Suppr超能文献

荧光光谱法和化学计量学用于同时监测海洋微拟球藻中的细胞浓度、叶绿素和脂肪酸。

Fluorescence spectroscopy and chemometrics for simultaneous monitoring of cell concentration, chlorophyll and fatty acids in Nannochloropsis oceanica.

机构信息

LAQV-REQUIMTE, Chemistry Department, FCT, Universidade Nova de Lisboa, Caparica, Portugal.

Bioprocess Engineering, AlgaePARC, Wageningen University and Research, Wageningen, Netherlands.

出版信息

Sci Rep. 2020 May 6;10(1):7688. doi: 10.1038/s41598-020-64628-7.

Abstract

Online monitoring of algal biotechnological processes still requires development to support economic sustainability. In this work, fluorescence spectroscopy coupled with chemometric modelling is studied to monitor simultaneously several compounds of interest, such as chlorophyll and fatty acids, but also the biomass as a whole (cell concentration). Fluorescence excitation-emission matrices (EEM) were acquired in experiments where different environmental growing parameters were tested, namely light regime, temperature and nitrogen (replete or deplete medium). The prediction models developed have a high R for the validation data set for all five parameters monitored, specifically cell concentration (0.66), chlorophyll (0.78), and fatty acid as total (0.78), saturated (0.81) and unsaturated (0.74). Regression coefficient maps of the models show the importance of the pigment region for all outputs studied, and the protein-like fluorescence region for the cell concentration. These results demonstrate for the first time the potential of fluorescence spectroscopy for in vivo and real-time monitoring of these key performance parameters during Nannochloropsis oceanica cultivation.

摘要

在线监测藻类生物技术过程仍然需要发展,以支持经济可持续性。在这项工作中,荧光光谱学与化学计量学建模相结合,用于同时监测几种感兴趣的化合物,如叶绿素和脂肪酸,以及整个生物量(细胞浓度)。在不同环境生长参数(光照制度、温度和氮(充足或缺乏培养基))的实验中采集了荧光激发-发射矩阵(EEM)。为所有监测的五个参数开发的预测模型对于验证数据集具有高 R 值,具体为细胞浓度(0.66)、叶绿素(0.78)和总脂肪酸(0.78)、饱和脂肪酸(0.81)和不饱和脂肪酸(0.74)。模型的回归系数图表明,对于所有研究的输出,色素区域对于所有输出都很重要,而对于细胞浓度,蛋白质样荧光区域很重要。这些结果首次证明了荧光光谱学在体内和实时监测海洋微拟球藻培养过程中的这些关键性能参数的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b46/7203222/7a31bd696988/41598_2020_64628_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验