Beyond the hype: using AI, big data, wearable devices, and the internet of things for high-throughput livestock phenotyping

Publication typeJournal Article
Publication date2024-08-19
scimago Q2
wos Q2
SJR0.860
CiteScore5.6
Impact factor2.5
ISSN20412649, 20412657
PubMed ID:  39158344
Abstract

Phenotyping of animals is a routine task in agriculture which can provide large datasets for the functional annotation of genomes. Using the livestock farming sector to study complex traits enables genetics researchers to fully benefit from the digital transformation of society as economies of scale substantially reduces the cost of phenotyping animals on farms. In the agricultural sector genomics has transitioned towards a model of ‘Genomics without the genes’ as a large proportion of the genetic variation in animals can be modelled using the infinitesimal model for genomic breeding valuations. Combined with third generation sequencing creating pan-genomes for livestock the digital infrastructure for trait collection and precision farming provides a unique opportunity for high-throughput phenotyping and the study of complex traits in a controlled environment. The emphasis on cost efficient data collection mean that mobile phones and computers have become ubiquitous for cost-efficient large-scale data collection but that the majority of the recorded traits can still be recorded manually with limited training or tools. This is especially valuable in low- and middle income countries and in settings where indigenous breeds are kept at farms preserving more traditional farming methods. Digitalization is therefore an important enabler for high-throughput phenotyping for smaller livestock herds with limited technology investments as well as large-scale commercial operations. It is demanding and challenging for individual researchers to keep up with the opportunities created by the rapid advances in digitalization for livestock farming and how it can be used by researchers with or without a specialization in livestock. This review provides an overview of the current status of key enabling technologies for precision livestock farming applicable for the functional annotation of genomes.

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Klingström T. et al. Beyond the hype: using AI, big data, wearable devices, and the internet of things for high-throughput livestock phenotyping // Briefings in Functional Genomics. 2024.
GOST all authors (up to 50) Copy
Klingström T., Zonabend König E., Zwane A. A. Beyond the hype: using AI, big data, wearable devices, and the internet of things for high-throughput livestock phenotyping // Briefings in Functional Genomics. 2024.
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TY - JOUR
DO - 10.1093/bfgp/elae032
UR - https://academic.oup.com/bfg/advance-article/doi/10.1093/bfgp/elae032/7735403
TI - Beyond the hype: using AI, big data, wearable devices, and the internet of things for high-throughput livestock phenotyping
T2 - Briefings in Functional Genomics
AU - Klingström, Tomas
AU - Zonabend König, Emelie
AU - Zwane, Avhashoni Agnes
PY - 2024
DA - 2024/08/19
PB - Oxford University Press
PMID - 39158344
SN - 2041-2649
SN - 2041-2657
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2024_Klingström,
author = {Tomas Klingström and Emelie Zonabend König and Avhashoni Agnes Zwane},
title = {Beyond the hype: using AI, big data, wearable devices, and the internet of things for high-throughput livestock phenotyping},
journal = {Briefings in Functional Genomics},
year = {2024},
publisher = {Oxford University Press},
month = {aug},
url = {https://academic.oup.com/bfg/advance-article/doi/10.1093/bfgp/elae032/7735403},
doi = {10.1093/bfgp/elae032}
}