Agrivoltaic systems combine solar energy and agriculture, promoting dual land use. Although grazing sheep in these systems is common, research on intentionally designed pastures to increase production is lacking. This study seeks to compare the herbage growth and lamb production in simple, diverse, and legume pastures in an agrivoltaic system...
Listeria monocytogenes contamination continues to pose challenges for the food industry and there is demand for effective methods of food preservation and protection that can also be considered clean label. A promising source of antilisterial compounds may be sourced from bacteria that produce novel byproducts. Ribosomally synthesized and post-translationally modified...
The information in this report is for the purpose of informing cooperators in industry, colleagues at other universities, and others of the results of research in field crops. Reference to products and companies in this publication is for specific information only and does not endorse or recommend that product or...
This report includes information concerning experimental use of unregistered pesticides or unregistered uses of pesticides. Experimental results should not be interpreted as recommendations for use. Use of unregistered materials or use of any registered pesticides inconsistent with its label is against both Federal Law and State Law.
A dissertation describing the results of a series of greenhouse experiments conducted to better understand phytoremediation in stormwater bioretention systems.
The Columbia River Gillnetter is the pilot of the Lower Columbia River commercial fishing industry, keeping fishermen and the public in touch with today's important issues.
The purpose of this project is to design and implement an intermediate language interpreter for a very high level language called Bagit. The Bagit compiler produces Bcode, and this in turn is interpreted by the program described in this report.
Iterative algorithms are simple yet efficient in solving large-scale optimization problems in practice. With a surge in the amount of data in past decades, these methods have become increasingly important in many application areas including matrix/tensor recovery, deep learning, data mining, and reinforcement learning. To optimize or improve iterative algorithms,...