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Meat spoilage: a complex phenomenon to decipher

Spoilage and Multiblock approach
Causal links between meat microbiota, volatiloma and sensory alteration in meat

The research of UMR INRAE ​​Oniris SECALIM aims to better control the microbial risk and spoilage to meet the societal challenges of public health and reduction of food waste. Meat spoilage corresponds to a degradation of the sensory qualities of meat which mainly results from bacterial metabolism. The study of spoilage requires the collection of different types of experimental data including microbiological, physicochemical and sensory measurements. The objective of the study carried out by SECALIM scientists as part of the ANR Redlosses project was to better understand the spoilage process by establishing causal links between different types of responses linked to spoilage : the characterization of microbiota, the quantification of volatile molecules or volatiloma, as well as the sensory profiles associated with odors. The biostatistical analysis, carried out in collaboration with the INRAE ​​StatSC unit, using the Path-ComDim approach, on a set of data collected on fresh turkey sausages at different stages of spoilage, made it possible to quantify and to confirm the importance of the causal links supposed a priori between each type of response, and to visualize the dynamic and temporal nature of spoilage. This is mainly characterized by an evolution of the profiles of undesirable odors due to the production of volatile organic compounds such as ethanol or ethyl acetate, likely to be produced by several bacterial species such as Lactococcus piscium, Leuconostoc gelidum, Psychrobacter sp. or Latilactobacillus fuchuensis. Likewise, the production of acetoin and diacetyl has also been associated with spoilage in meat. The Path-ComDim approach illustrated here through meat spoilage can be applied to other heterogeneous and large data sets, and represents a promising tool for deciphering the causal links in complex biological phenomena.

Associated publication: Luong, N.-D. M., J.-M. Membré, L. Coroller, M. Zagorec, S. Poirier, S. Chaillou, M.-H. Desmonts, D. Werner, V. Cariou and S. Guillou 2021. Application of a path-modelling approach for deciphering causality relationships between microbiota, volatile organic compounds and off-odour profiles during meat spoilage. International Journal of Food Microbiology 348: 109208. https://doi.org/10.1016/j.ijfoodmicro.2021.109208 .

Partners and funding: This study was carried out by the UMR INRAE ​​Oniris SECALIM and financed within the framework of the ANR Redlosses (ANR-16-CE21-0006) coordinated by SECALIM, in partnership with the Redlosses consortium, and more particularly with the Micalis Institute , UMR INRAE ​​AgroParisTech, the University Laboratory of Biodiversity and Microbial Ecology (LUBEM) and AERIAL. The biostatistical analysis was performed in collaboration with USC INRAE ​​Oniris StatSC.