Research Project: Multi-Dimension Phenotyping to Enhance Prediction of Performance in Swine

Location: Genetics and Animal Breeding

Publications (Clicking on the reprint icon will take you to the publication reprint.)

Novel precision tools to address labor challenges and improve daily management in swine production - (Abstract Only)

Deep learning algorithms to identify individual finishing pigs using 3D data - (Peer Reviewed Journal)
Paudel, S., Brown-Brandl, T.M., Rohrer, G., Sharma, S.R. 2025. Deep learning algorithms to identify individual finishing pigs using 3D data. Biosystems Engineering. 255. Article 104143. https://doi.org/10.1016/j.biosystemseng.2025.104143.

Multiscale vibration sensing for activity and vital signs monitoring in pig pens - (Proceedings)
Codling, J.R., Shulkin, J.D., Vibhatasilpin, A., Adhana, V., Rohrer, G.A., Miles, J.R., Sharma, S., Brown-Brandl, T.M., Noh, H., Zhang, P. 2025. Multiscale vibration sensing for activity and vital signs monitoring in pig pens. In: Proceedings of Association for Computing Machinery. 23rd Association for Computing Machinery Networked Sensor Systems, May 6-9, 2025, Irvine, California. p. 650-651. https://doi.org/10.1145/3715014.3724052.

Genomic analysis of mobility measures on 5-month-old gilts associated with structural soundness - (Peer Reviewed Journal)
Ostrand, L.M., Rempel, L.A., Keel, B.N., Snelling, W.M., Schmidt, T.B., Psota, E.T., Mote, B.E., Rohrer, G.A. 2025. Genomic analysis of mobility measures on 5-month-old gilts associated with structural soundness. Journal of Animal Science. 103. Article skaf001. https://doi.org/10.1093/jas/skaf001.

Insights into microbial compositions of the respiratory tract of neonatal dairy calves in a longitudinal probiotic trial through 16S rRNA sequencing - (Peer Reviewed Journal)
Tan, J.W., Eicher, S.D., Kritchevsky, J.E., Bryan, K.A., Dickey, A.M., Chitko-McKown, C.G., McDaneld, T.G. 2025. Insights into microbial compositions of the respiratory tract of neonatal dairy calves in a longitudinal probiotic trial through 16S rRNA sequencing. Frontiers in Microbiology. 15. Article 1499531. https://doi.org/10.3389/fmicb.2024.1499531.

The incidence of volatile anesthesia porcine stress syndrome in pigs (Sus scrofa domesticus) gives implications for physiology during anesthesia - (Peer Reviewed Journal)
Corrigan, J., Mares, J.A., Hutzler, J.D., Nonneman, D.J., Burmeister, D.M. 2025. The incidence of volatile anesthesia porcine stress syndrome in pigs (Sus scrofa domesticus) gives implications for physiology during anesthesia. Journal of the American Association for Laboratory Animal Science. 64(1):179-188. https://doi.org/10.30802/aalas-jaalas-24-077.

Robust piglet nursing behavior monitoring through multi-modal fusion of computer vision and ambient floor vibration - (Peer Reviewed Journal)
Dong, Y., Song, Z., Codling, J.R., Rohrer, G.A., Miles, J.R., Sharma, S., Brown-Brandl, T.M., Zhang, P., Noh, H. 2025. Robust piglet nursing behavior monitoring through multi-modal fusion of computer vision and ambient floor vibration. Computers and Electronics in Agriculture. 238. Article 110804. https://doi.org/10.1016/j.compag.2025.110804.

Impact of crate design, number of heat lamps, and lying posture on the occurrence of shoulder lesions in sows - (Peer Reviewed Journal)
Bery, S., Brown-Brandl, T.M., Rohrer, G.A., Sharma, S., Leonard, S.M. 2024. Impact of crate design, number of heat lamps, and lying posture on the occurrence of shoulder lesions in sows. Biosystems Engineering. 247:249-256. https://doi.org/10.1016/j.biosystemseng.2024.09.017.

