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dc.contributor.advisorApperley, Mark
dc.contributor.authorSmialowski, Grzegorz
dc.date.accessioned2014-08-01T04:39:52Z
dc.date.available2021-02-16T21:27:58Z
dc.date.issued2013
dc.identifier.citationSmialowski, G. (2013). Automatic Weighing for Dry Stock (Thesis, Master of Science (MSc)). University of Waikato, Hamilton, New Zealand. Retrieved from http://hdl.handle.net/10289/8763en
dc.identifier.urihttps://hdl.handle.net/10289/8763
dc.description.abstractThe aim of the research was to develop an accurate weight estimation algorithm for dry stock cattle using unsupervised walk-over equipment and to investigate the accuracy of the dairy cow algorithm for dry stock animals. Several customers and research organisations requested a suitable product for weighing dry stock, similar to the automatic weighing system for dairy cows. The development of the algorithm had to take into account the erratic behaviour of dry stock cattle. An additional requirement for the research was to improve cost effectiveness of the existing system, by removing the need for the lead-on platform. Data was collected from a series of dry stock herds, as they walked over the existing dairy cow walk-over weighing (WOW) platform, in either a paddock or a stockyard. All dry stock cattle were static weighed before walking over the WOW to obtain an accurate true weight of the animal. The weight estimations produced by the dairy cow algorithm were recorded and the raw load cell data was captured. The raw load cell data was then used to devise a new algorithm specifically for dry stock cattle. The new algorithm was tested against the collected load cell data from various herds. The dairy cow algorithm results were used to compare the accuracy of the existing algorithm on dry stock cattle. The new devised algorithm used a threshold to locate a rough start and end point for each walk-over event. The data between the initial start and end points was processed to locate the period which had the full weight of the cattle located on the weighing platform. The algorithm estimated the weight of the animal from the data between these points. It was found that the dairy cow algorithm was nearing the required accuracy, but was not able to determine weights for the majority of the animals. The new algorithm devised for dry stock cattle was unable to obtain an improvement in accuracy, but was able to estimate weights for a greater proportion of the cattle. Additionally the new algorithm was successful in eliminating the need for the lead-on platform for detecting animals.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherUniversity of Waikato
dc.rightsAll items in Research Commons are provided for private study and research purposes and are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectweighing
dc.subjectcattle
dc.subjectwalk over
dc.subjectbeef
dc.subjectdrystock
dc.subjectautomated
dc.titleAutomatic Weighing for Dry Stock
dc.typeThesisen_NZ
thesis.degree.grantorUniversity of Waikato
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (MSc)
dc.date.updated2013-05-16T04:48:10Z
pubs.place-of-publicationHamilton, New Zealanden_NZ


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