Comparison of Quality Changes in Eurasian Perch (<i>Perca fluviatilis</i> L.) Fillets Originated from Two Different Rearing Systems during Frozen and Refrigerated Storage

• Main Authors: Nima Hematyar, Jan Mraz, Vlastimil Stejskal, Sabine Sampels, Zuzana Linhartová, Marketa Prokesova, Frantisek Vacha, Martin Krizek, Eva Dadakova, Hanne Søndergård Møller, Trine Kastrup Dalsgaard
• Format: Article
• Language: English
• Published: MDPI AG 2021-06-01
• Series: Foods
• Subjects: rearing systems; fillet quality; protein characterization; hardness; liquid loss
• Online Access: https://www.mdpi.com/2304-8158/10/6/1405

The current knowledge on how different Eurasian perch rearing systems impact the final fillet quality is scant. Therefore, two domestic storage conditions were investigated—10 months frozen (−20 °C) and 12 days refrigerated (+4 °C) storage conditions—in order to determine (i) how the choice of rearing system affects fillets quality during different processing conditions and (ii) if oxidative changes and other quality parameters were interactive. For the proposed idea, proteome analysis, oxidative changes, and some quality parameters were considered in this study. Sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) indicated a higher loss of protein in the frozen fillets from ponds (PF) than the fillets from recirculating aquaculture systems (RAS) (RF). Western blot showed a higher protein carbonyls level in RF compared to PF, which was confirmed by the total protein carbonyls during frozen storage. PF indicated less liquid loss, hardness, and oxidation progress than RF in both storage conditions. The biogenic amines index (BAI) in the fillets from either origin showed acceptable levels during storage at +4 °C. Furthermore, the n-3/n-6 ratio was similar for both fillets. The deterioration of fillets during frozen storage was mainly caused by formation of ice crystals followed by protein oxidation, while protein oxidation was the main concern during refrigerated storage confirmed by principal component analysis (PCA) analysis.