Deep learning-based sow posture classifier using colour and depth images - (Peer Reviewed Journal)
Pacheco, V.M., Brown-Brandl, T.M., Vieira de Sousa, R., Rohrer, G.A., Sharma, S.R., Martello, L.S. 2024. Deep learning-based sow posture classifier using colour and depth images. Smart Agricultural Technology. 9. Article 100563. https://doi.org/10.1016/j.atech.2024.100563.

Classification of sow postures using convolutional neural network and depth images - (Proceedings)
Rahman, Md T., Brown-Brandl, T.M., Rohrer, G.A., Sharma, S.R., Shi, Y. 2024. Classification of sow postures using convolutional neural network and depth images. In: Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE), July 28-31, 2024, Anaheim, CA. Paper 2401533. https://doi.org/10.13031/aim.202401533.

Genomic regions associated with electronic measures indicative of structural soundness in pigs - (Abstract Only)
Rohrer, G.A., Ostrand, L., Rempel, L.A., Keel-Mercer, B.N., Schmidt, T.B., Mote, B.E. 2024. Genomic regions associated with electronic measures indicative of structural soundness in pigs [abstract]. American Society of Animal Science Annual Meeting. 102(3):24-25. https://doi.org/10.1093/jas/skae234.027.

Online feeding behavior monitoring of individual group-housed grow-finish pigs using a low-frequency RFID electronic feeding system - (Peer Reviewed Journal)
Funk, T.H., Rohrer, G.A., Brown-Brandl, T.M., Keel, B.N. 2024. Online feeding behavior monitoring of individual group-housed grow-finish pigs using a low-frequency RFID electronic feeding system. Translational Animal Science. 8. Article txae051. https://doi.org/10.1093/tas/txae051.

Impacts of farrowing pen design, season, and sow parity on litter performance and piglet mortality - (Peer Reviewed Journal)
Pacheco, V.M., Brown-Brandl, T., Rohrer, G.A., Vieira De Sousa, R., Silva Martello, L. 2024. Impacts of farrowing pen design, season, and sow parity on litter performance and piglet mortality. Animals. 14(2). Article 325. https://doi.org/10.3390/ani14020325.

Determining the presence and size of shoulder lesions in sows using computer vision - (Peer Reviewed Journal)
Bery, S., Brown-Brandl, T.M., Jones, B.T., Rohrer, G.A., Sharma, S.R. 2023. Determining the presence and size of shoulder lesions in sows using computer vision. Animals. 14(1). Article 131. https://doi.org/10.3390/ani14010131.

Statistical and machine learning approaches to describe factors affecting preweaning mortality of piglets - (Peer Reviewed Journal)
Rahman, M., Brown-Brandl, T.M., Rohrer, G.A., Sharma, S., Manthena, V., Shi, Y. 2023. Statistical and machine learning approaches to describe factors affecting preweaning mortality of piglets. Translational Animal Science. 7(1). Article txad117. https://doi.org/10.1093/tas/txad117.

Estimation of cell type proportions from bulk RNA-Seq of porcine whole blood samples using partial reference-free deconvolution - (Peer Reviewed Journal)
Keel, B.N., Lindholm-Perry, A.K., Rohrer, G.A., Oliver, W.T. 2023. Estimation of cell type proportions from bulk RNA-Seq of porcine whole blood samples using partial reference-free deconvolution. Animal Gene. 30. Article 200159. https://doi.org/10.1016/j.angen.2023.200159.

Identifying early-life behavior to predict mothering ability in swine utilizing NUtrack system - (Peer Reviewed Journal)
Millburn, S., Schmidt, T., Rohrer, G.A., Mote, B. 2023. Identifying early-life behavior to predict mothering ability in swine utilizing NUtrack system. Animals. 13(18). Article 2897. https://doi.org/10.3390/ani13182897.

Methods to predict lameness in sows - (Abstract Only)