A multiple parameters fusion model based on hydrogen sulfide for accurately evaluating the freshness of lamb meat

Hydrogen sulfide (H2S), as an important freshness indicator of meat, can effectively reflect the degree of spoilage. However, establishing a multiple parameters fusion model with temperature correction to fit the relationship between the H2S concentration and other freshness indicators is still a challenge. In this study, the M. longissimus thoracis et lumborum muscle (LTL) of lamb was stored in air packaging at 0 degrees C, 4 degrees C, 8 degrees C, 12 degrees C and 25 degrees C, respectively, to monitor the changes of gaseous H2S and other fresh indicators. The correlation analysis indicates that H2S concentration is highly consistent with lamb meat freshness. During the analysis, the well-fitted Stirling models show high statistical relationships between H2S and total viable count (TVC)/total volatile base nitrogen (TVB-N) values with the determination coefficients (R-2) all exceeding 0.9000. Subsequently, the fusion freshness prediction models with the temperature corrections were successfully established by fusing the exponential models into the Stirling models. As verified, the fusion freshness prediction models based on H2S concentration can offer accurate predictions of the TVC and TVB-N values of lamb meat at different temperatures with an R-2 of 0.9352 and 0.8627, respectively. The proposed models might be used to accurately forecast and evaluate the freshness of meat in the process of storage.