Degree Type


Date of Award


Degree Name

Doctor of Philosophy


Agricultural and Biosystems Engineering

First Advisor

Chenxu Yu


Technical progresses in the past two decades in instrumental design, laser and electronic technology, and computer-based data analysis have made Raman spectroscopy, a noninvasive, nondestructive optical molecular spectroscopic imaging technique, an attractive choice for analytical tasks. Raman spectroscopy provides chemical structural information at molecular level with minimal sample preparation in a quick, easy-to-operate and reproducible fashion. In recent years it has been applied more and more to the analysis and characterization of agricultural products and biological samples. This dissertation documents the innovative research in Raman spectroscopic characterization and analysis in both biomedical and agricultural systems that I have been working on throughout my PhD training.

The biomedical research conducted was focused on glaucoma. Glaucoma is a chronic neurodegenerative disease characterized by apoptosis of retinal ganglion cells and subsequent loss of visual function. Early detection of pathological changes and progression in glaucoma and other neuroretinal diseases, which is critical for the prevention of permanent structural damage and irreversible vision loss, remains a great challenge. In my research, the Raman spectra from canine retinal tissues were subjected to multivariate discriminant analysis with a support vector machine algorithm to differentiate disease tissues versus healthy tissues. The high classification accuracy suggests that Raman spectroscopic screening can be used for in vitro detection of glaucomatous changes in retinal tissue not only at late stage but also at early stage with high specificity.

To expand the scope of application of Raman analysis, it was also applied to characterize agricultural and food materials. More specifically, Raman spectroscopy was applied to analyze meat. Existing objective methods (e.g., mechanical stress/strain analysis, near infrared spectroscopy) to predict sensory attributes of pork in general do not yield satisfactory correlation to panel evaluations. Raman spectroscopic methodology was investigated in this study to evaluate and predict tenderness, juiciness and chewiness of fresh, uncooked pork loins from 169 pigs. The method developed in this thesis yielded good prediction of sensory attributes such as tenderness and chewiness, and it has the potential to become a rapid objective assay for tenderness and chewiness of pork products that may find practical applications in pork industry. In addition, a Raman spectroscopic screening method in conjunction with discriminant modeling was developed for rapid evaluation of boar taint level in pork. Through the research demonstrated in this dissertation, Raman spectroscopy has been shown to have great potential to address analytical needs in new fields with great potential for innovative applications.


Copyright Owner

Qi Wang



File Format


File Size

157 pages