Monitoring the properties of the heat-treated cassava starch by near infrared spectroscopy | |
| Author | Pansa Liplap |
| Call Number | AIT Thesis no.FB-05-18 |
| Subject(s) | Cassava industry Starch--Drying Near infrared spectroscopy Cassava--Drying |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Environment, Resources and Development |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. FB-05-18 |
| Abstract | Cassava starch was impregnated with ionic gums (sodium alginate, CMC and xanthan) in aqueous solution to levels of 1, 2 and 3% concentration and the pH adjusted to 6, 7 and 8. The wet starch samples were then dried at 50°C in hot air oven to reduce the moisture to about 5-8%. Subsequently, the dry starch samples were heat-treated at 120, 140 and 160°C in dry state for 0, 1, 2, 4 and 8 hours. Following heat treatments, the starch samples were analyzed by the Rapid Visco Analyzer for determining pasting properties as well as near infrared spectrophotometer in 1000-2500 rim range of wavelength. Cassava starch displayed a trend in which the pasting viscosity decreased as the heating time increased. Decreasing level of pasting viscogram depended on heating temperature especially at 160°C showed substantial decrease in pasting viscosity. For starch impregnated with various types of gums, xanthan gum showed greater changes in viscogram changes than sodium alginate and CMC. Use of ionic gums in the heat treatment produced product with restricted granular swelling similar to the chemically crosslinked starch. It was concluded that the changes in the properties of heat-treated starch mainly depended on gum type, heating time and temperature. The multiple linear regression models indicated the coefficient of determination (R2) values ranging from 0.60.8 especially for peak, breakdown and trough viscosities. The changes in the properties (RVA parameters) of heat-treated starch were correlated with NIR spectra using multiple linear regression (MLR), partial least square regression (PLSR), and artificial neural networks (ANNs). Separate models were developed for different types of gums. The best models for the prediction of pasting parameters were derived from ANN technique which showed high correlation coefficients in the ranges of 0.814-0.956, 0.833-0.925 and 0.752-0.927 for sodium alginate, xanthan and CMC gum, respectively. However, the accuracy of prediction was still not satisfactory because of relatively high error of prediction. The RMSEP in case of sodium alginate, xanthan and CMC were in the ranges of 6.983-28.277, 13.241-53.845 and 15.642-31.017 RVU, respectively. The comparison of multivariate mathematical models showed that both ANN and PLSR gave better results than MLR. The ANN generally indicated better performance in terms of correlation coefficient and RMSEP. It was concluded that the NIR spectroscopy could be used as a rapid and nondestructive method for the prediction or classification of pasting parameters of heat treated cassava starch impregnated with gums. |
| Year | 2005 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. FB-05-18 |
| 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 | Food Engineering and Bioprocess Technology (FB) |
| Chairperson(s) | Jindal, Vinod Kumar; |
| Examination Committee(s) | Athapol Noomhorm ;Rakshit, Sudip Kumar; |
| Scholarship Donor(s) | Royal Thai Government Fellowship; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2005 |