Equipment developed for biological systems frequently use microprocessors that are activated by electronic or biological sensors. Recent advances in electronic vision and computer technology have opened the research horizons for greater accuracy in process control, product sorting, and machine operation.
Several projects focus on biosensor technology. One involves the development of an on-line sensor for reproductive hormones in milk. This biosensor utilizes an immuno-reaction of molecular recognition and photometric sensing for transduction to an electron signal. Two other projects related to milk products involve the development of an enzyme-sensor for on-line measurement of milk urea for improving dairy herd nutritional management, and the creation of a rapid immunoassay for measuring antibiotic residues in milk. The goal of a fourth project is the development of a biosensor for detecting pesticide residues on farm produce and worker exposure to pesticides. Hardware includes a fluorescent immunoassay, an infrared laser diode, and a high sensitivity photodiode. As with most of our department’s projects, these include collaborators from elsewhere on campus.
For quality assessment, grading, and sorting of biological products, several types of electronic sensors are being investigated for providing rapid and non-destructive determination of internal qualities. For example, we have developed a near infrared (NIR) sensing technique that can rapidly determine the sugar content of intact peaches. This technology is being extended to a number of other commodities, including avocados for oil content, and kiwifruit for starch and sugar content. Results of previous studies have shown that nuclear magnetic resonance (NMR) techniques can be used for nondestructive evaluation of various internal quality factors, such as bruises, dry regions, worm damage, stage of maturity, oil content, sugar content, tissue breakdown, and the presence of voids, seeds, and pits. Recent research has demonstrated the feasibility of using NMR techniques for high-speed on-line sensing of fruit and vegetable qualities.
Machine vision for postharvest sorting and grading is being developed for a number of commodities. Recent research has included development of a high-speed prune defect sorter, color and defect detection for fresh-market stone fruits, raisin grading, and flower grading. In this technology, electronic cameras are used for viewing the product in various packing-line handling situations. Quality features are computed from digitized images, and a control system allows for grading and sorting. Machine vision has also been used on other projects for reducing the need of herbicide use on farms and roadways.
This cooperative research project with industry personnel is aimed at developing color sorting instruments for use in tomato grading stations.
Molecular recognition with a biosensor is often accomplished through the use of an antibody, which selectively binds to the target molecule. Here, monoclonal antibodies for penicillin are being produced in cell culture
A biosensor has been developed for detection of penicillin residues in food. The sensor implements an antibody capture assay using micro-injection pumps and valves under computer control.
Reproductive management is a major financial concern for the dairy industry, with missed attempts at breeding being a significant cause of lost income. Missed breeding is caused by an inability to accurately detect estrus. This biosensor has been developed for on-line measurement of bovine progesterone. The assay was adapted to a computer controlled sensor using miniature valves and pumps, fiber optics, and photoelectronics.
Accelerometers placed within a truck load of strawberries destined for the eastern US provide an insight into vibration damage of the fruit. Optimal procedures for packaging the fruit and suitable transport trailer suspensions have been studied