The performance of a dynamic stability test for moisture sensitivity

Haralampu, Stephen G.; Saguy, I. Sam; Karel, Marcus

doi:10.1016/0270-0255(86)90118-1

Cited by 7 publications

(2 citation statements)

References 3 publications

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“…The estimated parameters should be judged on the size of 0 EX;ERIME;TAL the joint confidence region at a 90% (or any other) level. This region is the ellipsoid in which the true parameters probably exist together at a specified confidence level (Cohen and Saquy, 1985;Draper and Smith, 1981;Haralampu et al, 1986). The confidence contour was derived by implementing the Draper and Smith's (1981) technique.…”

Section: Nonenzymaticmentioning

confidence: 99%

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Kinetic Parameter Estimation for Quality Change during Continuous Thermal Processing of Grapefruit Juice

Cohen

Birk

Mannheim

et al. 1994

Journal of Food Science

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Reaction order, activation energy (E,) and average rate constant (k,) were evaluated by dynamic modeling for color degradation of grapefruit juice during thermal processing. Simulated aseptic conditions were: 85-135"C, 40-175 set processing time, and average velocities 5-30 cm/set. Quality was assessed by nonenzymatic browning index (NEBI) and S-hydroxymethyl-furfural (HMF). Average values for reaction-order and energy of activation were: 0 and 21.4 kcal/g-mol (NEBI) and 0.3 and 23.2 kcal/g-mol (HMF), respectively. These values were compared with those contained in the deformed ellipsoid which define the 90% joint confidence interval of all possible parameter combinations. Based on initial and final concentrations, the method can predict effects of processing on liquid foods.

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Section: Nonenzymaticmentioning

confidence: 99%

“…The concept of kinetic studies under dynamic thermal conditions originated in the pharmaceutical industry (Rogers, 1963). For food products, the dynamic approach was implemented in various processes (e.g., Haralampu et al, 1986;Mishkin et al, 1984;Saguy et al, 1978b;Nunes and Swartzel, 1990).…”

Section: Introductionmentioning

confidence: 99%