Interpretation of Nonlogarithmic Survivor Curves of Heated Bacteria

Abstract

Complex survivor curves of heated bacteria are interpreted to be composites of several convex survivor cutves that represent populations of different heat resistances in a single culture of bacteria.The variation in heat resistance appears to be physiological rather than genetic since subcultures of heat-resistant cells were no more heat resistant than the parent culture. Composite cures can appear to be nearly exponential.Results support a multiple-site hypothesis of thermal death. Tailing of survivor curves, with small numbers of cells surviving extended heating, wus frequently noted when curves were carried through 6-9 log cycles. Such tailing might be of practical importance because it would predict that small numbers of cells might survive much longer heating than would be predicted from D-values calculated from curves carried through 4-5 log cycles.

The effect of high hydrostatic pressure on Listeria monocytogenes in phosphate‐buffered saline and model food systems

“…Even though inactivation of cells within each clump would (1992) found that inactivation of E. coli by high pressure was logarithmic at 250 MPa for 20 min at 40°and 50°C. However, as has been widely documented in thermal and irradiation resistance studies (Moats 1971;Moats et al 1971; Silverman at below 30°C, a small proportion of survivors appeared to be less sensitive to pressure, resulting in a tailing effect. This and Sinskey 1977), inactivation by high pressure did not always follow simple first order kinetics (logarithmic death effect could be a result of the membranes of these cells undergoing a liquid crystalline to gel transition at ¼30°C.…”

“…These tended to be an initial rapid reduction in numbers followed by a gradual tailing off in the inactivation rate. Inactivation differences are illustrated by the D-values listed in Tables 2 Table 2 Decimal reduction time values* (D-values, min) for the ------------------------------------------------------temperature ----------------------------------------------------- ----------------------------------------------------- ----------------------------------------------------- --------------------------------------------------- ----------------------------------------------------- it undergoes an increase in hydration due partly to the elecobtained for inactivation of Lm1 and Lm3 in 8% (w/v) BSA trostriction of water molecules around newly exposed charged were 18·7 and 17·4 min, respectively, compared to 12·4 and groups (Masson 1992). It may be possible that once the 12·1 min for inactivation of these strains in 10% (w/v) denaturant (i.e.…”

“…The results seemed to the cell in a homogeneous population, which subsequently results in the inability of the cell to reproduce and form a indicate that there is a threshold concentration of these basic food constituents below which no protection is conferred on visible colony (Moats et al 1971). This form of survivor curve, exhibited most closely and frequently in this study by L. monocytogenes, and that this threshold is dependent to a large extent on the severity of the treatment and strain constrain Lm1, enables easy quantification of the effects of lethal treatments by the calculation of decimal reduction or Dcerned.…”

Thermal inactivation ofEscherichia coliO157:H7

“…Indeed Pflug and Holcomb (1991) estimated that only one-third of thermal destruction data follow such kinetics. Deviations take the form of shoulders or tails, and this subject has been reviewed (Moats et al 1971;Cerf 1977). There are two basic explanations why first-order kinetics are not followed.…”

“…Some are based on understanding the physiological mechanism of inactivation. For example, Moats et al (1971) assumed that targets are clumped at critical sites within the cell, Kormendy and Kormendy (1997) assumed that there is a distribution of resistance within the population, and Smerage and Teixeira (1993) assumed that heterogeneity occurs by adaptation to heat during heating. Other models involve empirical curve fitting (e.g.…”