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dc.contributor.authorBrooks (Turner), Rachel J.
dc.contributor.authorTolleson, Douglas R.
dc.contributor.authorRuyle, George B.
dc.contributor.authorFaulkner, Dan B.
dc.date.accessioned2021-09-22T22:48:21Z
dc.date.available2021-09-22T22:48:21Z
dc.date.issued2021
dc.identifier.citationBrooks, R. J., Tolleson, D. R., Ruyle, G. B., & Faulkner, D. B. (2021). A production-scale evaluation of nutritional monitoring and decision support software for free-ranging cattle in an arid environment. Rangeland Journal.en_US
dc.identifier.issn1036-9872
dc.identifier.doi10.1071/rj20116
dc.identifier.urihttp://hdl.handle.net/10150/661855
dc.description.abstractRange cattle in semi-arid regions are commonly limited by lack of nitrogen and other nutrients from grazing low-quality forage, with managers needing to monitor diet quality to address nutrient limitations. Near-infrared spectroscopy of faecal samples (FNIRS) is an accurate method used to determine diet quality in grazing animals. When combined with a nutritional balance software such as the Nutritional Balance Analyser (NUTBAL), FNIRS can monitor nutritional status and estimate weight change. We aimed to test the ability of NUTBAL to predict animal performance as represented by body condition score (BCS) in cattle grazing on a semi-desert rangeland. BCS and faecal samples were collected from a Red Angus herd (n = 82) at the Santa Rita Ranch (June 2016-July 2017). Standing biomass and botanical composition were measured before each grazing period, and relative utilisation was measured following each grazing period. During the midpoint of grazing in each pasture, 30 BCS and a faecal composite of 15 samples were collected. Faecal derived diet quality varied between a maximum of 10.75% crude protein (CP) and 61.25% digestible organic matter (DOM) in early August 2016, to a minimum value of 4.22% CP and 57.68% DOM in January 2017. Three NUTBAL evaluations were conducted to determine the likelihood of accurately predicting animal performance: one with typical user defined inputs; one with improved environment and herd descriptive inputs; and one with these improvements plus the use of metabolisable protein in the model. This third evaluation confirmed the ability of FNIRS:NUTBAL to predict future BCS within 0.5 BCS more than 75% of the time. With this information, cattle managers in semi-arid regions can better address animal performance needs and nutrient deficiencies.en_US
dc.language.isoenen_US
dc.publisherCSIRO Publishingen_US
dc.rights© 2021 Australian Rangeland Society.en_US
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en_US
dc.subjectarid environmenten_US
dc.subjectcattleen_US
dc.subjectdiet managementen_US
dc.subjectgrazingen_US
dc.subjectnutritional monitoringen_US
dc.subjectprediction softwareen_US
dc.titleA production-scale evaluation of nutritional monitoring and decision support software for free-ranging cattle in an arid environmenten_US
dc.typeArticleen_US
dc.contributor.departmentUniversity of Arizona, School of Natural Resources and the Environmenten_US
dc.contributor.departmentUniversity of Arizona Agriculture Research Stationen_US
dc.identifier.journalRangeland Journalen_US
dc.description.noteImmediate accessen_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal accepted manuscripten_US
dc.identifier.piiRJ20116
dc.source.journaltitleThe Rangeland Journal
dc.source.volume43
dc.source.issue1
dc.source.beginpage35
refterms.dateFOA2021-09-22T22:48:22Z


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