination duration and intensity,these two kinds of species of microalgae cells were immobilized by using agar,and then the samples were placed under 514.5 nm Raman laser to collect Raman spectra of different growth periods of different species.An approach to remove fluorescence background in Raman spectra called Rolling Circle Filter(RCF) algorithm was adopted to remove the fluorescent background,and then some preprocessing methods were used to offset the baseline and smooth method of Savitzky-Golay was tried to make the spectra curves of total 80 samples smoother.Then 50 samples were randomly extracted from 80 samples for modeling,and the remaining 30 samples for independent validation.This paper adopted different pretreatment methods,and used the partial least squares(PLS) to establish model between the spectral data and the microalgae species,then compared the effects of different pretreatment methods.The results showed that with Raman microspectroscopy technology,the pretreatment method of max-peak ratio standardization was a more effective identification approach which utilizes the different content ratios of pigments of different microalgae species.This method could efficiently eliminate the influence on Raman signal due to different growth stages of microalgae and decomposition of pigments contents of microalgae in vivo.Compared with other traditional classification methods,this method had significant advantages like simpler procedure and shorter testing time,and it can also avoid some subjective measurement errors caused by unskilled operations.If the threshold was set to ±0.5,the prediction accuracy can reach 100%,and when the threshold was ±0.2,the prediction accuracy reached 86.67%,which proves the proposed new method can be a good approach to identify different algae varieties.