Detection in situ of carotenoid in microalgae by transmission spectroscopy

Vis/NIR transmission spectra in situ to determine the CC in Spirulina sp.Variable selection method of LW analysis, UVE and SPA were used.The prediction performance of x-LW-PLS, UVE-PLS and SPA-PLS were compared.A high RPD value of 3.40 and 3.44 were obtained by x-LW-PLS and SPA-PLS models. Carotenoids, which can be part of the food additives and drug additive, are one of important internal quality indexes for living microalgae. In the present study, visible/near infrared (Vis/NIR) transmission spectra in situ of Spirulina sp. suspension were required using an Ocean Optics USB 4000 Spectrometer in the wavelength range of 346-1038nm, and the loading weights (LW) analysis, uninformative variables elimination (UVE) and successive projections algorithm (SPA) were used to select important variables related to the carotenoids content (CC) for the Spirulina sp. suspension. Different concentrations of 100 samples of Spirulina sp. suspension were selected. The results showed the correlation coefficient (r), root mean square error (RMSE) and residual predictive deviation (RPD) in the prediction sets were 0.96, 0.23mg/L, 3.40, 0.89, 0.39mg/L, 1.59 and 0.96, 0.24mg/L, 3.44 for x-LW-PLS, UVE-PLS and SPA-PLS model respectively. It indicated that SPA-PLS gave the best result, while x-LW-PLS was better than UVE-PLS. So, Vis/NIR transmission spectra combined with SPA method was feasible to assess CC of Spirulina sp. suspension. And SPA variable selection method can simplify the prediction model and improve the model prediction precision. Furthermore, the method can be used as a good example for the detection in situ of other pigment content in other microalgae.

[1]  Fan Zhang,et al.  Applying Near-Infrared Spectroscopy and Chemometrics to Determine Total Amino Acids in Herbicide-Stressed Oilseed Rape Leaves , 2011 .

[2]  A. Gitelson,et al.  Assessing Carotenoid Content in Plant Leaves with Reflectance Spectroscopy¶ , 2002, Photochemistry and photobiology.

[3]  F. Xavier Malcata,et al.  Optimization of ω-3 fatty acid production by microalgae: crossover effects of CO2 and light intensity under batch and continuous cultivation modes , 2005, Marine Biotechnology.

[4]  J. Prebble.  Carotenoid Chemistry and Biochemistry : Edited by G. Britton and T.W. Goodwin Pergamon Press; Oxford, 1982 ix + 399 pages. £47.50 , 1983 .

[5]  Jerry Workman,et al.  Practical guide to interpretive near-infrared spectroscopy , 2007 .

[6]  J. Pérez,et al.  Biomass nutrient profiles of the microalga Porphyridium cruentum , 2000 .

[7]  Lin Zhang,et al.  Evaluation of FT-IR and Nile Red methods for microalgal lipid characterization and biomass composition determination. , 2013, Bioresource technology.

[8]  C. Wilhelm,et al.  The use of FTIR spectroscopy to assess quantitative changes in the biochemical composition of microalgae , 2010, Journal of biophotonics.

[9]  Fei Liu,et al.  Application of successive projections algorithm for variable selection to determine organic acids of plum vinegar. , 2009 .

[10]  Yidan Bao,et al.  Quantitative Analysis of Total Amino Acid in Barley Leaves under Herbicide Stress Using Spectroscopic Technology and Chemometrics , 2012, Sensors.

[11]  L. Kaplan,et al.  Separation and quantitation of serum beta-carotene and other carotenoids by high performance liquid chromatography. , 1984, Journal of lipid research.

[12]  Ami Ben-Amotz,et al.  Stereoisomers of β-Carotene and Phytoene in the Alga Dunaliella bardawil , 1988 .

[13]  Emilio Molina,et al.  Modelling of growth and accumulation of carotenoids in Haematococcus pluvialis as a function of irradiance and nutrients supply , 2005 .

[14]  D. Massart,et al.  Elimination of uninformative variables for multivariate calibration. , 1996, Analytical chemistry.

[15]  Roberto Kawakami Harrop Galvão,et al.  The successive projections algorithm , 2013 .

[16]  H. Ramon,et al.  Effect of Wavelength Range on the Measurement Accuracy of Some Selected Soil Constituents Using Visual-Near Infrared Spectroscopy , 2006 .

[17]  Jo‐Shu Chang,et al.  Effect of light supply and carbon source on cell growth and cellular composition of a newly isolated microalga Chlorella vulgaris ESP‐31 , 2010 .

[18]  Freddy Guihéneuf,et al.  Combined effects of irradiance level and carbon source on fatty acid and lipid class composition in the microalga Pavlova lutheri commonly used in mariculture , 2009 .

[19]  Svante Wold,et al.  Hierarchical multiblock PLS and PC models for easier model interpretation and as an alternative to variable selection , 1996 .

[20]  Ronald Rousseau,et al.  Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient , 2003, J. Assoc. Inf. Sci. Technol..

[21]  M. Barańska,et al.  Determination of lycopene and beta-carotene content in tomato fruits and related products: Comparison of FT-Raman, ATR-IR, and NIR spectroscopy. , 2006, Analytical chemistry.

[22]  N. Berardo,et al.  Application of near-infrared reflectance spectroscopy (NIRS) to the evaluation of carotenoids content in maize. , 2004, Journal of agricultural and food chemistry.

[23]  E. Becker.  Micro-algae as a source of protein. , 2007, Biotechnology advances.

[24]  X. Shao,et al.  Simultaneous Wavelength Selection and Outlier Detection in Multivariate Regression of Near-Infrared Spectra , 2005, Analytical sciences : the international journal of the Japan Society for Analytical Chemistry.

[25]  O. Pulz,et al.  Valuable products from biotechnology of microalgae , 2004, Applied Microbiology and Biotechnology.

[26]  W. K. Higby.  A simplified method for determination of some aspects of the carotenoid distribution in natural and carotene-fortified orange juice. , 1962 .