Preconditions for the creation of a meat freshness control and identification system

dc.citation.epage65
dc.citation.issue3
dc.citation.journalTitleВимірювальна техніка та метрологія
dc.citation.spage59
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorBubela, Tetiana
dc.contributor.authorBohush, Bohdan
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2024-03-11T09:15:12Z
dc.date.available2024-03-11T09:15:12Z
dc.date.created2023-02-28
dc.date.issued2023-02-28
dc.description.abstractThe relevance of creating a comprehensive system for meat control and identification to determine its freshness level has been demonstrated in the study. The drawbacks of traditional organoleptic and laboratory methods commonly used for meat inspection were analyzed. The authors presented the advantages and challenges of employing an electronic nose. A design for a meat control and identification system was proposed, which includes an Arduino Uno microcontroller, Raspberry Pi, USB to TTL adapter, gas sensors, color sensor, thermal camera, and image sensor. The proposed implementation of the electronic nose system on a single-board computer demonstrates its success in controlling and identifying meat freshness. A matrix of semiconductor gas sensors, TGS2602, MQ137, and MQ138, is formed as olfactory sensors, and TCS3200 is used as an RGB vision sensor, enabling the identification of the smell and color of different degrees of meat freshness. To obtain clear output differences from the gas sensors that react to the freshness level of meat, the baseline method is proposed for use. Therefore, a system enhanced with neural network capabilities will replace traditional devices for identifying meat freshness.
dc.format.extent59-65
dc.format.pages7
dc.identifier.citationBubela T. Preconditions for the creation of a meat freshness control and identification system / Tetiana Bubela, Bohdan Bohush // Measuring Equipment and Metrology. — Lviv : Lviv Politechnic Publishing House, 2023. — Vol 84. — No 3. — P. 59–65.
dc.identifier.citationenBubela T. Preconditions for the creation of a meat freshness control and identification system / Tetiana Bubela, Bohdan Bohush // Measuring Equipment and Metrology. — Lviv : Lviv Politechnic Publishing House, 2023. — Vol 84. — No 3. — P. 59–65.
dc.identifier.doidoi.org/10.23939/istcmtm2023.03.059
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/61435
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofВимірювальна техніка та метрологія, 3 (84), 2023
dc.relation.ispartofMeasuring Equipment and Metrology, 3 (84), 2023
dc.relation.references[1] DSTU 7992:2015 Meat and meat raw materials. Methods of sampling and organoleptic assessment of freshness. Available online: http://online.budstandart.com/ua/catalog/
dc.relation.references[2] Commission Regulation (EC) N. On microbiologicalcriteria for foodstuffs. Available online: https://www.fsai.ie/uploadedFiles/Reg2073_2005(1).pdf (accessed on 13 June 2019).
dc.relation.references[3] Linee Guida per l’analisi del rischio nel campo della microbiologia degli alimenti. Available online: https://www.ceirsa.org/docum/allegato_punto4.pdf (accessed on 13 June 2019)
dc.relation.references[4] Song S., Tang Q., Hayat K., Karangwa E., Zhang X., Xiao Z. Effect of enzymatic hydrolysis with subsequent mild thermal oxidation of tallow on precursor formation and sensory profiles of beef flavours assessed by partial least squares regression. Meat Sci. 2014; 96:1191–1200. DOI: 10.1016/j.meatsci.2013.11.008
dc.relation.references[5] Tian X., Wang J., Cui S. Analysis of pork adulteration in minced mutton using electronic nose of metal oxide sensors. J. Food Eng. 2013; 119:744–749. DOI: 10.1016/j.jfoodeng.2013.07.004
dc.relation.references[6] Wijaya D.R., Sarno R., Zulaika E., Sabila S.I. Development of mobile electronic nose for beef quality monitoring. Procedia Comput. Sci. 2017; 124:728–735. DOI: 10.1016/j.procs.2017.12.211
dc.relation.references[7] Wojnowski W., Majchrzak T., Dymerski T., Gębicki J., Namieśnik J. Electronic noses: Powerful tools in meat quality assessment.Meat Sci. 2017; 131:119–131. DOI: 10.1016/j.meatsci.2017.04.240.
dc.relation.references[8] De las NievesLópez de Lerma M., Bellincontro A., García-Martínez T., Mencarelli F., Moreno J. J. Feasibility of an electronic nose to differentiate commercial Spanish wines elaborated from the same grape variety. Food Res. Int. 2013; 51:790–796. DOI: 10.1016/j.foodres.2013.01.036.
