Abstract
Ridgetail white prawns, Exopalaemon carinicauda, storage time rapid determination method based on electronic nose was investigated in this paper. Prawns were stored at 4 °C for 9 days. Each day, electronic nose responses, and total volatile basic nitrogen index were measured during the storage period. Total volatile basic nitrogen index provided a freshness standard according to China standard protocols. Signal-to-noise ratio spectrum calculated by stochastic resonance discriminates prawn samples under different storage days successfully. Prawns' storage time determination model was developed based on signal-to-noise ratio eigenvalues. Validating experiments demonstrated that this model predicted prawn storage time with an accuracy of 90 %. Prawn freshness critical value −82.77066 was also obtained by referring to total volatile basic nitrogen index and the developed model. This method is promising in seafood freshness evaluation.
Similar content being viewed by others
References
Benedetti, S., Buratti, S., Spinardi, A., Mannino, S., Mignani, I. Electronic nose as a non-destructive tool to characterize peach cultivars and to monitor their ripening stage during shelf-life [J]. 47 (2008) 181–188
Benzi R, Sutera A, Vulpiana A (1981) The mechanism of stochastic resonance [J]. J Phys A 14:L453–L456
Brezmes J, Llobet E, Vilanova X, Orts J, Saiz G, Correig X (2001) Correlation between electronic nose signals and fruit quality indicators on shelf-life measurements with pinklady apples [J]. Sensors Actuators B Chem 80:41–50
Chai C, Ling Y (2010) Identification of shrimp freshness by electronic nose [J]. Food Sci Technol 35(2):246–249
China standard protocols, GB 2733–2005, 2005
China standard protocols, GB/T 5009.44-2003, 2003
Dutta R, Hines EL, Gardner JW, Udrea DD, Boilot P (2003) Non-destructive egg freshness determination: an electronic nose based approach [J]. Meas Sci Technol 14(2):190–198
Dutta R, Das A, Stocks NG, Morgan D (2006) Stochastic resonance-based electronic nose: A novel way to classify bacteria [J]. Sensors Actuators B Chem 115:17–27
Fishery Bureau, Ministry of Agriculture, China. China Fisheries Yearbook 2010. Chinese Agriculture Express; 2010
Gammaitoni L., Hanggi. P., Jung. P., Marchesoni. F, Stochastic resonance [J]. Review of Modern Physics, 70 (1998) 223–287
Gu S, Wang X, Tao N, Wu N (2013) Characterization of volatile compounds in different edible parts of steamed Chinese mitten crab (Eriocheir sinensis) [J]. Food Res Int 54(1):81–92
Hui GH, Mi SS, Deng SP (2012a) Sweet and bitter tastants specific detection by the taste cell-based sensor [J]. Biosens Bioelectron 35:429–438
Hui GH, Wu YL, Ye DD, Ding WW, Wang LY (2012b) Study of peach freshness predictive method based on electronic nose [J]. Food Control 166–167:25–32
Hui GH, Wang LY, Mo YH, Zhang LX (2012c) Study of grass carp (Ctenopharyngodon idellus) quality predictive model based on electronic nose [J]. Sensors Actuators B Chem 35:301–308
Lerma-Garcia MJ, Simo-Alfonso EF, Bendini A, Cerretani L (2009) Metal oxide semiconductor sensors for monitoring of oxidative status evolution and sensory analysis of virgin olive oils with different phenolic content [J]. Food Chem 117:608–614
Lorenzen PC, Walte HG, Bosse B (2013) Development of a method for butter type differentiation by electronic nose technology [J]. Sensors Actuators B Chem 181:690–693
Luzuriaga DA, Korel F, Balaban M (2008) Odor evaluation of shrimp treated with different chemicals using an electronic nose and a sensory panel [J]. J Aquat Food Prod Technol 16(2):57–75
McElyea KS, Pohlman FW, Meullenet JF, Suwansri S (2003) Evaluation of the electronic nose for rapid determination of meat freshness [J]. Arkansas Animal Science Department Report 2003. AAES Res Ser 509:32–35
Panigrahi S, Balasubramanian S, Gu H, Logue CM, Marchello M (2006) Design and development of a metal oxide based electronic nose for spoilage classification of beef [J]. Sensors Actuators B Chem 119:2–4
Peris M, Escuder-Gilabert L (2009) A 21st century technique for food control: electronic noses [J]. Anal Chim Acta 638:1–15
