Die chronologische Liste zeigt aktuelle Veröffentlichungen aus dem Forschungsbetrieb der Hochschule Weihenstephan-Triesdorf. Zuständig ist das Zentrum für Forschung und Wissenstransfer (ZFW).
Faktencheck Eutergesundheit (2014) 1. Tiergesundheitstag zum Thema "Eutergesundheit interaktiv" im Alten Reithaus in Triesdorf am 04. April 2014 .
Prof. Dr. Prisca Kremer-Rücker
In vivo Phänotypisierung von Schlachtkörpermerkmalen bei Schwein und Schaf mittels Magnetresonanztomographie (2013) Habilitationsschrift, Ludwig-Maximilians-Universität München, 319 S .
Maren Bernau,
Prof. Dr. Prisca Kremer-Rücker,
Prof. Dr. Armin Manfred Scholz
Berechtigungen: Peer Reviewed
Vergleich der Körperzusammensetzung von Schweinen bei 80 kg und 100 kg Lebendmasse mittels Magnetresonanztomographie (2013) Züchtungskunde 85 (6), S. 430-439.
Maren Bernau,
Prof. Dr. Prisca Kremer-Rücker,
Elke Pappenberger,
Lena Sophie Kreuzer,
Klaus Cussler,
Prof. Dr. Armin Manfred Scholz
Safety testing of veterinary vaccines in pigs using magnetic resonance imaging (2013) Posterbeitrag [P197] zum 7th ISV Annual Congress, 27.-29.Oktober 2013 in Barcelona (Spanien) .
Maren Bernau,
Prof. Dr. Prisca Kremer-Rücker,
Elke Pappenberger,
Klaus Cussler,
Andreas Hoffmann,
Prof. Dr. Armin Manfred Scholz
Magnetic resonance imaging as an alternative method in safety-testing of veterinary vaccines – preliminary results in pigs (2013) LINZ 2013 – EUSAAT 2013 – ESNATS Conference, ALTEX Proceedings 2 (2), S. 7.
Maren Bernau,
Prof. Dr. Prisca Kremer-Rücker,
Ernst Tholen,
Steffen Müller,
Elke Pappenberger,
P. Grün,
Elisabeth Lauterbach,
Prof. Dr. Armin Manfred Scholz
New lean meat formulas for progeny testing of intact boars - developed by using MRI and DXA (2013) Book of Abstracts 19 of the 64th Annual Meeting of the European Federation of Animal Science (EAAP), 26 -30 August 2013 in Nantes (France) , S. 102.
Prof. Dr. Armin Manfred Scholz,
Prof. Dr. Prisca Kremer-Rücker,
Rita Wenczel,
Elke Pappenberger,
Maren Bernau
Body composition in farm animals by dual energy X-ray absorptiometry (2013) FARM ANIMAL IMAGING DUBLIN 2012, Quality Meat Scotland, Hrsg.: C. Maltin, C. Craigie, and L. Bünger , S. 9-15.
Prof. Dr. Prisca Kremer-Rücker,
Martin Förster,
Prof. Dr. Armin Manfred Scholz
Berechtigungen: Open Access
Berechtigungen: Peer Reviewed
Use of magnetic resonance imaging to predict the body composition of pigs in vivo (2013) Animal 7 (6), S. 879-884.
DOI: 10.1017/s1751731112002340
The objective of the study was to evaluate whether magnetic resonance imaging (MRI) offers the opportunity to reliably analyze body composition of pigs in vivo. Therefore, the relation between areas of loin eye muscle and its back fat based on MRI images were used to predict body composition values measured by dual energy X-ray absorptiometry (DXA). During the study, a total of 77 pigs were studied by MRI and DXA, with a BW ranging between 42 and 102 kg. The pigs originated from different extensive or conventional breeds or crossbreds such as Cerdo Iberico, Duroc, German Landrace, German Large White, Hampshire and Pietrain. A Siemens Magnetom Open was used for MRI in the thorax region between 13th and 14th vertebrae in order to measure the loin eye area (MRI-LA) and the above back fat area (MRI-FA) of both body sides, whereas a whole body scan was performed by DXA with a GE Lunar DPX-IQ in order to measure the amount and percentage of fat tissue (DXA-FM; DXA-%FM) and lean tissue mass (DXA-LM; DXA-%LM). A linear single regression analysis was performed to quantify the linear relationships between MRI- and DXA-derived traits. In addition, a stepwise regression procedure was carried out to calculate (multiple) regression equations between MRI and DXA variables (including BW). Single regression analyses showed high relationships between DXA-%FM and MRI-FA (R2 = 0.89, √MSE = 2.39%), DXA-FM and MRI-FA (R2 = 0.82, √MSE = 2757 g) and DXA-LM and MRI-LA (R2 = 0.82, √MSE = 4018 g). Only DXA-%LM and MRI-LA did not show any relationship (R2 = 0). As a result of the multiple regression analysis, DXA-LM and DXA-FM were both highly related to MRI-LA, MRI-FA and BW (R2 = 0.96; √MSE = 1784 g, and R2 = 0.95, √MSE = 1496 g). Therefore, it can be concluded that the use of MRI-derived images provides exact information about important ‘carcass-traits’ in pigs and may be used to reliably predict the body composition in vivo.
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Gerhard Radlmayr
Referent für Wissenstransfer und Forschungskommunikation
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