Fatty acid analysis in microalgal mono- and polycultures using diffuse reflectance infrared Fourier transform spectroscopy coupled with partial least squares analysis

• Published in: Heliyon 2024-06, Vol.10 (12), p.e33058, Article e33058
• Main Authors: Niemi, Calle, Gentili, Francesco G.
• Format: Article
• Language: English
• Subjects: Analytical Chemistry; Analytisk kemi; Diffuse reflectance infrared fourier transform spectroscopy (DRIFT); Fatty acids; Microalgae; Partial least squares regression (PLSR)
• ISSN: 2405-8440; 2405-8440
• DOI: 10.1016/j.heliyon.2024.e33058

Fatty acids are of particular interest for industrial applications of microalgal feedstock, as these have a wide array of different uses such as pharmaceuticals and biofuels. Fourier transform infrared (FTIR) spectroscopic techniques used in combination with multivariate prediction modeling are showing great potential as analytical methods for characterizing microalgal biomass. The present study investigated the use of diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS) coupled with partial least squares regression (PLSR) to estimate fatty acid contents in microalgae. A prediction model for microalgal samples was developed using algae cultivated in both Bold's basal medium (BBM) and sterilized municipal wastewater under axenic conditions, as well as algal polycultures cultivated in open raceway ponds using untreated municipal wastewater influent. This universal prediction model was able to accurately predict microalgal samples of either type with high accuracy (RMSEP = 1.38, relative error = 0.14) and reliability (R2 > 0.92). DRIFTS in combination with PLSR is a rapid method for determining fatty acid contents in a wide variety of different microalgal samples with high accuracy. The use of spectral characterization techniques offers a reliable and environmentally friendly alternative to traditional labor intensive techniques based on the use of toxic chemicals. •Multivariate FTIR analysis can accurately predict microalgal fatty acid contents.•The method works regardless of culture medium and microalgal species.•The same model can be used to predict both monocultures and complex polycultures.•The study develops an environmental sustainable method for the microalgae industry.