PSIII-25 Dairy Data: Challenges and Opportunities. (7th December 2018)

• Record Type: Journal Article
• Authors: Schenkels, J; Hamed, T; Laundry, N; Szkotnicki, B; Baes, C
• Is Part Of: Journal of animal science. Volume 96(2018)Supplement 3
• Page Start: 103
• Page End: 104
• Publication Date: 2018-12-07
• Subjects: Precision farming -- dairy -- data -- genomics; Livestock -- Periodicals; Livestock; Electronic journals; Periodicals; 636.005
• DOI: 10.1093/jas/sky404.229
• Languages: English
• ISSNs: 0021-8812

Abstract

Abstract: Data on dairy animals are being generated under a wide variety of conditions (laboratory, research facilities, on farm). Each year, hundreds of research trials are carried out on the genetics, metabolism, nutrition, physiology and behavior of dairy animals. Furthermore, companies and manufacturers are producing various devices and sensors capable of automatically collecting data on farms. The capture, integration, and use of the information generated represents both a great challenge but also a tremendous opportunity to allow the sector to progress more effectively. Datasets collected in the field of dairy science are growing rapidly, and are expected to increase exponentially in size in the near future. Numerous phenotypes (immune responses, behavioral observations, nutritional information, bodily fluids such as milk, blood, rumen fluid, etc.) are being recorded. Various cost-effective information-sensing mobile devices are being implemented or will be implemented in the near future, including remote sensing, software logs, cameras, microphones, radio-frequency identification (RFID) readers and wireless sensor networks. Finally, genomic information (SNP-chip genotypes, next-generation sequence data, metagenomic and epigenetic information) are also being collected on a number of animals. The volume and the diversity in the accuracy, format, scope, structure and pattern of this data are creating important challenges. Information is compiled and kept in idiosyncratic formats by different research groups or individual farmers. Finding and valorizing existing information is complicated. This leads to overlooking potentially valuable information. Here we present the development of a standardized and curated database, which enables higher-level, more comprehensive theoretical and experimental analyses. Our work is currently focused on dairy cattle, but will be expanded to include other livestock species in the near future.