At-market sensor technologies to develop proxies for resilience and efficiency in dairy cows

W. Ouweltjes, Y. De Haas, C. Kamphuis*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

Abstract

We hypothesise that at-market sensor technologies can be used to develop proxies for complex traits such as resilience and feed efficiency (FE). This was tested by comparing variables describing sensor data patterns (“curve-parameters”) from resilient or FE cows with non-resilient or non-FE cows. Sensor data included data from weighing scales, activity (steps) and rumination activity from neck collars, and milk production from the parlour or the milking robot. Curve-parameters were calculated for each sensor for each lactation for which data was available and included the mean, standard deviation (std), slope, skewness, and the autocorrelation. Data originated from a Wageningen Research farm, and included data from 1,800 cows with calvings between 1995-2016. During this time frame, there were 98 lactations with sufficient feed intake recordings to compute FE at lactation level (DMI (kg) / milk yield (kg)), and to rank them accordingly. The 1,800 cows that could be ranked according to their lifetime resilience (ability to re-calf in combination with the number of health and insemination events) based on scores for each of the, in total, 5,771 lactations. Subsequently, the 20% or 10% most and least FE or resilient lactations, respectively, were selected. Curve-parameters of these selected lactations were compared. Results imply that using a single sensor, or a single curve parameter, is likely to be insufficient as a proxy for resilience of efficiency. Future research should focus on studying which combination of curve parameters and sensors are most informative as proxy for these two complex traits.

Original languageEnglish
Title of host publicationPrecision Livestock Farming 2019
Subtitle of host publicationPapers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019
EditorsBernadette O'Brien, Deirdre Hennessy, Laurence Shalloo
PublisherTeagasc
Pages246-253
Number of pages8
ISBN (Electronic)9781841706542
Publication statusPublished - Aug 2019
Event9th European Conference on Precision Livestock Farming, ECPLF 2019 - Cork, Ireland
Duration: 26 Aug 201929 Aug 2019

Publication series

NamePrecision Livestock Farming 2019 - Papers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019

Conference

Conference9th European Conference on Precision Livestock Farming, ECPLF 2019
CountryIreland
CityCork
Period26/08/1929/08/19

Fingerprint

sensors (equipment)
dairy cows
lactation
markets
feed conversion
cows
rumination
robots
collars
weighing devices
autocorrelation
milking
insemination
neck
milk yield
milk production
feed intake
calves
farms

Keywords

  • Feed efficiency
  • Precision livestock farming
  • Proxies
  • Resilience

Cite this

Ouweltjes, W., De Haas, Y., & Kamphuis, C. (2019). At-market sensor technologies to develop proxies for resilience and efficiency in dairy cows. In B. O'Brien, D. Hennessy, & L. Shalloo (Eds.), Precision Livestock Farming 2019: Papers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019 (pp. 246-253). (Precision Livestock Farming 2019 - Papers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019). Teagasc.
Ouweltjes, W. ; De Haas, Y. ; Kamphuis, C. / At-market sensor technologies to develop proxies for resilience and efficiency in dairy cows. Precision Livestock Farming 2019: Papers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019. editor / Bernadette O'Brien ; Deirdre Hennessy ; Laurence Shalloo. Teagasc, 2019. pp. 246-253 (Precision Livestock Farming 2019 - Papers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019).
@inproceedings{756550762efb411687deb075f80dea66,
title = "At-market sensor technologies to develop proxies for resilience and efficiency in dairy cows",
abstract = "We hypothesise that at-market sensor technologies can be used to develop proxies for complex traits such as resilience and feed efficiency (FE). This was tested by comparing variables describing sensor data patterns (“curve-parameters”) from resilient or FE cows with non-resilient or non-FE cows. Sensor data included data from weighing scales, activity (steps) and rumination activity from neck collars, and milk production from the parlour or the milking robot. Curve-parameters were calculated for each sensor for each lactation for which data was available and included the mean, standard deviation (std), slope, skewness, and the autocorrelation. Data originated from a Wageningen Research farm, and included data from 1,800 cows with calvings between 1995-2016. During this time frame, there were 98 lactations with sufficient feed intake recordings to compute FE at lactation level (DMI (kg) / milk yield (kg)), and to rank them accordingly. The 1,800 cows that could be ranked according to their lifetime resilience (ability to re-calf in combination with the number of health and insemination events) based on scores for each of the, in total, 5,771 lactations. Subsequently, the 20{\%} or 10{\%} most and least FE or resilient lactations, respectively, were selected. Curve-parameters of these selected lactations were compared. Results imply that using a single sensor, or a single curve parameter, is likely to be insufficient as a proxy for resilience of efficiency. Future research should focus on studying which combination of curve parameters and sensors are most informative as proxy for these two complex traits.",
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Ouweltjes, W, De Haas, Y & Kamphuis, C 2019, At-market sensor technologies to develop proxies for resilience and efficiency in dairy cows. in B O'Brien, D Hennessy & L Shalloo (eds), Precision Livestock Farming 2019: Papers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019. Precision Livestock Farming 2019 - Papers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019, Teagasc, pp. 246-253, 9th European Conference on Precision Livestock Farming, ECPLF 2019, Cork, Ireland, 26/08/19.

