Evaluation of an electronic nose for monitoring roasting of cashew kernels | |
| Author | Mohapatra, Punyatoya |
| Call Number | AIT Thesis no.FB-06-11 |
| Subject(s) | Cashew nut industry Food|xQuality--Evaluation |
| 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-06-11 |
| Abstract | Electronic nose technology finds its wide application in various areas including food and beverage industries for rapid non-destructive assessment of food quality. The rationale behind using this technology is to distinguish products based on their aroma and thereby determining the overall quality. The purpose of this study was to apply a portable electronic nose (Cyranose 320TM) to monitor the degree of roasting of cashew kernels. The e-nose was operated under ambient conditions (24±2°C). Initially, the performance of the instrument was evaluated with banana in different ripening stages to confirm its capability for product classification. It was necessary to incubate the cashew kernels at 50°C prior to their exposure to e-nose. The odor patterns of cashew kernels roasted at 140, 160 and 180°C for different time intervals were obtained. The instrumental quality measurement parameters such as Kramer shear force (F), lightness index (L*) and total color difference (DE*) of roasted cashew kernels were modeled to account for the effect of roasting time and temperature indicating coefficient of determination (R2) of 0.98, 0.93 and 0.94, respectively. The summation of changes in resistances of all sensors (EAR;/Ro) and the area computed from the radar plots (Y-A) for different e-nose sensor output patterns were also related to the degree of roasting of cashew kernels similar to instrumental quality measurement parameters. Also, there were high correlation coefficients between the parameters derived from c-nose patterns and instrumental measurements such as F, L* and AE*. Principal component analysis showed that about 99.41% and 0.28% variations in e-nose sensor output patterns were accounted by the first and second principal component, respectively. Developed partial least squares regression (PLSR) models predicted F, L* and DE* of roasted cashew kernels from the e-nose sensor response patterns with R2 value of 0.839, 0.86 and 0.89, respectively. The validation of PLSR models with an independent set of experimental data showed that F, L* and AE* for roasted cashew kernels could be predicted from the e-nose sensor response patterns with R2 of 0.905, 0.86 and 0.901, respectively. Results of this study showed that an c-nose could be used for monitoring the roasting of cashew kernels in hot air. |
| Year | 2006 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. FB-06-11 |
| Type | Thesis |
| School | School of Environment, Resources, and Development (SERD) |
| Department | Other Field of Studies (No Department) |
| Academic Program/FoS | Food Engineering and Bioprocess Technology (FB) |
| Chairperson(s) | Athapol Noomhorm; Jindal, V. K. |
| Examination Committee(s) | Rakshit, Sudip Kumar |
| Scholarship Donor(s) | AIT Fellowship |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2006 |