Knowledge of physical properties of crops is necessary for the development of processing machines. Relationships between the various physical properties of crops could also be useful in ensuring proper handling and more efficient design of processing machineries. This study was therefore, aimed at developing mathematical models for predicting the mass and volume of Tacca involucrata tubers using some physical characteristics of the crop. Physical characteristics of Tacca tubers at average moisture content of 73.3% (wet basis) namely axial dimensions, Arithmetic Mean Diameter (AMD), Geometric Mean Diameter (GMD), projected areas along the three mutually-perpendicular axes, criterion area (Ac), mass and volume were determined. Out of 240 samples used in the study, data from 120 samples were used for development of the prediction models while the remaining were used for validation of the developed models. Data analysis tool in Microsoft Excel (2013 version) was used to carry out regression analysis and develop the predictive models. Statistical parameters namely correlation coefficient, coefficient of determination, root mean square error and mean bias error were used to determine the goodness of fit of the predictive models. The mass and volume models were divided into three classifications namely: single and multiple variable regression models based on axial dimensions; single and multiple variable regression models based on the projected areas; single variable regression model based on volume (for mass prediction only). Average length, width, thickness, AMD and GMD of the tubers were 71.88, 57.22, 46.71, 58.60 and 57.57 mm respectively while average criterion area, longitudinal, cross-sectional and transversal projected areas were 2614.24, 2580.61, 2097.04 and 3165.07 mm2 respectively. Average mass and volume of the tubers were 129.30 g and 111.55 cm3 respectively. All the developed models performed well in predicting the mass and volume of Tacca tubers (R2 ≥ 0. 905) except for those based on the axial dimensions as single independent variables (R2 ≤ 0.890). The predicted mass and volume of Tacca tubers were not significantly different (p ≤ 0.05) from the experimentally observed values for all the classifications considered. Mass and volume modelling based on a single variable of any of the projected areas was the most convenient modelling for Tacca tubers since it involves the use of a single image capturing device and the whole measurement could therefore, be automated. The developed models would be useful for automated sorting and packaging of Tacca tubers.
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