Citation
Roslan, Syazili and Razali, Mohd. Hudzari and Mustafa, Kamarul Ain and Wan Ismail, Wan Ishak and Abbas, Zulkifly and Zainuddin, Mohamad Faiz
(2013)
Rapid detection techniques for mechanical properties
Determination on surface of dioscorea hispida rhizome.
Procedia Engineering, 68.
pp. 446-452.
ISSN 1877-7058
Abstract
This study introduces the potential of microwave and machine vision application as the rapid detection method in determination the amount of alkaloid via contacting the surface of Dioscorea hispida rhizome. The importance to determine the amount of alkaloid because the rhizome only can be consumed after some detoxified process, so the amount of flowing water needed can be calculated and time needed will be decreased. For microwave device, the FieldFox Radio Frequency (RF) Analyzer is used in this
study while Chromameter CR-400 by Konica Minolta is used for machine vision device. This microwave device is used to
measure the coefficient permittivity of microwave level at rhizome surface using mechanical probe while machine device is used to measure the images of variety for harvested Dioscorea hispida will be captured at rhizome surface and the reading in L*a*b color space were converted. There was a correlation between microwave level and alkaloid content with regression, R2 is >0.8. Mathematical equation, y = 1E-05x6 - 0.0005x5 + 0.0072x4 - 0.0512x3 + 0.1727x2 - 0.204x + 0.382, where x=alkaloid content (%) and y= magnitude of the reflection coefficient (unitless) can be used to find the amount of the alkaloid in the tested rhizome. While correlation between hue color space and alkaloid content in the Dioscorea hispida rhizome samples is R2=0.9999 where the mathematical equation, y = -3E+07x4 + 2E+06x3 - 23045x2 + 106.84x + 48.901 where x=alkaloid content (%) and y= Hue value to find the amount of the alkaloid in the tested rhizome. This result means that this method can be used because the alkaloid level is also depending on the visual color of Dioscorea hispida rhizome. Using microwave device grouped as less destructive method while using machine vision device grouped as destructive method.
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