At-market sensor technologies to develop proxies for resilience and efficiency in dairy cows. / Ouweltjes, W.; De Haas, Y.; Kamphuis, C.

Precision Livestock Farming 2019: Papers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019. ed. / Bernadette O'Brien; Deirdre Hennessy; Laurence Shalloo. Teagasc, 2019. p. 246-253 (Precision Livestock Farming 2019 - Papers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019).

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

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AU - De Haas, Y.

AU - Kamphuis, C.

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N2 - We hypothesise that at-market sensor technologies can be used to develop proxies for complex traits such as resilience and feed efficiency (FE). This was tested by comparing variables describing sensor data patterns (“curve-parameters”) from resilient or FE cows with non-resilient or non-FE cows. Sensor data included data from weighing scales, activity (steps) and rumination activity from neck collars, and milk production from the parlour or the milking robot. Curve-parameters were calculated for each sensor for each lactation for which data was available and included the mean, standard deviation (std), slope, skewness, and the autocorrelation. Data originated from a Wageningen Research farm, and included data from 1,800 cows with calvings between 1995-2016. During this time frame, there were 98 lactations with sufficient feed intake recordings to compute FE at lactation level (DMI (kg) / milk yield (kg)), and to rank them accordingly. The 1,800 cows that could be ranked according to their lifetime resilience (ability to re-calf in combination with the number of health and insemination events) based on scores for each of the, in total, 5,771 lactations. Subsequently, the 20% or 10% most and least FE or resilient lactations, respectively, were selected. Curve-parameters of these selected lactations were compared. Results imply that using a single sensor, or a single curve parameter, is likely to be insufficient as a proxy for resilience of efficiency. Future research should focus on studying which combination of curve parameters and sensors are most informative as proxy for these two complex traits.

AB - We hypothesise that at-market sensor technologies can be used to develop proxies for complex traits such as resilience and feed efficiency (FE). This was tested by comparing variables describing sensor data patterns (“curve-parameters”) from resilient or FE cows with non-resilient or non-FE cows. Sensor data included data from weighing scales, activity (steps) and rumination activity from neck collars, and milk production from the parlour or the milking robot. Curve-parameters were calculated for each sensor for each lactation for which data was available and included the mean, standard deviation (std), slope, skewness, and the autocorrelation. Data originated from a Wageningen Research farm, and included data from 1,800 cows with calvings between 1995-2016. During this time frame, there were 98 lactations with sufficient feed intake recordings to compute FE at lactation level (DMI (kg) / milk yield (kg)), and to rank them accordingly. The 1,800 cows that could be ranked according to their lifetime resilience (ability to re-calf in combination with the number of health and insemination events) based on scores for each of the, in total, 5,771 lactations. Subsequently, the 20% or 10% most and least FE or resilient lactations, respectively, were selected. Curve-parameters of these selected lactations were compared. Results imply that using a single sensor, or a single curve parameter, is likely to be insufficient as a proxy for resilience of efficiency. Future research should focus on studying which combination of curve parameters and sensors are most informative as proxy for these two complex traits.

KW - Feed efficiency

KW - Precision livestock farming

KW - Proxies

KW - Resilience

M3 - Conference paper

T3 - Precision Livestock Farming 2019 - Papers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019

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BT - Precision Livestock Farming 2019

A2 - O'Brien, Bernadette

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A2 - Shalloo, Laurence

PB - Teagasc

ER -

Ouweltjes W, De Haas Y, Kamphuis C. At-market sensor technologies to develop proxies for resilience and efficiency in dairy cows. In O'Brien B, Hennessy D, Shalloo L, editors, Precision Livestock Farming 2019: Papers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019. Teagasc. 2019. p. 246-253. (Precision Livestock Farming 2019 - Papers Presented at the 9th European Conference on Precision Livestock Farming, ECPLF 2019).