Ragazzo-Sanchez JA, Chalier R, Chevalier D, Calderon-Santoyo M, Ghommidh C (2008) Identification of different alcoholic beverages by electronic nose coupled to GC [J]. Sensors Actuators B Chem 134:43–48
Reinhard H, Sager F, Zoller O (2008) Citrus juice classification by SPME-GC-MS and electronic nose measurements [J]. Lwt-Food Sci Technol 41:1906–1912
Shi B, Zhao L, Zhi R, Xi X (2013) Optimization of electronic nose sensor array by genetic algorithms in Xihu-Longjing Tea quality analysis [J]. Math Comput Model 58(3–4):752–758
Tang X, Sun X, Wu VCH, Xie J, Pan Y, Zhao Y, Malakar PK (2013) Predicting shelf-life of chilled pork sold in China [J]. Food Control 32(1):334–340
Wang TH, Hui GH, Deng SP (2010) A novel sweet taste cell-based sensor [J]. Biosens Bioelectron 26:929–934
Xie W, Yang X, Zhang C, Xia Y, Tang J (2009) Evaluation of the flavor development based on sensors and actuators technology and SPME-GC-MS analysis [J]. Int Conf Inf Eng Comp Sci 1:1–3
Xu W, Xie J, Shi H, Li C (2010) Hematodinium infections in cultured ridgetail white prawns, Exopalaemon carinicauda, in eastern China [J]. Aquaculture 300:25–31
Zeng QZ, Thorarinsdottir KA, Olafsdottir G (2005) Quality changes of shrimp (Pandalus borealis) stored under different cooling conditions [J]. J Food Sci 70(7):S459–S466
Acknowledgments
Hui Guohua declares that this work is financially supported by National Natural Science Foundation of China (grant no. 81000645), Zhejiang Province Science and Technology Research Project (grant no. 2011C21051), Zhejiang Province Natural Science Foundation (grant no. Y1100150, Y1110074), Higher Education Research Project of Zhejiang Gongshang University (Xgy13080). Yang Yue received research grant from Zhejiang Province Science and Technology Research Project (grant no. 2011C21051). Zhou Yao received research grant from student Innovation Projects of Zhejiang Gongshang University (2013–157, 158). Wang Minmin received research grant from student Innovation Projects of Zhejiang Gongshang University (2013–157, 158). Huang Jie received research grant from student Innovation Projects of Zhejiang Gongshang University (2013–157, 158). Yin Fangyuan received research grant from Student Innovation Projects of Zhejiang Province (2012R408041, 2010R408015). Shen Feng received research grant from student Innovation Projects of Zhejiang Gongshang University (2012–160). Wang Lvye received research grant from Student Innovation Projects of Zhejiang Province (2012R408041, 2010R408015). Jiang Yan received research grant from student Innovation Projects of Zhejiang Gongshang University (2012–161). Deng Shanggui received research grant from National Natural Science Foundation of China (grant no. 31071628) and International Science and Technology Cooperation Project of China (no. 2010DFB34220).
Conflict of Interest
Hui Guohua declares that he has no conflict of interest. Yang Yue declares that he has no conflict of interest. Zhou Yao declares that he has no conflict of interest. Zhou Yuren declares that he has no conflict of interest. Wang Minmin declares that he has no conflict of interest. Huang Jie declares that he has no conflict of interest. Yin Fangyuan declares that he has no conflict of interest. Shen Feng declares that he has no conflict of interest. Jiang Yan declares that he has no conflict of interest. Wang Lvye declares that he has no conflict of interest. Deng Shanggui declares that he has no conflict of interest. This article does not contain any studies with human subjects.
Compliance with Ethics Requirements
All institutional and national guidelines for the care and use of laboratory animals were followed.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hui, G., Yue, Y., Yao, Z. et al. Ridgetail White Prawns, Exopalaemon carinicauda, Storage Time Rapid Determination Using Electronic Nose. Food Anal. Methods 7, 986–993 (2014). https://doi.org/10.1007/s12161-013-9703-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12161-013-9703-8