In silico Logistic Model for Table Olive Related Microorganisms As a Function of Sodium Metabisulphite, Cinnamaldehyde, pH, and Type of Acidifying Agent
A probabilistic/logistic model, based on binary data (growth/no growth), was used to assess the effects of sodium metabisulphite (SM) and cinnamaldehyde (CIN; 0–1000 mg/L) against the main microbial groups found in table olive environment [lactic acid bacteria (LAB), yeasts, and Enterobacteriaceae], according to pH (range 3.5–5.0), and type of acidifying agent (HCl or pyruvic acid). The inhibitory effect of SM depended on the pH while that of CIN was scarcely influenced by it (except for LAB). LAB were more sensitive to SM, while yeasts were to CIN. The use of pyruvic acid for correction of pH always produced a reduction (compared to HCl) of the inhibitory power of both preservatives. The in silico models for HCl showed that, at pH 4.0, and growth probability 0.01, the LAB population might be inhibited by the presence in the medium of 150 mg/L SM or 1000 mg/L CIN, while in the case of yeasts, 450 mg/L SM, or 150 mg/L CIN are required. No growth of Enterobacteriaceae was observed at this (or lower) pH level. The results obtained may contribute to the stabilization of non-thermally treated table olive packaging.
Quantitative Tools and Procedures for Shelf Life Determination in Minimally Processed Fruits and Vegetables
In minimally processed fruits and vegetables (MPFV) the exposure of internal tissues, the lack of skin or cuticle and the accelerated metabolism after processing lead to deterioration of sensory attributes mainly due to biochemical processes, physiological ageing and microbial spoilage. Therefore, processing operations such as peeling, slicing or shredding make MPFV more perishable than intact fresh produce. Shelf life of these products is not homogenous and can greatly vary mainly due to differences in manufacturing processes to which they are subjected. Reliable techniques that allow determining shelf life in an effective and precise way are necessary, as small changes in shelf life determinations could represent big economic losses. The shelf life of MPFV is usually determined by means of methods that evaluate changes in organoleptic characteristics during the distribution chain. Hence, it is essential to understand the processes influencing changes in MPFV quality as well as treatments and management techniques that are applied to evaluate and monitor their quality. Innovative techniques that allow modelling the influence of different environmental conditions and processing operations on MPFV quality are being proposed as more objective techniques to determine shelf life. Within these innovative procedures, shelf life estimation by means of the use of predictive microbiology models is one of the most useful ones. The purpose of this chapter is to provide an overview on processes influencing quality changes of minimally processed fruits and vegetables as well as the available procedures and quantitative tools that are applied in shelf life determination.
Inhibition of malolactic fermentation by Saccharomyces during alcoholic fermentation under low- and high-nitrogen conditions: a study in synthetic media
The ability of different wine yeast (Saccharomyces cerevisiae) to inhibit malolactic bacteria (Oenococcus oeni) and the influence of nitrogen were studied using a synthetic grape juice. Malolactic fermentation was induced in fermenting synthetic grape juice or synthetic wines inoculated with different commercial strains of S. cerevisiae. O. oeni was generally inhibited in wines that contained higher concentrations of total SO2 although many yeast strains only inhibited the bacteria during fermentation under high nitrogen conditions. Yeast produced higher amounts of SO2 during fermentation under high nitrogen conditions suggesting that nitrogen affected the malolactic fermentation by influencing yeast SO2 production. However, the production of SO2 by yeast did not always account for the inhibition of O. oeni, suggesting the presence of other inhibitory mechanisms.