Cargando…

Digital Phenotyping in Livestock Farming

SIMPLE SUMMARY: Wearable technology has launched human medicine toward new successes, but are these versatile devices really being leveraged to their best capacity? Applying wearable sensors to animal farming contexts represents tremendous potential for cost-conscious growers and welfare-minded cons...

Descripción completa

Detalles Bibliográficos
Autores principales: Neethirajan, Suresh, Kemp, Bas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8300347/
https://www.ncbi.nlm.nih.gov/pubmed/34359137
http://dx.doi.org/10.3390/ani11072009
_version_ 1783726452195196928
author Neethirajan, Suresh
Kemp, Bas
author_facet Neethirajan, Suresh
Kemp, Bas
author_sort Neethirajan, Suresh
collection PubMed
description SIMPLE SUMMARY: Wearable technology has launched human medicine toward new successes, but are these versatile devices really being leveraged to their best capacity? Applying wearable sensors to animal farming contexts represents tremendous potential for cost-conscious growers and welfare-minded consumers alike. Each farm animal’s phenotype—the set, observable variables that an organism displays based on interactions with their environment—offers unique information on health, welfare, and profitability. Previously, these important observations had to be conducted with extensive time, cost, and labor resources—and even then, the results were impossible to standardize or obtain continuously. Thanks to their proven benefits across many human-based studies, digital phenotype readers can collect and relay specific metrics, such as body temperature, cardiovascular functioning, activity level, and even more complex behaviors such as sociability. Due to cross-species variations, these sensors need to be tailored efficiently and accurately. Future research should inform the design of digital phenotyping options that will offer farmers reliable, robust information, with the long-term goal of creating shared data standards and stores. ABSTRACT: Currently, large volumes of data are being collected on farms using multimodal sensor technologies. These sensors measure the activity, housing conditions, feed intake, and health of farm animals. With traditional methods, the data from farm animals and their environment can be collected intermittently. However, with the advancement of wearable and non-invasive sensing tools, these measurements can be made in real-time for continuous quantitation relating to clinical biomarkers, resilience indicators, and behavioral predictors. The digital phenotyping of humans has drawn enormous attention recently due to its medical significance, but much research is still needed for the digital phenotyping of farm animals. Implications from human studies show great promise for the application of digital phenotyping technology in modern livestock farming, but these technologies must be directly applied to animals to understand their true capacities. Due to species-specific traits, certain technologies required to assess phenotypes need to be tailored efficiently and accurately. Such devices allow for the collection of information that can better inform farmers on aspects of animal welfare and production that need improvement. By explicitly addressing farm animals’ individual physiological and mental (affective states) needs, sensor-based digital phenotyping has the potential to serve as an effective intervention platform. Future research is warranted for the design and development of digital phenotyping technology platforms that create shared data standards, metrics, and repositories.
format Online
Article
Text
id pubmed-8300347
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-83003472021-07-24 Digital Phenotyping in Livestock Farming Neethirajan, Suresh Kemp, Bas Animals (Basel) Review SIMPLE SUMMARY: Wearable technology has launched human medicine toward new successes, but are these versatile devices really being leveraged to their best capacity? Applying wearable sensors to animal farming contexts represents tremendous potential for cost-conscious growers and welfare-minded consumers alike. Each farm animal’s phenotype—the set, observable variables that an organism displays based on interactions with their environment—offers unique information on health, welfare, and profitability. Previously, these important observations had to be conducted with extensive time, cost, and labor resources—and even then, the results were impossible to standardize or obtain continuously. Thanks to their proven benefits across many human-based studies, digital phenotype readers can collect and relay specific metrics, such as body temperature, cardiovascular functioning, activity level, and even more complex behaviors such as sociability. Due to cross-species variations, these sensors need to be tailored efficiently and accurately. Future research should inform the design of digital phenotyping options that will offer farmers reliable, robust information, with the long-term goal of creating shared data standards and stores. ABSTRACT: Currently, large volumes of data are being collected on farms using multimodal sensor technologies. These sensors measure the activity, housing conditions, feed intake, and health of farm animals. With traditional methods, the data from farm animals and their environment can be collected intermittently. However, with the advancement of wearable and non-invasive sensing tools, these measurements can be made in real-time for continuous quantitation relating to clinical biomarkers, resilience indicators, and behavioral predictors. The digital phenotyping of humans has drawn enormous attention recently due to its medical significance, but much research is still needed for the digital phenotyping of farm animals. Implications from human studies show great promise for the application of digital phenotyping technology in modern livestock farming, but these technologies must be directly applied to animals to understand their true capacities. Due to species-specific traits, certain technologies required to assess phenotypes need to be tailored efficiently and accurately. Such devices allow for the collection of information that can better inform farmers on aspects of animal welfare and production that need improvement. By explicitly addressing farm animals’ individual physiological and mental (affective states) needs, sensor-based digital phenotyping has the potential to serve as an effective intervention platform. Future research is warranted for the design and development of digital phenotyping technology platforms that create shared data standards, metrics, and repositories. MDPI 2021-07-05 /pmc/articles/PMC8300347/ /pubmed/34359137 http://dx.doi.org/10.3390/ani11072009 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Neethirajan, Suresh
Kemp, Bas
Digital Phenotyping in Livestock Farming
title Digital Phenotyping in Livestock Farming
title_full Digital Phenotyping in Livestock Farming
title_fullStr Digital Phenotyping in Livestock Farming
title_full_unstemmed Digital Phenotyping in Livestock Farming
title_short Digital Phenotyping in Livestock Farming
title_sort digital phenotyping in livestock farming
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8300347/
https://www.ncbi.nlm.nih.gov/pubmed/34359137
http://dx.doi.org/10.3390/ani11072009
work_keys_str_mv AT neethirajansuresh digitalphenotypinginlivestockfarming
AT kempbas digitalphenotypinginlivestockfarming