Projects

Spoilage of bulk-stored grain leads to decreased nutritional value and poses health hazards due to the formation of irritating volatile metabolites inside grain bins. Co-occurrence of insect species and molds are common in a stored-grain ecosystem and are the causes of spoilage. In this study, new chemical signatures and volatile compounds evolving from grain having a combination of molds and insects were identified. The results of this research provided confident information for the development of odor sensor arrays for grain quality monitoring. In this project, Gas Chromatography and Mass Spectrometric (GC-MS) analysis of the gas samples trapped in dimethylpoly-siloxane was performed. The analytical data from the GC-MS spectra were validated, interpreted and compared using the NIST/NIH (National Institute of Standards and Technology and National Institute of Health, USA) Mass Spectral Library.

For high temperatures, corrosive and harsh environmental applications in the agricultural and food industry, SiCN based sensors are preferred. Experimental methods for making thin films of SiCN to facilitate sensor fabrication is explored in this study. Silicon carbonitride films were grown on silicon substrate using ammonia and hexamethyldisilazane gas sources using catalytic chemical vapour deposition process. Parameter regimes such as influence of flow rates of target gas and variation in substrate temperature are identified for effective deposition of SiCN thin films. Compositions of silicon, carbon and nitrogen in the SiCN films were varied by changing the flow rate of ammonia gas. The effect of deposition conditions on the structural, optical and mechanical properties of SiCN thin films was examined. X-ray photoelectron spectroscopy analysis indicated that the higher flow rate of ammonia gas results in higher nitrogen and lower carbon content in the deposited thin films. The measurement of stress as a function of substrate temperature in the SiCN film showed that the stress changes from compressive to tensile in the range of 275°C to 325°C.

grain moisture contentPhysical appearance and kernel morphology significantly affect the grade of a harvested crop in addition to other factors such as test weight, percentage of foreign matter and constituent components. Moisture content of grain can potentially affect the physical appearance and kernel morphology, which in turn affects the grade of the harvested crop. In this project, we evaluated the effect of moisture content on the classification capability of color, morphology and textural features of imaged grains. Color images of individual kernels and bulk samples of wheat and barley were acquired using a high resolution color camera with an IEEE 1394 interface machine vision system. Algorithms developed by Grain Storage Research Laboratory were implemented to extract color, textural and morphological features from grain images. Image segmentation was applied to remove the background from the single kernel images. The extracted features were analyzed and classified for the effect of moisture content using statistical classifiers and a devised back propagation neural network model.

Link to paper

software x raySprouted wheat kernels adversely affect bread and pasta making quality, thus lowering the grade and value to millers, bakers and grain dealers. In this study, the potential of using soft X-ray system in detecting the sprouted wheat kernels was evaluated. Sprouted kernels were produced by germinating seeds. Both the sprouted and healthy samples were X-rayed using a soft X-ray system. White specks were observed in all the sprouted kernel X-ray images. Algorithms were written to extract 55 image features including gray level modeling and histogram from the scanned images. Identification of sprouted and healthy kernels was determined using statistical and neural network classifiers. A four-layer back propagation neural network model correctly classified 90% and 95% of the sprouted and healthy kernels, respectively. Statistical classifier correctly identified 87% and 92% of the sprouted and healthy kernels, respectively.

Link to paper

DurumKnowledge of the structure and properties of microscopic surfaces of durum wheat starch granules is essential for understanding the functional and physico-chemical properties. The nanoscale surface undulations on the starch granules inside durum wheat macroscopically influence the milling properties. The objective of this study was to visualize the size and dispersion of the starch grains in vitreous and non-vitreous durum wheat kernels using atomic force microscopy. The distribution of starch granules in the vitreous and non-vitreous durum wheat starch samples were examined and compared. The results of our study confirm the ‘blocklet’ model of the ultra structure of the starch granule surface. Image contrast enhancement using UV/Ozone treatment of microtomed starch samples improved the characterization of growth rings on the starch samples. The observation of growth rings in the non-vitreous starch granule surfaces indicates that amylopectin is more common than amylose compared to the composition of vitreous starch.

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Contact Us

Bionanotechnology Laboratory
Suresh Neethirajan

School of Engineering
University of Guelph
Guelph, Ontario
Canada N1G 2W1

Office:
Room 3513 - Richards Building
50 Stone Road East

Lab: THRN 2133 BioNano Lab

Phone: (519) 824-4120 Ext 53922
Fax: (519) 836-0227

E-mail: sneethir@uoguelph.ca

 
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