A method of rapid determination of chlorophyll a and lipid contents of microalgae based on colorimetric analysis of the digital images of the microalgae is proposed. The color variation of microalgae during cultivation is evaluated by the brightness of the three primary colors (red, green, and blue). The brightness values of the three primary colors are modeled as two linear correlation functions (RGB model) for microalgal chlorophyll a and lipid contents, respectively. The chlorophyll a and lipid contents predicted by the proposed model are compared with that determined by the standard methods. The good agreement of the model predictions with experimental results is demonstrated with a squared correlation coefficient (R(2)) of 0.99 for chlorophyll a and lipid. The reliability of the RGB model was verified in real cultivations of the microalgae in a photobioreactor. Growth dynamics, contents of chlorophyll a and lipid corresponded very well with previously reported studies.
in Wiley InterScience (www.interscience.wiley.com).In this work, biodiesel synthesis via fatty acids esterification with methanol is conducted by using a heterogeneous catalyst made from cation-exchange resin. The kinetics of esterification is studied at the different levels of catalyst loading (3.65-53.6%, w/w), reaction temperature (333-353 K) and molar ratio of methanol to fatty acids (1:1 to 20:1). The reaction rate and fatty acids conversion increased with increases in catalyst loading, reaction temperature and molar ratio of feeding reactants. A pseudo-homogeneous kinetic model coupling the effect of catalyst loading, reaction temperature and methanol/fatty acids molar ratio used for describing the process gave a correlation coefficient of 0.95 between experimental and predicted data. The proposed model was further used to predict the optimal operating condition for obtaining equilibrium conversion of 0.99. A reaction temperature of 372.15 K, molar ratio of feeding reactants of 14.9:1 and reaction time of 9.5 h was numerically calculated as the optimal operating condition. Under this optimal operating condition, an experimental verification was carried out and a satisfactory match was observed between experimental data and model prediction.
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