Qualitative and quantitative evaluation of microalgal biomass using portable attenuated total reflectance-Fourier transform infrared spectroscopy and machine learning analytics

被引:4
|
作者
Sweiss, Mais [1 ]
Assi, Sulaf [2 ]
Barhoumi, Lina [3 ]
Al-Jumeily, Dhiya [4 ]
Watson, Megan [2 ]
Wilson, Megan [2 ]
Arnot, Tom [5 ]
Scott, Rod [6 ]
机构
[1] Al Balqa Appl Univ, Fac Agr Technol, Dept Biotechnol, Al Salt, Jordan
[2] Liverpool John Moores Univ, Sch Pharm & Biomol Sci, Byrom St, Liverpool L3 3AF, England
[3] Al Balqa Appl Univ, Fac Sci, Dept Chem, Al Salt, Jordan
[4] Liverpool John Moores Univ, Sch Comp Sci & Math, Liverpool, England
[5] Univ Bath, Water Innovat & Res Ctr, Dept Chem Engn, Bath, England
[6] Univ Bath, Dept Biol & Biochem, Bath, England
关键词
attenuated total reflectance Fourier transform infrared; biomass; microalgae; spectroscopy; wastewater; principal component; analysis; MUNICIPAL WASTE-WATER; BIOCHEMICAL-COMPOSITION; LIPID PRODUCTION; FTIR SPECTRA; CULTIVATION; GROWTH; ALGAE; EXTRACTION; CHLORELLA; STRAINS;
D O I
10.1002/jctb.7512
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
BACKGROUND: Using microalgae for wastewater treatment offers an environmentally friendly method to produce microalgal biomass that can be used for many applications. However, the biochemical characteristics of microalgal biomass vary from species to species, from strain to strain, and between different growth stages within the same species/strain. This study utilized portable attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy to determine the composition of freeze-dried microalgal biomass corresponding to eight different locally isolated microalgae and a reference strain that were grown in wastewater and then harvested at the log and stationary phases, respectively. RESULTS: The results showed that the portable ATR-FTIR spectroscopy offered a rapid, non-destructive, and accurate technique for monitoring changes in the biochemical composition of algal biomass at stationary and log phases, as well as quantifying their main constituents. For qualitative analysis of species, two machine learning analytics (MLAs; correlation in wavenumber space and principal component analysis) were able to differentiate between microalgae isolates in both their stationary and log phases. For quantification, univariate or multivariate regression offered accuracy in quantifying key microalgal constituents related to proteins, lipids, and carbohydrates. In this sense, multivariate methods showed more accuracy for quantifying carbohydrates, yet proteins and lipids were more accurately quantified with univariate regression. Based on quantification, the highest relative content of carbohydrates in the log phase was for Jordan-23 (Jo-23; Desmodesmus sp.), whereas the highest content in the stationary phase was that for Jordan-29 (Jo-29; Desmodesmus sp). Regarding the relative lipid content in the log phase, Jo-23 had the highest lipid content, while the highest content in the stationary phase was for Jo-29. CONCLUSION: ATR-FTIR spectroscopy offered a rapid and sustainable method for monitoring the microalgal biomass produced during wastewater treatment processes. (c) 2023 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).
引用
收藏
页码:92 / 108
页数:17
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