Introduction: Poor quality silage can derive from the presence of deleterious microorganisms such as clostridia. Their dissemination along the food chain, especially in milk, causes issues such as the cheese late-blowing defect, particularly triggered by Clostridium tyrobutyricum. The scope of our study was to determine the C. tyrobutyricum occurrence in three different farms across four time periods in relation to the animal diets, specifically the Total Mixed Ration (TMR), by using real-time PCR. Methods: For this purpose, molecular-derived data were exploited to optimize a predictive model that simulated the farm conditions favoring the growth of butyric acid bacteria such as C. tyrobutyricum. Results: Our results showed that the originally utilized predictive model strongly underestimated the growth of C. tyrobutyricum in comparison to the molecular data. At the same time, our findings uncovered an additional source of contamination in the TMR related to silage and dietary residues that represent a reservoir of microbial contamination during successive TMR preparation. Based on these findings, the optimization of the model parameters such as growth rate range and the inclusion of the residues in the model, allowed a more accurate prediction of the contamination levels. Therefore, this study revealed that proper hygiene practices such as the removal of silage and TMR residues within the farm environment is essential to control the contamination by C. tyrobutyricum and avoid food waste and economic losses.

Mosconi, M., Fontana, A., Belloso Daza, M. V., Bassi, D., Gallo, A., Clostridium tyrobutyricum occurrence in silages and cattle feed: use of molecular and simulation data to optimizepredictive models, <<FRONTIERS IN MICROBIOLOGY>>, 2023; (14): N/A-N/A. [doi:10.3389/fmicb.2023.1118646] [https://hdl.handle.net/10807/230662]

Clostridium tyrobutyricum occurrence in silages and cattle feed: use of molecular and simulation data to optimize predictive models

Fontana, Alessandra
Co-primo
;
Belloso Daza, Mireya Viviana
Secondo
;
Bassi, Daniela
Penultimo
;
Gallo, Antonio
Ultimo
2023

Abstract

Introduction: Poor quality silage can derive from the presence of deleterious microorganisms such as clostridia. Their dissemination along the food chain, especially in milk, causes issues such as the cheese late-blowing defect, particularly triggered by Clostridium tyrobutyricum. The scope of our study was to determine the C. tyrobutyricum occurrence in three different farms across four time periods in relation to the animal diets, specifically the Total Mixed Ration (TMR), by using real-time PCR. Methods: For this purpose, molecular-derived data were exploited to optimize a predictive model that simulated the farm conditions favoring the growth of butyric acid bacteria such as C. tyrobutyricum. Results: Our results showed that the originally utilized predictive model strongly underestimated the growth of C. tyrobutyricum in comparison to the molecular data. At the same time, our findings uncovered an additional source of contamination in the TMR related to silage and dietary residues that represent a reservoir of microbial contamination during successive TMR preparation. Based on these findings, the optimization of the model parameters such as growth rate range and the inclusion of the residues in the model, allowed a more accurate prediction of the contamination levels. Therefore, this study revealed that proper hygiene practices such as the removal of silage and TMR residues within the farm environment is essential to control the contamination by C. tyrobutyricum and avoid food waste and economic losses.
2023
Inglese
Mosconi, M., Fontana, A., Belloso Daza, M. V., Bassi, D., Gallo, A., Clostridium tyrobutyricum occurrence in silages and cattle feed: use of molecular and simulation data to optimizepredictive models, <<FRONTIERS IN MICROBIOLOGY>>, 2023; (14): N/A-N/A. [doi:10.3389/fmicb.2023.1118646] [https://hdl.handle.net/10807/230662]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/230662
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