Work

Biodegradable antimicrobial coating and model prediction based on lab-derived supernatant and Lepidium perfoliatum mucilage for beef preservation

Year: 2025

Type: article

Abstract: • Bioactive coating from L. helveticus and Lepidium mucilage extended beef shelf life at 4°C for 10 days • Coated samples showed reduced microbial growth, lipid oxidation, moisture loss, and TVB-N levels • Sensory and color stability improved significantly with MLP+2%CFS, confirming packaging effectiveness This study focused on developing a bioactive coating for fresh beef using cell-free supernatant (CFS) from Lactobacillus helveticus strain CMI1 and mucilage from Lepidium perfoliatum (MLP) seeds, aiming to improve biodegradability in packaging. We aimed to evaluate the coating's impact on the shelf life of beef stored for ten days at 4°C. We measured microbial counts, including total viable counts (TVC), psychrotrophic counts (PTC), fungi, and coliform bacteria in treated samples. Results showed that while microbial growth increased in beef slices, control samples had higher counts than those treated with CFS and mucilage. Specifically, higher concentrations of CFS led to reduced microbial growth. Additionally, samples treated with MLP and 2% CFS exhibited the lowest pH levels compared to controls and significantly reduced moisture loss during storage. Over the ten-day period, these coated samples recorded lower levels of peroxide and thiobarbituric acid reactive substances. The loss of hardness was also less in coated samples compared to controls, with total volatile basic nitrogen levels in MLP + 2% CFS samples significantly below the critical threshold of 15 mg/100 g. Color assessments indicated effective preservation of meat coloration, while sensory evaluations revealed the coated samples received the highest ratings. In this study, Gaussian Process Regression (GPR) model was used to predict key quality indicators such as microbial counts (TVC, PTC, coliforms, fungi), physicochemical parameters (pH, TVBN, PV, TBA, moisture, hardness), color metrics (ΔE) and sensory scores. The model achieved exceptional predictive performance, with R² values consistently exceeding 0.97 and Mean Absolute Percentage Error (MAPE) below 0.9% across all parameters.

Source: Applied Food Research

DOI: 10.1016/j.afres.2025.101604

Authors: Pegah Namazi, Behrooz Alizadeh Behbahani, Mohammad Noshad, Alireza Vasiee, Morteza Taki, Hossein Jooyandeh

Institutions: Agricultural Sciences and Natural Resources University of Khuzestan, Research Institute of Food Science and Technology

Language: English

Topic: Meat and Animal Product Quality

Subfield: Animal Science and Zoology

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $2,050