dc.relation.references[9] Lozano J., Arroyo T., Santos J. P., Cabellos J. M., Horrillo M. C. Electronic nose for wine ageing detection. Sens. Actuators B Chem. 2008; 133:180–186. DOI: 10.1016/j.snb.2008.02.011.
dc.relation.references[10] Prieto N., Rodriguez-Méndez M.L., Leardi R., Oliveri P., Hernando-Esquisabel D., Iñiguez-Crespo M., de Saja J.A. Application of multi-way analysis to UV–visible spectroscopy, gas chromatography and electronic nose data for wine ageing evaluation. Anal. Chim. Acta. 2012; 719:43–51. DOI: 10.1016/j.aca.2012.01.009.
dc.relation.references[11] Aleixandre M., Santos J., Sayago I., Cabellos J., Arroyo T., Horrillo M. A Wireless and Portable Electronic Nose to DifferentiateMusts of Different Ripeness Degree and Grape Varieties. Sensors. 2015; 15:8429–8443. DOI: 10.3390/s150408429.
dc.relation.references[12] Wei Z., Xiao X., Wang J., Wang H. Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform. Sensors. 2017; 17:2500. DOI: 10.3390/s17112500.
dc.relation.references[13] Gobbi E., Falasconi M., Concina I., Mantero G., Bianchi F., Mattarozzi M.,MusciM., Sberveglieri G. Electronic nose and Alicyclobacillus spp. spoilage of fruit juices: An emerging diagnostic tool. Food Control. 201 21:1374–1382. DOI: 10. 1016/j.foodcont.2010.04.011.
dc.relation.references[14] Gruber J., Nascimento H. M., Yamauchi E Y., Li R. W. C., Esteves C. H. A., Rehder G P., Gaylarde C. C., Shirakawa M. A. A conductive polymer based electronic nose for early detection of Penicillium digitatum in post-harvest oranges. Mater. Sci. Eng. C. 2013; 33:2766–2769. DOI: 10.1016/j.msec.2013.02.043.
dc.relation.references[15] Chen L.-Y., Wu C.-C., Chou T.-I., Chiu S.-W., Tang K.-T. Development of a Dual MOS Electronic Nose/Camera System for Improving Fruit Ripeness Classification. Sensors. 2018; 18:3256. DOI: 10.3390/s18103256.
dc.relation.references[16] Xu S., Sun X., Lu H., Yang H., Ruan Q., Huang H., ChenM. Detecting andMonitoring the Flavor of Tomato (Solanum lycopersicum) under the Impact of Postharvest Handlings by Physicochemical Parameters and Electronic Nose. Sensors. 2018; 18:1847. DOI: 10.3390/s18061847.
dc.relation.references[17] Lingling Guo, Ting Wang, Zhonghua Wu, Jianwu Wang, Ming Wang, Zequn Cui, Shaobo Ji, Jianfei Cai, Chuanlai Xu, Xiaodong Chen. Portable Food-Freshness Prediction Platform Based on Colorimetric Barcode Combinatorics and Deep Convolutional Neural Networks. Advanced Materiales. Vol. 32, Iss. 45, 2004805, 2020. https://doi.org/10.1002/adma.202004805
dc.relation.referencesen[1] DSTU 7992:2015 Meat and meat raw materials. Methods of sampling and organoleptic assessment of freshness. Available online: http://online.budstandart.com/ua/catalog/
dc.relation.referencesen[2] Commission Regulation (EC) N. On microbiologicalcriteria for foodstuffs. Available online: https://www.fsai.ie/uploadedFiles/Reg2073_2005(1).pdf (accessed on 13 June 2019).
dc.relation.referencesen[3] Linee Guida per l’analisi del rischio nel campo della microbiologia degli alimenti. Available online: https://www.ceirsa.org/docum/allegato_punto4.pdf (accessed on 13 June 2019)
dc.relation.referencesen[4] Song S., Tang Q., Hayat K., Karangwa E., Zhang X., Xiao Z. Effect of enzymatic hydrolysis with subsequent mild thermal oxidation of tallow on precursor formation and sensory profiles of beef flavours assessed by partial least squares regression. Meat Sci. 2014; 96:1191–1200. DOI: 10.1016/j.meatsci.2013.11.008
dc.relation.referencesen[5] Tian X., Wang J., Cui S. Analysis of pork adulteration in minced mutton using electronic nose of metal oxide sensors. J. Food Eng. 2013; 119:744–749. DOI: 10.1016/j.jfoodeng.2013.07.004
dc.relation.referencesen[6] Wijaya D.R., Sarno R., Zulaika E., Sabila S.I. Development of mobile electronic nose for beef quality monitoring. Procedia Comput. Sci. 2017; 124:728–735. DOI: 10.1016/j.procs.2017.12.211
dc.relation.referencesen[7] Wojnowski W., Majchrzak T., Dymerski T., Gębicki J., Namieśnik J. Electronic noses: Powerful tools in meat quality assessment.Meat Sci. 2017; 131:119–131. DOI: 10.1016/j.meatsci.2017.04.240.
