Thermal Conductivity of Fresh Lamb Meat, Offals and Fat in the Range ‐40 to +30oC: Measurements and Correlations

Meat Industry Research Institute of New Zealand (Inc.), PO Box 617, Hamilton, New Zealand
Journal of Food Science (Impact Factor: 1.78). 06/2008; 54(3):508 - 515. DOI: 10.1111/j.1365-2621.1989.tb04639.x

ABSTRACT The thermal conductivity of fresh lamb meat, offals and fat was measured over the temperature range -40°C to +30°C using a guarded hot plate apparatus. Simple empirical equations were presented for the conductivity of high-moisture (65 to 80%) meat and offals. With independently obtained values of physical parameters, several theoretical models were tested to sec if thermal conductivity could be calculated from composition and temperature. Over a wide range of compositions and temperatures, best predictions (in terms of mean, standard deviation and range of errors) were obtained with Levy's modification to the Maxwell-Eucken equation. Its accuracy was not unduly sensitive to the uncertainties in the values of the physical parameters, the prediction errors remaining in the range ± 10% for all reasonable values of the latter.

1 Bookmark
  • [Show abstract] [Hide abstract]
    ABSTRACT: The aim of this study was to investigate the effects of meat fiber directions and air conditions on moisture and temperature developments, shrinkage, and effective diffusivity constants compared to homogenous minced meat samples. The lean meat with three fiber directions and minced meat samples were dried at temperatures of 48 and 70°C and air flow rates of 0.5, 1.0, and 1.7 m/s. The minced meat samples showed 1.0 ± 0.19 to 4.4 ± 0.03°C higher temperature values and 2.3 ± 0.004 to 6.2 ± 0.003% lower moisture losses than the lean meat samples in all fiber directions. The lowest temperatures were observed in lean meat with h 1 (normal flow, normal drying) fiber direction. The highest moisture loss and diffusion coefficient were observed in lean meat with h 2 (parallel flow, normal drying) and v (normal flow, parallel drying) fiber directions, which also possessed the shortest drying times (10.4 and 13.4 h, respectively). The estimated diffusion coefficient values ranged between 1.11 × 10−9 and 5.54 × 10−9. The results indicated that lean and minced meat samples differed in their drying behaviors in a tray dryer under the tested conditions with >90% reproducibility (or ≤10% coefficient of variation).
    Drying Technology 04/2014; 32(6). DOI:10.1080/07373937.2013.855784 · 1.77 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Recibido para revisar 19 de Octubre de 2004, aceptado 29 de Agosto de 2005, versión final 1 de Octubre de 2005 RESUMEN: Una recopilación de las publicaciones sobre los métodos utilizados para medir las propiedades termofísicas de la carne, los modelos matemáticos asociados y los valores publicados se presenta en este trabajo. Se incluyen propiedades como: la conductividad térmica, la difusividad térmica, el calor específico y la temperatura inicial de congelación. Se halló que el estudio de las propiedades termofísicas de la carne carece de modelos confiables que permitan predecir su comportamiento en diferentes condiciones de procesamiento, además los valores publicados presentan una dispersión que afecta su precisión. ABSTRACT: A review of publications on methods used for measuring thermophysical properties of meat, mathematical models associated and published values is presented in this paper. Some of the properties included are: thermal conductivity, thermal diffusivity, heat capacity and freezing point. It was found that the study of the thermophysical properties of meat lacks reliable models that allow to predict their behavior under different processing conditions and that published values present a dispersion that affects their precision.
    Dyna (Medellin, Colombia) 03/2006; 73(148):103-118. · 0.22 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Existing food freezing time formulas have not been tested on low moisture, low freezing point foods or cryogenic temperatures. A systematic numerical experiment was therefore performed to generate freezing times over a wide range of parameters, never before covered in the literature, yet still within industrial practice. The results were used to evaluate four well-known freezing time formulas. Pham’s first (three-stage) method has the best theoretical basis and fewest empirical parameters, and agrees best with numerical predictions. By applying simple correction factors, this method agrees with numerical predictions to within ±10% while Pham’s second (two-stage) method is almost as accurate. For the freezing time of fresh foods (Tf ⩾ −1.5 °C), Pham’s first method can be used without modification. The corrected formulas remain accurate under cryogenic freezing conditions.
    Journal of Food Engineering 04/2014; 127:85–92. DOI:10.1016/j.jfoodeng.2013.12.007 · 2.58 Impact Factor