Innovative postbiotic-chia seed mucilage packaging to extend ostrich meat quality and shelf life: development and Support Vector Regression (SVR) modeling of quality parameters

Abstract Lactococcus lactis is a safe lactic acid bacterium widely used in the food industry. This study aimed to develop an active edible coating by combining chia seed mucilage with different concentrations (0%, 1%, and 2%) of cell-free supernatant (CFS) from L. lactis PAN1 to improve the microbial and physicochemical stability of ostrich meat stored at 4 ± 1 °C for 10 days. The results showed that coatings containing 2% CFS significantly reduced total viable counts, psychrotrophic bacteria, coliforms, and fungi compared to uncoated samples. In addition, CFS-enriched coatings limited lipid oxidation, preserved color attributes, and improved sensory acceptability during storage. To translate these experimental findings into a predictive tool, a Support Vector Regression (SVR) model was developed to estimate key quality parameters as functions of treatment type and storage time, achieving Mean Absolute Percentage Error (MAPE) values ranging from 1.10% to 9.90%. Coliforms exhibited the highest prediction accuracy (MAPE = 1.10%), whereas total color difference ( ΔE ) showed the lowest accuracy. Overall, the combination of chia seed mucilage and postbiotic CFS represents a promising clean-label strategy for extending the shelf life of ostrich meat, while the SVR model provides a practical framework for rapid quality prediction in meat preservation systems. Graphical Abstract

Authors

Institutions

Publication Details

Journal
Food Production Processing and Nutrition
Published
2026-04-14
DOI
https://doi.org/10.1186/s43014-026-00369-w
Primary Topic
Meat and Animal Product Quality
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Innovative postbiotic-chia seed mucilage packaging to extend ostrich meat quality and shelf life: development and Support Vector Regression (SVR) modeling of quality parameters

Hossein Jooyandeh, Mohammad Hojjati, Behrooz Alizadeh Behbahani, Alireza Vasiee et al.
Food Production Processing and Nutrition
Meat and Animal Product Quality
article

Innovative postbiotic-chia seed mucilage packaging to extend ostrich meat quality and shelf life: development and Support Vector Regression (SVR) modeling of quality parameters

Hossein Jooyandeh, Mohammad Hojjati, Behrooz Alizadeh Behbahani, Alireza Vasiee, Morteza Taki, Bahareh Goudarzi Shams Abadi
article en

Abstract

Abstract Lactococcus lactis is a safe lactic acid bacterium widely used in the food industry. This study aimed to develop an active edible coating by combining chia seed mucilage with different concentrations (0%, 1%, and 2%) of cell-free supernatant (CFS) from L. lactis PAN1 to improve the microbial and physicochemical stability of ostrich meat stored at 4 ± 1 °C for 10 days. The results showed that coatings containing 2% CFS significantly reduced total viable counts, psychrotrophic bacteria, coliforms, and fungi compared to uncoated samples. In addition, CFS-enriched coatings limited lipid oxidation, preserved color attributes, and improved sensory acceptability during storage. To translate these experimental findings into a predictive tool, a Support Vector Regression (SVR) model was developed to estimate key quality parameters as functions of treatment type and storage time, achieving Mean Absolute Percentage Error (MAPE) values ranging from 1.10% to 9.90%. Coliforms exhibited the highest prediction accuracy (MAPE = 1.10%), whereas total color difference ( ΔE ) showed the lowest accuracy. Overall, the combination of chia seed mucilage and postbiotic CFS represents a promising clean-label strategy for extending the shelf life of ostrich meat, while the SVR model provides a practical framework for rapid quality prediction in meat preservation systems. Graphical Abstract

Food Production Processing and NutritionVol. 8(1)
Agricultural Sciences and Natural Resources University of Khuzestan
Openalex Percentile: Top 24%
Meat and Animal Product Quality
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.