Mechanical and acoustical testing of snack food texture | |
| Author | Weena Srisawas |
| Call Number | AIT Thesis no.PH-00-19 |
| Subject(s) | Snack food industry Food--Quality |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science |
| Publisher | Asian Institute of Technology |
| Abstract | In this study, the applications of mechanical and acoustical measurements were investigated for the evaluation of crispness of selected snack foods; Pringles potato chips, Paprika extruded snack and Munchy crackers. At first, the relationships between sensory crispness and moisture content of three snack food products at moisture content ranging from 2 to 10 % db were examined. Moisture content was found highly related with sensory crispness and could be used for its estimation. Mechanical properties of snack foods were determined from the force-deformation curves and related to the moisture content of samples using stepwise multiple regression (SMR) and backpropagation neural network (NN) techniques. The sound generated by breaking the samples with a pair of pincers was recorded digitally with a microphone fixed 3 cm away from the product. The features of the sound signals were extracted by applying fast Fourier transform to obtained frequency domain spectra. Amplitudes at fixed frequencies were used to train backpropagation neural networks with moisture content as output. The results showed the effectiveness of the techniques employed to extract and use sound signal features for quality evaluation in terms of moisture content and sensory crispness. Backpropagation NN models performed slightly better than SMR models for the moisture content prediction. Better predictions were obtained with acoustical inputs than the mechanical inputs for Pringles potato chips and Munchy cracker models. Finally, probabilistic NN models were applied to classify the products based on four grades of sensory crispness to an accuracy of about 98, 96 and 98 % for Pringles potato chips, Paprika extruded snack and Munchy crackers, respectively. The results of this study successfully showed the development of techniques used to analyze experimental acoustic data for developing NN models to predict the quality of snack products. |
| Year | 2000 |
| Type | Thesis |
| School | School of Environment, Resources, and Development (SERD) |
| Department | Department of Food, Agriculture and Natural Resources (Former title: Department of Food Agriculture, and BioResources (DFAB)) |
| Academic Program/FoS | Postharvest and Food Process Engineering (PH) |
| Chairperson(s) | Jindal, Vinod K.; |
| Examination Committee(s) | Athapol Noomhorm ;Rakshit, Sudip K.; |
| Scholarship Donor(s) | Asian Institute of Technology (Partial Scholarship);JFK scholarship; |
| Degree | Thesis (M.Sc.) - Asian Institute of Technology, 2000 |