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Quality Changes Of Frozen Grass Carp & Fast Detection Method For Grass Carp Based On Machine Vision

Posted on:2016-09-06Degree:MasterType:Thesis
Country:ChinaCandidate:C XuFull Text:PDF
GTID:2191330479487539Subject:Food Science and Engineering
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In this study, physical and chemical indicators and texture properities were used to characterize the quality of grass carp samples, which were stored in different temperature with different pre-process methods. By studying the color changes of grass carp gills, a novel fish freshness rapid detection method was put forward.The freezing curves of grass carp under different freezing velocity were studied.The grass carp quality was determined by p H value, Water Holding Capacity, Total Volatile Basic Nitrogen(TVB-N) and Texture Profile Analysis(TPA). Grass carp samples were divided into 3 groups: Pickled groups, Blank groups and Ice-coating groups. All groups were stored separately in-18℃ and-25℃. All the indicators of pickled groups were used to compare with those of blank groups and ice-coating groups during 105d’s storage. Results showed that in the condition of same storage temperature and same storage time, the quality of grass carp samples in pickled groups was better than that in blank groups, but not so good as the samples in ice-coating groups. Compared with pickled group stored at-18℃, the quality of pickled groups stored at-25℃ was better. Compared with ice-coating groups, the advantages of pickled groups were higher hardness value and easier pre-process methods. And store pickled grass carp at-25℃ could also be coincided as a good way to keep grass carp quality during frozen storage.Regard grass carp gills which were stored at 20 ℃ with constant humidity as the research objects. Acquire the graph information under different light conditions(LED light with 24 lamps whose power could change from 2W to 1.8W) by using CCD camera once per hour. The grass carp gills’ color information were characterized by using RGB values, L*a*b* values and CMYK values. And also these data was made a match to the storage time in the units of hour. Results showed that R value of RGB presented a downward trend. G value of RGB showed a slight upward tendency. While the B value of RGB behaved a drop trend, then after 10h’s drop, it began to rise. The L* value of L*a*b* presented a liner upward trend, the liner correlation coefficient between L* value in 1.8W light group and storage time of fish gills(with the unit of 1 hour) was high, with the R2=0.89. The a* value of Lab in the two groups both showed a liner drop down. Linear correlation coefficient in 2W light group was 0.96, and in 1.8W group was 0.91. The b* value of Lab presented a small rising before stored 3h, then its’ value showed a small wave between 130 to 135 in two groups. C value of CMYK behaved a rising after slight decreasing. Like the red color in RGB and L*a*b*, the M value of CMYK presented a liner decreasing tendency with R2=0.88 in 2W light group and R2=0.87 in 1.8W light group. The Y value of CMYK showed a stable trend after 3h’ slight increasing. The K value behaved a small rising trend in both groups. As a conclusion the a* value of Lab showed a high liner correlation coefficient with storage time in both groups, and its’ linear correlation coefficient were both above 0.9. So this a* value of L*a*b* could be used as the characteristic information for the freshness fast determination for grass carp, and 2W light group showed a higher reliability.
Keywords/Search Tags:Grass carp, Quality, Pickling, Ice-coating, gill, machine vision
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