{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T03:50:06Z","timestamp":1762660206777,"version":"build-2065373602"},"reference-count":51,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T00:00:00Z","timestamp":1651017600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Rapiscan Systems and Meat and Livestock Australia Donor Company","award":["P.PSH.0886","V.DSP.2018","DP210100521"],"award-info":[{"award-number":["P.PSH.0886","V.DSP.2018","DP210100521"]}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["P.PSH.0886","V.DSP.2018","DP210100521"],"award-info":[{"award-number":["P.PSH.0886","V.DSP.2018","DP210100521"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Automatic identification and sorting of livestock organs in the meat processing industry could reduce costs and improve efficiency. Two hyperspectral sensors encompassing the visible (400\u2013900 nm) and short-wave infrared (900\u20131700 nm) spectra were used to identify the organs by type. A total of 104 parenchymatous organs of cattle and sheep (heart, kidney, liver, and lung) were scanned in a multi-sensory system that encompassed both sensors along a conveyor belt. Spectral data were obtained and averaged following manual markup of three to eight regions of interest of each organ. Two methods were evaluated to classify organs: partial least squares discriminant analysis (PLS-DA) and random forest (RF). In addition, classification models were obtained with the smoothed reflectance and absorbance and the first and second derivatives of the spectra to assess if one was superior to the rest. The in-sample accuracy for the visible, short-wave infrared, and combination of both sensors was higher for PLS-DA compared to RF. The accuracy of the classification models was not significantly different between data pre-processing methods or between visible and short-wave infrared sensors. Hyperspectral sensors, particularly those in the visible spectrum, seem promising to identify organs from slaughtered animals which could be useful for the automation of quality and process control in the food supply chain, such as in abattoirs.<\/jats:p>","DOI":"10.3390\/s22093347","type":"journal-article","created":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T22:20:20Z","timestamp":1651098020000},"page":"3347","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Differentiation of Livestock Internal Organs Using Visible and Short-Wave Infrared Hyperspectral Imaging Sensors"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4151-6890","authenticated-orcid":false,"given":"Cassius E. O.","family":"Coombs","sequence":"first","affiliation":[{"name":"Sydney Institute of Agriculture, School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Sydney, NSW 2006, Australia"}]},{"given":"Brendan E.","family":"Allman","sequence":"additional","affiliation":[{"name":"Rapiscan Systems Pty Ltd., 6-8 Herbert Street, Unit 27, Sydney, NSW 2006, Australia"}]},{"given":"Edward J.","family":"Morton","sequence":"additional","affiliation":[{"name":"Rapiscan Systems Pte Ltd., Singapore 348574, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7368-6646","authenticated-orcid":false,"given":"Marina","family":"Gimeno","sequence":"additional","affiliation":[{"name":"University Veterinary Teaching Hospital Camden, Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Sydney, NSW 2006, Australia"}]},{"given":"Neil","family":"Horadagoda","sequence":"additional","affiliation":[{"name":"University Veterinary Teaching Hospital Camden, Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Sydney, NSW 2006, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6605-7478","authenticated-orcid":false,"given":"Garth","family":"Tarr","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Faculty of Science, The University of Sydney, Sydney, NSW 2006, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6400-2588","authenticated-orcid":false,"given":"Luciano A.","family":"Gonz\u00e1lez","sequence":"additional","affiliation":[{"name":"Sydney Institute of Agriculture, School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Sydney, NSW 2006, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.prevetmed.2019.03.014","article-title":"Evaluation of the diagnostic sensitivity and specificity of meat inspection for hepatic hydatid disease in beef cattle in an Australian abattoir","volume":"167","author":"Wilson","year":"2019","journal-title":"Prev. 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