Methods of Determination for Effective Diffusion Coefficient During Convective Drying of Clay Products
© 2012 Vasic et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Methods of Determination for Effective Diffusion Coefficient During Convective Drying of Clay Products
Heat and mass transfer models in convection drying of clay slabs
Abstract Drying kinetics data for convection drying of industrially prepared roof tile clay slab were approximated with different mathematical models. Applied conventional model analysis enables evaluation of main transport properties: effective diffusion coefficient, mass and heat transfer coefficients, thermal conductivity, drying constant, and exponential model parameters. A neural network-based drying model was established using backpropagation algorithm for dynamics modelling of moisture content and temperature of thin clay sample. Obtained results confirm the assumption that both, the heat and mass transfers, are under external conditions. Very small values of Biot numbers confirm that fact. Drying air temperature and initial moisture content of clay strongly influence the drying kinetics and transport properties. The dependence between the drying air temperature and evaluated transport properties shows an exponential trend. Tomas and Skansi exponential model parameter, n , is independent from temperature. At lower values of initial moisture content of clay higher drying rates are achieved, which results with higher values of calculated transport properties. It was shown that neural network as an alternative method has potential for modelling the drying process and predicting drying dynamics based on experimental data.
Genetics of the phenotypic evolution in sheep: a molecular look at diversity-driving genes
Background After domestication, the evolution of phenotypically-varied sheep breeds has generated rich biodiversity. This wide phenotypic variation arises as a result of hidden genomic changes that range from a single nucleotide to several thousands of nucleotides. Thus, it is of interest and significance to reveal and understand the genomic changes underlying the phenotypic variation of sheep breeds in order to drive selection towards economically important traits. Review Various traits contribute to the emergence of variation in sheep phenotypic characteristics, including coat color, horns, tail, wool, ears, udder, vertebrae, among others. The genes that determine most of these phenotypic traits have been investigated, which has generated knowledge regarding the genetic determinism of several agriculturally-relevant traits in sheep. In this review, we discuss the genomic knowledge that has emerged in the past few decades regarding the phenotypic traits in sheep, and our ultimate aim is to encourage its practical application in sheep breeding. In addition, in order to expand the current understanding of the sheep genome, we shed light on research gaps that require further investigation. Conclusions Although significant research efforts have been conducted in the past few decades, several aspects of the sheep genome remain unexplored. For the full utilization of the current knowledge of the sheep genome, a wide practical application is still required in order to boost sheep productive performance and contribute to the generation of improved sheep breeds. The accumulated knowledge on the sheep genome will help advance and strengthen sheep breeding programs to face future challenges in the sector, such as climate change, global human population growth, and the increasing demand for products of animal origin.