Assessments of Biomaterials Using Non-Destructive Optical Inspection
Date Issued
2009
Date
2009
Author(s)
Yang, I-Chang
Abstract
Non-destructive and non-invasive inspection of biomaterials is a relatively new technology. The detection apparatus design depends on the purpose of the inspection, such as whether external or internal quality is of interest. There are three parts in this dissertation. From the view point of the optical analysis, the safety and quality issues of grain were discussed in the first two parts, and the monitoring and management of seedling production in the greenhouse was also elaborated in this dissertation. These three parts are summarized as follows: First, a study was implemented to develop more efficient methods for optically detecting wheat kernels damaged by Fusarium head blight, a fungal disease that is usually accompanied by the mycotoxin, deoxynivalenol. Through development of a high-power pulsed LED (green and red light) inspection system, it was found that Fusarium-damaged and normal wheat kernels have different reflected energy responses. Two parameters (slope and coefficient of determination r2) from a regression analysis of the green and red LED responses were used as input parameters in linear discriminant analysis models. The examined factors affecting accuracy were the orientation of the optical probe, the color contrast between normal and Fusarium-damaged kernels, and the manner in which one LED’s response was time-matched to the other LED. The current research on free-falling kernels has demonstrated accuracies (>90% for wheat samples with high visual contrast) that approach those of controlled, in-laboratory conditions. This approach may lead to improvements in high-speed optical sorters. Second, a feasibility study was conducted on the use of hyperspectral imaging to differentiate sound wheat kernels from those with a damage condition called black point. Through analysis of wavelength images, one fluorescence wavelength (531 nm) was selected for image processing and classification analysis. Results indicated that with this wavelength alone, classification accuracy could be as high as 95% when kernels were oriented with their dorsal side toward the camera. Third, a system was designed and implemented for precision cultivation and micro-environment monitoring for seedling production in the greenhouse. Based on RFID-integrated multi-functional remote sensors with a plant-oriented sensing algorithm for both monitoring and controlling the greenhouse environment, the system linked spectral and environmental inputs for the control of seedling irrigation. Further, the study aimed to construct a traceability system for seedling production in greenhouses using RFID technology. The contents of the developed database were divided into two parts, a management traceability system and an environment traceability system. The traceability systems provided the operators with records of seedling growth and management history and served as the decision bases for spray and related operations.
Subjects
Biomaterials
Optical Inspection
Wheat Kernel
Fusarium Head Blight
Seedlings
Greenhouse
RFID (Radio Frequency Identification)
Spectral Imaging
Type
thesis
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