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Accuracy to Predict the Onset of Calving in Dairy Farms by Using Different Precision Livestock Farming Devices

SIMPLE SUMMARY: If the onset of calving can be accurately detected as well as appropriate calving assistance can be performed on a dairy farm, at that time, the prevalence of dystocia, stillbirth, vaginal laceration, retained fetal membranes, and consequent clinical metritis/endometritis can be decr...

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Autor principal: Szenci, Ottó
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9367308/
https://www.ncbi.nlm.nih.gov/pubmed/35953995
http://dx.doi.org/10.3390/ani12152006
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author Szenci, Ottó
author_facet Szenci, Ottó
author_sort Szenci, Ottó
collection PubMed
description SIMPLE SUMMARY: If the onset of calving can be accurately detected as well as appropriate calving assistance can be performed on a dairy farm, at that time, the prevalence of dystocia, stillbirth, vaginal laceration, retained fetal membranes, and consequent clinical metritis/endometritis can be decreased significantly. Therefore, in order to reduce these losses, our primary task must be to predict the onset of calving accurately and provide timely and professional calving assistance. This review focuses on the diagnostic possibilities and limitations of detecting the onset calving in the field. ABSTRACT: Besides traditional methods such as evaluation of the external preparatory and behavioral signs, which even presently are widely used also in large dairy farms, there are several new possibilities such as measuring body (intravaginal, ventral tail-base surface, ear surface, or reticulo-ruminal) temperature, detecting behavioral signs (rumination, eating, activity, tail raising) or detecting the expulsion of the device inserted into the vagina or fixed to the skin of the vulva when allantochorion appears in the vulva to predict the onset of the second stage of calving. Presently none of the single sensors or a combination of sensors can predict the onset of calving with acceptable accuracy. At the same time, with the exception of the iVET(®) birth monitoring system, not only the imminent onset of calving could be predicted with high accuracy, but a significantly lower prevalence rate of dystocia, stillbirth, retained fetal membranes, uterine diseases/clinical metritis could be reached while calving-to-conception interval was significantly shorter compared with the control groups. These results may confirm the use of these devices in dairy farms by allowing appropriate intervention during calving when needed. In this way, we can reduce the negative effect of dystocia on calves and their dams and improve their welfare.
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spelling pubmed-93673082022-08-12 Accuracy to Predict the Onset of Calving in Dairy Farms by Using Different Precision Livestock Farming Devices Szenci, Ottó Animals (Basel) Review SIMPLE SUMMARY: If the onset of calving can be accurately detected as well as appropriate calving assistance can be performed on a dairy farm, at that time, the prevalence of dystocia, stillbirth, vaginal laceration, retained fetal membranes, and consequent clinical metritis/endometritis can be decreased significantly. Therefore, in order to reduce these losses, our primary task must be to predict the onset of calving accurately and provide timely and professional calving assistance. This review focuses on the diagnostic possibilities and limitations of detecting the onset calving in the field. ABSTRACT: Besides traditional methods such as evaluation of the external preparatory and behavioral signs, which even presently are widely used also in large dairy farms, there are several new possibilities such as measuring body (intravaginal, ventral tail-base surface, ear surface, or reticulo-ruminal) temperature, detecting behavioral signs (rumination, eating, activity, tail raising) or detecting the expulsion of the device inserted into the vagina or fixed to the skin of the vulva when allantochorion appears in the vulva to predict the onset of the second stage of calving. Presently none of the single sensors or a combination of sensors can predict the onset of calving with acceptable accuracy. At the same time, with the exception of the iVET(®) birth monitoring system, not only the imminent onset of calving could be predicted with high accuracy, but a significantly lower prevalence rate of dystocia, stillbirth, retained fetal membranes, uterine diseases/clinical metritis could be reached while calving-to-conception interval was significantly shorter compared with the control groups. These results may confirm the use of these devices in dairy farms by allowing appropriate intervention during calving when needed. In this way, we can reduce the negative effect of dystocia on calves and their dams and improve their welfare. MDPI 2022-08-08 /pmc/articles/PMC9367308/ /pubmed/35953995 http://dx.doi.org/10.3390/ani12152006 Text en © 2022 by the author. 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
Szenci, Ottó
Accuracy to Predict the Onset of Calving in Dairy Farms by Using Different Precision Livestock Farming Devices
title Accuracy to Predict the Onset of Calving in Dairy Farms by Using Different Precision Livestock Farming Devices
title_full Accuracy to Predict the Onset of Calving in Dairy Farms by Using Different Precision Livestock Farming Devices
title_fullStr Accuracy to Predict the Onset of Calving in Dairy Farms by Using Different Precision Livestock Farming Devices
title_full_unstemmed Accuracy to Predict the Onset of Calving in Dairy Farms by Using Different Precision Livestock Farming Devices
title_short Accuracy to Predict the Onset of Calving in Dairy Farms by Using Different Precision Livestock Farming Devices
title_sort accuracy to predict the onset of calving in dairy farms by using different precision livestock farming devices
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9367308/
https://www.ncbi.nlm.nih.gov/pubmed/35953995
http://dx.doi.org/10.3390/ani12152006
work_keys_str_mv AT szenciotto accuracytopredicttheonsetofcalvingindairyfarmsbyusingdifferentprecisionlivestockfarmingdevices