Engineering properties of Cassia tora L. seeds and meal as a function of moisture content

Engineering properties are of great importance for Cassia tora L. seeds in aspects of harvesting, handling mechanical design and product processing. The effect of moisture content (7, 10, 13, 16 and 19%) (wet basis) on the properties: physical (length, width, bulk and true density, porosity, thousand seeds mass, coefficient of static friction and angle of repose), mechanical (hardness, fragmentation energy and failure deformations), and thermal (specific heat, thermal conductivity and thermal diffusivity), were systematically studied. As the moisture contents increase from 7 to 19%, the length (L) increased from 4.52 to 5.87 mm, the thickness (T) from 2.51 to 3.21 mm and the width (W) from 2.36 to 3.02 mm, respectively. The bulk and true density of Cassia tora L. seeds decreased from 775.83 to 654.17 kg/m³ and from 1295.21 to 1154.72 kg/m³, respectively, with the moisture content raised from 7 to 19%. The thermal conductivity of Cassia tora L. seeds meal was found to be 0.068-0.098 W m^-1 K^-1, 0.078-0.112 W m^-1 K^-1, 0.089-0.125 W m^-1 K^-1, 0.098-0.136 W m^-1 K^-1, 0.108-0.148 W m^-1 K^-1, 0.119-0.159 W m^-1 K^-1, respectively, at 25 °C, 45 °C, 65 °C, 85 °C, 105 °C and 125 °C in moisture ranges of 7-19%. The thermal diffusivity was found to decrease from 5.21 × 10^-8 to 4.53 × 10^-8 m²/s, from 5.75 × 10^-8 to 4.91 × 10^-8 m²/s, from 6.11 × 10^-8 to 5.17 × 10^-8 m²/s, from 6.52 × 10^-8 to 5.36 × 10^-8 m²/s, from 7.17 × 10^-8 to 5.77 × 10^-8 m²/s, from 7.36 × 10^-8 to 5.84 × 10^-8 m²/s, respectively, at 25 °C, 45 °C, 65 °C, 85 °C, 105 °C and 125 °C in moisture ranges of 7-19%. The results suggested that physical properties exhibited linear relationships with moisture content using the regression model, while mechanical properties showed a second-order polynomial relationship with moisture content. Furthermore, significant variation existed in thermal properties because of differentiate moisture content and temperature. These data and rules are also useful for high efficiency machines design and mechanisms development.