Early detection of weed resistance : pattern-thinking and rapid microcalorimetric assay Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/jw827f50j

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  • Weed resistance is usually diagnosed after a weed control practice has lost efficacy and weed populations begin to increase rapidly. Prediction and validation in the field at a very early stage of resistance development is a promising method for preventing an uncontrollable problem. Pattern-thinking helped individuals connect their experience of weed infestations with development of weed resistance. Field representatives connected early verification with immediate management to reduce the potential problem of weed resistance. A method for rapid detection of weed resistance by microcalorimetry was developed to distinguish between herbicide resistant and susceptible biotypes. This general method was used to test three different weed species and three different herbicide modes of action. Heat evolution as a product of plant respiration by samples of meristematic tissue was compared between resistant and susceptible biotypes. The procedure readily distinguished between biotypes. Since microcalorimetry provided quick and accurate results, all field representatives stated that the combination of pattern-thinking and rapid assay would improve management of weed resistant populations. The combination would improve visual detection based on the standard growth and development model for weed resistance and population growth. Also, biological verification using microcalorimetry provides immediate feedback and validation of weed resistance. Thus, early detection of weed resistance is a very important tool which will assist farmers in dynamically managing weed infestations.
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  • File scanned at 300 ppi (Monochrome) using Scamax Scan+ V.1.0.32.10766 on a Scanmax 412CD by InoTec in PDF format. LuraDocument PDF Compressor V.5.8.71.50 used for pdf compression and textual OCR.
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  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2011-11-17T22:41:50Z (GMT) No. of bitstreams: 1 SUWANAGULDUANGPORN1996.pdf: 886235 bytes, checksum: 0f092383b30b38c58b4d110519e81953 (MD5)
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