Using Multispectral Imaging for Spoilage Detection of Pork Meat
The quality of stored minced pork meat was monitored using a rapid multispectral imaging device to quantify the degree of spoilage. Bacterial counts of a total of 155 meat samples stored for up to 580 h have been measured using conventional laboratory methods. Meat samples were maintained under two...
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| Veröffentlicht in: | Food and bioprocess technology 2013-09, Vol.6 (9), p.2268-2279 |
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| creator | Dissing, Bjørn Skovlund Papadopoulou, Olga S. Tassou, Chrysoula Ersbøll, Bjarne Kjaer Carstensen, Jens Michael Panagou, Efstathios Z. Nychas, George-John |
| description | The quality of stored minced pork meat was monitored using a rapid multispectral imaging device to quantify the degree of spoilage. Bacterial counts of a total of 155 meat samples stored for up to 580 h have been measured using conventional laboratory methods. Meat samples were maintained under two different storage conditions: aerobic and modified atmosphere packages as well as under different temperatures. Besides bacterial counts, a sensory panel has judged the spoilage degree of all meat samples into one of three classes. Results showed that the multispectral imaging device was able to classify 76.13 % of the meat samples correctly according to the defined sensory scale. Furthermore, the multispectral camera device was able to predict total viable counts with a standard error of prediction of 7.47 %. It is concluded that there is a good possibility that a setup like the one investigated will be successful for the detection of spoilage degree in minced pork meat. |
| doi_str_mv | 10.1007/s11947-012-0886-6 |
| format | Article |
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Bacterial counts of a total of 155 meat samples stored for up to 580 h have been measured using conventional laboratory methods. Meat samples were maintained under two different storage conditions: aerobic and modified atmosphere packages as well as under different temperatures. Besides bacterial counts, a sensory panel has judged the spoilage degree of all meat samples into one of three classes. Results showed that the multispectral imaging device was able to classify 76.13 % of the meat samples correctly according to the defined sensory scale. Furthermore, the multispectral camera device was able to predict total viable counts with a standard error of prediction of 7.47 %. 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Bacterial counts of a total of 155 meat samples stored for up to 580 h have been measured using conventional laboratory methods. Meat samples were maintained under two different storage conditions: aerobic and modified atmosphere packages as well as under different temperatures. Besides bacterial counts, a sensory panel has judged the spoilage degree of all meat samples into one of three classes. Results showed that the multispectral imaging device was able to classify 76.13 % of the meat samples correctly according to the defined sensory scale. Furthermore, the multispectral camera device was able to predict total viable counts with a standard error of prediction of 7.47 %. It is concluded that there is a good possibility that a setup like the one investigated will be successful for the detection of spoilage degree in minced pork meat.</description><subject>Agriculture</subject><subject>Biotechnology</subject><subject>Chemistry</subject><subject>Chemistry and Materials Science</subject><subject>Chemistry/Food Science</subject><subject>Food Science</subject><subject>Imaging</subject><subject>Laboratory methods</subject><subject>Meat</subject><subject>Original Paper</subject><subject>Pork</subject><subject>Sensory evaluation</subject><subject>Spoilage</subject><subject>Standard error</subject><subject>Storage conditions</subject><issn>1935-5130</issn><issn>1935-5149</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp1kE1LxDAQhosouK7-AG8FL16qM81XcxJZvxZ2UdA9hzRNl67dpibtwX9vS0VB8DRh8rwvwxNF5whXCCCuA6KkIgFME8gynvCDaIaSsIQhlYc_bwLH0UkIOwAOFMksutmEqtnG677uqtBa03ldx8u93o7b0vn4tXVVrbc2vrPd8F25JnZl_OL8e7y2ujuNjkpdB3v2PefR5uH-bfGUrJ4fl4vbVWIosi7Jc24YLZFlBSMWmDVCS0k4LyjmghZGGJPlaVYInpKs4FZmkkNBiMjBouVkHl1Ova13H70NndpXwdi61o11fVDIBgtc0hQG9OIPunO9b4brVEoRhGACxkKcKONdCN6WqvXVXvtPhaBGpWpSqgalalSqxkw6ZcLANlvrf5v_D30BIc13NQ</recordid><startdate>20130901</startdate><enddate>20130901</enddate><creator>Dissing, Bjørn Skovlund</creator><creator>Papadopoulou, Olga S.</creator><creator>Tassou, Chrysoula</creator><creator>Ersbøll, Bjarne Kjaer</creator><creator>Carstensen, Jens Michael</creator><creator>Panagou, Efstathios Z.</creator><creator>Nychas, George-John</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X2</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>ABJCF</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M0K</scope><scope>M7S</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>7QO</scope><scope>7T7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope></search><sort><creationdate>20130901</creationdate><title>Using Multispectral Imaging for Spoilage Detection of Pork Meat</title><author>Dissing, Bjørn Skovlund ; 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| subjects | Agriculture Biotechnology Chemistry Chemistry and Materials Science Chemistry/Food Science Food Science Imaging Laboratory methods Meat Original Paper Pork Sensory evaluation Spoilage Standard error Storage conditions |
| title | Using Multispectral Imaging for Spoilage Detection of Pork Meat |
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