Smart sensor to predict retail fresh fish quality under ice storage
| Autor: | Marta López Cabo, Míriam R. García, J.R. Herrera, Eva Balsa-Canto, Antonio A. Alonso, Graciela Ramilo-Fernández |
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| Rok vydání: | 2016 |
| Předmět: |
Ice storage
Engineering Food spoilage computer.software_genre 01 natural sciences Fish quality 0404 agricultural biotechnology Core predictions Quality index method Index method Predictive microbiology business.industry 010401 analytical chemistry 04 agricultural and veterinary sciences 040401 food science Retail fish quality 0104 chemical sciences Reliability engineering Fish-to-fish variability Smart sensor Total volatile Fresh fish Dynamic models Data mining business computer Food Science Biological variability |
| Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname |
| Popis: | 11 páginas, 4 tablas, 9 figuras Fish wastage and market prices highly depend on accurate and reliable predictions of product shelf life and quality. The Quality Index Method (QIM) and EU grading criteria for whitefish (Council Regulation(EC) No 2406/96, 1996) are established sensory methods used in the market to monitor fish quality. Each assessment requires the consultation of a panel of trained experts. The indexes refer exclusively to the current state of the fish without any predictions about its evolution in the following days. This work proposes the development of a smart quality sensor which enables to measure quality and to predict its progress through time. The sensor combines information of biochemical and microbial spoilage indexes with dynamic models to predict quality in terms of the QIM and EU grading criteria. Besides, the sensor can account for the variability inside the batch if spoilage indexes are measured in more than one fish sample. The sensor is designed and tested to measure quality in fresh cod (Gadus morhua) under commercial ice storage conditions. Only two spoilage indexes, psychrotrophic counts and total volatile base-nitrogen content, were required to get accurate estimations of the two usual established sensory methods. The sensor is able to account for biological variability as shown with the validation and demonstration data sets. Moreover, new research and technologies are in course to make these measurements faster and non-destructive. This would allow having at hand a smart non-intrusive fish quality sensor This work has been funded by the Spanish Ministry of Science and Innovation throughout project ISFORQUALITY (AGL2012- 39951-C02-01), RESISTANCE (DPI2014-54085-JIN) and FP7 SPEC- TRAFISH project (FP7/2007-2013: grant no 605399) |
| Databáze: | OpenAIRE |
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