dc.relation.referencesen[8] De las NievesLópez de Lerma M., Bellincontro A., García-Martínez T., Mencarelli F., Moreno J. J. Feasibility of an electronic nose to differentiate commercial Spanish wines elaborated from the same grape variety. Food Res. Int. 2013; 51:790–796. DOI: 10.1016/j.foodres.2013.01.036.
dc.relation.referencesen[9] Lozano J., Arroyo T., Santos J. P., Cabellos J. M., Horrillo M. C. Electronic nose for wine ageing detection. Sens. Actuators B Chem. 2008; 133:180–186. DOI: 10.1016/j.snb.2008.02.011.
dc.relation.referencesen[10] Prieto N., Rodriguez-Méndez M.L., Leardi R., Oliveri P., Hernando-Esquisabel D., Iñiguez-Crespo M., de Saja J.A. Application of multi-way analysis to UV–visible spectroscopy, gas chromatography and electronic nose data for wine ageing evaluation. Anal. Chim. Acta. 2012; 719:43–51. DOI: 10.1016/j.aca.2012.01.009.
dc.relation.referencesen[11] Aleixandre M., Santos J., Sayago I., Cabellos J., Arroyo T., Horrillo M. A Wireless and Portable Electronic Nose to DifferentiateMusts of Different Ripeness Degree and Grape Varieties. Sensors. 2015; 15:8429–8443. DOI: 10.3390/s150408429.
dc.relation.referencesen[12] Wei Z., Xiao X., Wang J., Wang H. Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform. Sensors. 2017; 17:2500. DOI: 10.3390/s17112500.
dc.relation.referencesen[13] Gobbi E., Falasconi M., Concina I., Mantero G., Bianchi F., Mattarozzi M.,MusciM., Sberveglieri G. Electronic nose and Alicyclobacillus spp. spoilage of fruit juices: An emerging diagnostic tool. Food Control. 201 21:1374–1382. DOI: 10. 1016/j.foodcont.2010.04.011.
dc.relation.referencesen[14] Gruber J., Nascimento H. M., Yamauchi E Y., Li R. W. C., Esteves C. H. A., Rehder G P., Gaylarde C. C., Shirakawa M. A. A conductive polymer based electronic nose for early detection of Penicillium digitatum in post-harvest oranges. Mater. Sci. Eng. P. 2013; 33:2766–2769. DOI: 10.1016/j.msec.2013.02.043.
dc.relation.referencesen[15] Chen L.-Y., Wu C.-C., Chou T.-I., Chiu S.-W., Tang K.-T. Development of a Dual MOS Electronic Nose/Camera System for Improving Fruit Ripeness Classification. Sensors. 2018; 18:3256. DOI: 10.3390/s18103256.
dc.relation.referencesen[16] Xu S., Sun X., Lu H., Yang H., Ruan Q., Huang H., ChenM. Detecting andMonitoring the Flavor of Tomato (Solanum lycopersicum) under the Impact of Postharvest Handlings by Physicochemical Parameters and Electronic Nose. Sensors. 2018; 18:1847. DOI: 10.3390/s18061847.
dc.relation.referencesen[17] Lingling Guo, Ting Wang, Zhonghua Wu, Jianwu Wang, Ming Wang, Zequn Cui, Shaobo Ji, Jianfei Cai, Chuanlai Xu, Xiaodong Chen. Portable Food-Freshness Prediction Platform Based on Colorimetric Barcode Combinatorics and Deep Convolutional Neural Networks. Advanced Materiales. Vol. 32, Iss. 45, 2004805, 2020. https://doi.org/10.1002/adma.202004805
dc.relation.urihttp://online.budstandart.com/ua/catalog/
dc.relation.urihttps://www.fsai.ie/uploadedFiles/Reg2073_2005(1).pdf
dc.relation.urihttps://www.ceirsa.org/docum/allegato_punto4.pdf
dc.relation.urihttps://doi.org/10.1002/adma.202004805
dc.rights.holder© Національний університет “Львівська політехніка”, 2023
dc.subjectMeat freshness level
dc.subjectElectronic nose
dc.subjectGas sensors
dc.subjectColor sensors
dc.subjectThermal camera
dc.subjectNeural network
dc.subjectIdentification and control of meat freshness
dc.titlePreconditions for the creation of a meat freshness control and identification system
dc.typeArticle

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