Recovery of carotenoids from shrimp waste in organic solvents

• Published in: Waste management (Elmsford) Vol. 26; no. 10; pp. 1092 - 1098
• Main Authors: Sachindra, N.M., Bhaskar, N., Mahendrakar, N.S.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 2006; New York, NY Elsevier Science
• Subjects: 2-Propanol; Animals; Applied sciences; Carotenoids - isolation & purification; Exact sciences and technology; Fisheries - methods; Hexanes; India; Other wastes and particular components of wastes; Penaeidae - chemistry; Pollution; Regression Analysis; Solvents - chemistry; Waste Products - analysis; Wastes; India; Crustacea; Organic solvent; Statistical analysis; Arthropoda; Prediction; Seafood; Decapoda; Invertebrata; Modeling; Shrimp; Petroleum; Macrura
• ISSN: 0956-053X; 1879-2456
• DOI: 10.1016/j.wasman.2005.07.002

Shrimp waste, which is produced in large quantities in the Indian seafood processing industries, is one of the important sources of natural carotenoids. Studies were carried out to assess the extractability of shrimp waste carotenoids in different organic solvents and solvent mixtures and to optimize the extraction conditions for maximum yield. A 50:50 mixture of isopropyl alcohol and hexane gave the highest (43.9 μg/g waste) carotenoid extraction yield compared to acetone, methanol, ethanol, isopropyl alcohol, ethyl acetate, ethyl methyl ketone, petroleum ether, and hexane individually and to a mixture of acetone and hexane. Extraction conditions such as percentage of hexane in the solvent mixture of isopropyl alcohol and hexane, ratio of solvent to waste and number of extractions was optimized using a statistically designed experiment. The optimized conditions for maximum yield of carotenoids were 60% hexane in solvent mixture, solvent mixture to waste ratio of 5:1 in each extraction and three extractions. A regression equation for predicting the carotenoid yield as a function of three processing variable (hexane % in solvent mixture, solvent-to-waste ratio and number of extractions) was derived by statistical analysis, and a model with predictive ability of 0.98 was obtained.