Discrimination of wheat crown rot utilising wavelet based models in the NIR spectrum

Humpal, Jacob (2020) Discrimination of wheat crown rot utilising wavelet based models in the NIR spectrum. [Thesis (PhD/Research)]

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Item Type: Thesis (PhD/Research)
Item Status: Live Archive
Additional Information: Doctor of Philosophy (PhD) thesis.
Faculty/School / Institute/Centre: Current - Institute for Advanced Engineering and Space Sciences - Centre for Agricultural Engineering (1 Aug 2018 -)
Faculty/School / Institute/Centre: Current - Institute for Advanced Engineering and Space Sciences - Centre for Agricultural Engineering (1 Aug 2018 -)
Supervisors: McCarthy, Cheryl; Percy, Cassandra; Thomasson, Alex
Date Deposited: 21 Dec 2020 03:20
Last Modified: 21 Apr 2021 00:15
Uncontrolled Keywords: crown rot, machine-learning,PCA, wavelet, crop disease, deep-learning
Fields of Research (2008): 09 Engineering > 0999 Other Engineering > 099901 Agricultural Engineering
Fields of Research (2020): 40 ENGINEERING > 4099 Other engineering > 409901 Agricultural engineering
Identification Number or DOI: doi:10.26192/gkp6-xx10
URI: http://eprints.usq.edu.au/id/eprint/40402

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