Banca de DEFESA: FRANCISLAINE DE OLIVEIRA VALENTE

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : FRANCISLAINE DE OLIVEIRA VALENTE
DATE: 11/05/2026
TIME: 14:00
LOCAL: videoconferencia
TITLE:

Modeling the growth of natural microbiota in sliced
cooked ham for predictive validation of shelf life.

 

KEY WORDS:

Predictive microbiology; Shelf-life; Meat products; Microbial spoilage

PAGES: 105
BIG AREA: Ciências Agrárias
AREA: Ciência e Tecnologia de Alimentos
SUBÁREA: Tecnologia de Alimentos
SPECIALTY: Tecnologia de Produtos de Origem Animal
SUMMARY:

Food loss and waste represent a significant global challenge, particularly in the meat sector,
where microbial spoilage limits shelf life and contributes to losses throughout the production
chain. Predictive microbiology has emerged as a promising tool for shelf-life estimation and
food safety management. However, its practical application remains limited due to the lack of
integration between theoretical models and real food systems, as well as the difficulty in
representing the complexity of natural microbial communities. This thesis aimed to
investigate microbial spoilage in meat products and to evaluate the use of predictive
microbiology as a tool for shelf-life estimation, integrating both theoretical and experimental
approaches. In study 1, a structured review of predictive tools applied to meat systems was
conducted, identifying 76 platforms, of which 20 were considered applicable in industrial
environments. The analysis revealed that few tools incorporate spoilage-related parameters
and consumer acceptance criteria. In Study 2, spoilage mechanisms of sliced cooked ham
were investigated under different temperature conditions (4, 12, 24, and 36 °C). Microbial
growth, physicochemical parameters, quality attributes, and volatile compounds were
evaluated. The results demonstrated a strong influence of temperature on spoilage progression
and indicated that sensory changes are more closely associated with microbial metabolic
activity than with microbial counts alone. Overall, the integration of microbial growth data
with quality parameters is a promising approach for developing more realistic predictive
models, contributing to improved shelf-life estimation and reduction of losses in meat
products.

 

COMMITTEE MEMBERS:
Externa à Instituição - Marciane Magnani - UFPB
Presidente - ***.179.236-** - ANDRE FIORAVANTE GUERRA - CEFET/RJ
Interna - 359403 - ROSA HELENA LUCHESE