Application of Machine Learning Using Color and Texture Analysis to Recognize Microwave Vacuum Puffed Pork Snacks
| cris.virtual.author-orcid | 0000-0001-5738-8737 | |
| cris.virtual.author-orcid | 0000-0001-6128-0315 | |
| cris.virtual.author-orcid | 0000-0002-2535-8370 | |
| cris.virtual.author-orcid | 0000-0002-3849-4435 | |
| cris.virtual.author-orcid | 0000-0002-4709-4601 | |
| cris.virtual.author-orcid | 0000-0003-1174-1915 | |
| cris.virtual.author-orcid | 0000-0003-0810-8086 | |
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| cris.virtualsource.author-orcid | 73a8f241-62c7-4a1e-96b3-8e6b4e185e6a | |
| cris.virtualsource.author-orcid | ab187d78-3916-499a-a077-9e8a0069cf71 | |
| cris.virtualsource.author-orcid | 898dc715-0fc1-42af-a4d7-0bc909752fee | |
| cris.virtualsource.author-orcid | 7583f283-39ec-4125-9e34-6f6a60d31a2d | |
| cris.virtualsource.author-orcid | 547fae8f-3c82-43d7-9832-0ba1dc522cf2 | |
| cris.virtualsource.author-orcid | 86cf2372-a835-4dbf-b1cb-6200ecf27dd5 | |
| cris.virtualsource.author-orcid | 90398b3a-5dd4-4557-a041-509a3389a7fb | |
| cris.virtualsource.author-orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| dc.abstract.en | The objective of the study was to create artificial neural networks (ANN) capable of highly efficient recognition of modified and unmodified puffed pork snacks for the purposes of obtaining an optimal final product. The study involved meat snacks produced from unmodified and papain modified raw pork (Psoas major) by means of microwave-vacuum puffing (MVP) under specified conditions. The snacks were then analyzed using various instruments in order to determine their basic chemical composition, color and texture. As a result of the MVP process, the moisture-to-protein ratio (MPR) was reduced to 0.11. A darker color and reduction in hardness of approx. 25% was observed in the enzymatically modified products. Multi-layer perceptron networks (MLPN) were then developed using color and texture descriptor training sets (machine learning), which is undoubtedly an innovative solution in this area. | |
| dc.affiliation | Wydział Nauk o Żywności i Żywieniu | |
| dc.affiliation | Wydział Inżynierii Środowiska i Inżynierii Mechanicznej | |
| dc.affiliation.institute | Katedra Mleczarstwa i Inżynierii Procesowej | |
| dc.affiliation.institute | Katedra Inżynierii Wodnej i Sanitarnej | |
| dc.affiliation.institute | Katedra Zarządzania Jakością i Bezpieczeństwem Żywności | |
| dc.affiliation.institute | Katedra Inżynierii Biosystemów | |
| dc.contributor.author | Pawlak, Tomasz | |
| dc.contributor.author | Pilarska, Agnieszka | |
| dc.contributor.author | Przybył, Krzysztof | |
| dc.contributor.author | Stangierski, Jerzy | |
| dc.contributor.author | Ryniecki, Antoni | |
| dc.contributor.author | Cais-Sokolińska, Dorota | |
| dc.contributor.author | Pilarski, Krzysztof | |
| dc.contributor.author | Peplińska, Barbara | |
| dc.date.access | 2026-01-26 | |
| dc.date.accessioned | 2026-02-06T09:08:13Z | |
| dc.date.available | 2026-02-06T09:08:13Z | |
| dc.date.copyright | 2022-05-18 | |
| dc.date.issued | 2022 | |
| dc.description.abstract | <jats:p>The objective of the study was to create artificial neural networks (ANN) capable of highly efficient recognition of modified and unmodified puffed pork snacks for the purposes of obtaining an optimal final product. The study involved meat snacks produced from unmodified and papain modified raw pork (Psoas major) by means of microwave-vacuum puffing (MVP) under specified conditions. The snacks were then analyzed using various instruments in order to determine their basic chemical composition, color and texture. As a result of the MVP process, the moisture-to-protein ratio (MPR) was reduced to 0.11. A darker color and reduction in hardness of approx. 25% was observed in the enzymatically modified products. Multi-layer perceptron networks (MLPN) were then developed using color and texture descriptor training sets (machine learning), which is undoubtedly an innovative solution in this area.</jats:p> | |
| dc.description.accesstime | at_publication | |
| dc.description.bibliography | il., bibliogr. | |
| dc.description.finance | publication_nocost | |
| dc.description.financecost | 0,00 | |
| dc.description.if | 2,7 | |
| dc.description.number | 10 | |
| dc.description.points | 100 | |
| dc.description.version | final_published | |
| dc.description.volume | 12 | |
| dc.identifier.doi | 10.3390/app12105071 | |
| dc.identifier.issn | 2076-3417 | |
| dc.identifier.uri | https://sciencerep.up.poznan.pl/handle/item/7191 | |
| dc.identifier.weblink | https://www.mdpi.com/2076-3417/12/10/5071 | |
| dc.language | en | |
| dc.relation.ispartof | Applied Sciences (Switzerland) | |
| dc.relation.pages | art. 5071 | |
| dc.rights | CC-BY | |
| dc.sciencecloud | nosend | |
| dc.share.type | OPEN_JOURNAL | |
| dc.subject.en | machine learning | |
| dc.subject.en | artificial neural networks | |
| dc.subject.en | pork muscle | |
| dc.subject.en | papain | |
| dc.subject.en | microwave-vacuum drying | |
| dc.subject.en | puffing | |
| dc.subject.en | texture analysis | |
| dc.subject.en | color analysis | |
| dc.title | Application of Machine Learning Using Color and Texture Analysis to Recognize Microwave Vacuum Puffed Pork Snacks | |
| dc.type | JournalArticle | |
| dspace.entity.type | Publication | |
| oaire.citation.issue | 10 | |
| oaire.citation.volume | 12 |