< Programme
Tuesday 3 September 2024 – Morning, 8:30
Session 43. Digital phenotyping, sensors, ‘omics’ and genetics in enhanced sustainability
Room: Auditorium – Palazzo Congressi Lower Ground Floor
Chair: Egger-Danner / Lebreton
Session Type: Theme session
Theatre Session
8:30
Genomic selection in the era of digital phenotyping
InvitedD. Lourenco, M. Bermann, M. K. Hollifield, M. Billah, C. Y. Chen, E. Psota, J. Holl, S. Tsuruta, I. Misztal
9:00
Comparison of the potential of cow-side blood tests, MIR spectra and wearable sensor devices for breeding for metabolic health in dairy cows
K. Schodl, B. Fuerst-Waltl, D4Dairy Consortium, C. Egger-Danner
9:15
Can daily rumination time be used to breed for resilient Holstein cows?
W. Lou, B. Ducro, A. Van Der Linden, Y. Wang
9:30
Use of machine learning methods to predict feed efficiency traits in dairy cows using phenotypic and genomic information
A. Seidel, L. Stahmer, G. Thaller
9:45
Comparison of methods to identify resilience indicator phenotypes using across lactation robot milk yield dynamics in the Nordic Red cows
A. Kavlak, E. Negussie, M. Lidauer, M. Pastell
10:00
Genetic correlation between residual feed intake and easily measurable plasma parameters in early-fattening young bulls
S. Taussat, H. Aboshady, P. Martin, G. Cantalapiedra-Hijar
10:45
Genetic parameters for novel climatic resilience indicators derived from automatically-recorded vaginal temperature in lactating sows under heat stress conditions
L. F. Brito, H. Wen
11:00
The relationship between microbial composition and feed efficiency in Iberian pigs
P. Nuñez, C. Casto-Rebollo, S. Negro, J. Casellas, L. Varona, R. Pena, N. Ibáñez-Escriche
11:15
Machine learning approaches for classifying the Iberian pig strains based on microbiome
L. Azouggagh, C. Casto-Rebollo, L. Varona, J. Casellas, S. Negro, M. Martínez-Álvaro, N. Ibáñez-Escriche
11:30
In-abattoir 3D measurements of beef carcasses for the prediction of saleable meat yield and novel carcass traits
H. Nisbet, N. Lambe, G. Miller, A. Doeschl-Wilson, D. Barclay, A. Wheaton, C. A. Duthie
11:45
Pixels to feed: Digital phenotyping potential for genetic analysis of feed intake and efficiency in Atlantic salmon
A. Ahmad, A. Sonesson, B. Hatlen, G. Bæverfjord, P. Berg, A. Norris, G. Difford
12:00
Genotype-by-environment interaction with high-dimensional environmental data: an example in pigs
F. Bussiman, D. Lourenco, C. Y. Chen, J. Holl, I. Misztal, Z. G. Vitezica
Poster Session
43.13
Association analysis of daily rumination time with hindgut microbiota and metabolites in dairy cows
H. Lu, F. Li, Y. Wang
43.14
Sensitive pathogens detection using nanozyme-based catalysis amplification on Ag-PSi SERS scaffold
G. Shtenberg, N. R Nirala
43.15
Usability of raw phenotypic data in selective breeding of dairy cattle on health traits in Slovakia
M. Chalupková, N. Moravčíková, A. Halvoník, J. Candrák, L. Zavadilová, R. Kasarda
43.16
Machine learning and parametric methods for genomic prediction of feed efficiency-related traits
L. F. M. Mota, L. M. Arikawa, S. W. Boer, M. E. Z. Mercadante, J. N. S. G. Cyrillo, H. N. Oliveira, L. G. Albuquerque
43.17
Prediction of blood β-hydroxybutyrate and hyperketonemia based on milk mid-infrared spectra in dairy cows
S. Gruber, A. Köck, C. Egger-Danner, M. Iwersen, B. Fuerst-Waltl, J. Sölkner
43.18
Dissecting production traits using metabolomics in pigs
S. Bovo, G. Schiavo, F. Bertolini, M. Bolner, M. Cappelloni, M. Gallo, P. Zambonelli, S. Dall’Olio, L. Fontanesi
43.19
Longitudinal feed intake deviations at the pen level as a resilience indicator for pigs
W. Gorssen, C. Winters, R. Meyermans, L. Chapard, K. Hooyberghs, J. Depuydt, S. Janssens, N. Buys
43.20
Genetic analysis of milk FTIR spectra in Italian Simmental Cattle
R. Negrini, G. Gaspa, L. Degano, D. Vicario, A. Cesarani, N. P. P. Macciotta
43.21
Prediction of nutritional content of black soldier fly (BSF) larvae using multispectral imaging
G. Gebreyesus, K. Jensen, A. Luca
43.22
Comprehensive analysis of whole-transcriptome and metabolome provides insights into estrus expression in Holstein cattle
T. Yang, Y. Chang, Y. Wang
43.23
Unraveling metabolic stress response in dairy cows: genetic control of plasma biomarkers throughout lactation and the transition period
M. M. Passamonti, M. Milanesi, L. Cattaneo, J. Ramirez Diaz, A. Stella, M. Barbato, C. Urbano Braz, R. Negrini, D. Giannuzzi, S. Pegolo, A. Cecchinato, E. Trevisi, J. L. Williams, P. Ajmone Marsan
43.24
Phenotyping tools and data collection for the agroecological transition
G. Pairault, C. Allain, R. Baumont, Y. Billon, S. Brard-Fudulea, M. Brochard, B. Dumon-Saint-Priest, N. Gaudillière, L. Griffon, L. Journaux, J. Magadray, T. Morin, M. Tabouret, M. Sourdioux, A. Travel, J. P. Bidanel
43.25
Blood metabolic biomarkers predicted from milk spectra are heritable in Holstein transition cows
S. Magro, A. Costa, R. Finocchiaro, M. Marusi, M. Cassandro, M. De Marchi
43.26
Evaluating the Efficiency of Phenomic Selection in Dairy Cattle
E. O. Odah, M. P. Sanchez, B. Cuyabano, P. Croiseau
43.27
Genomic evaluation of SA Holsteins incorporating local and foreign genetic markers under two production systems
M. Van Niekerk, E. D. Cason, F. W. C. Neser, J. B. Van Wyk, V. Ducrocq
43.28
Evaluation of muscle transcriptome of beef cattle after intramuscular application of vitamin A
W. Baldassini, C. Costa, M. Tagiariolli, L. Camargo, R. Curi, G. Pereira, G. Ramírez-Zamudio, O. Machado Neto, M. Ladeira, L. A. Chardulo
