Predicting CO2 production of lactating dairy cows from animal, dietary, and production traits using an international dataset Article Swipe
Maria Holst Kjeldsen
,
Marianne Johansen
,
Martin Riis Weisbjerg
,
Anne Louise Frydendahl Hellwing
,
A. Bannink
,
S. Colombini
,
L.A. Crompton
,
J. Dijkstra
,
Maguy Eugène
,
Abdulai Guinguina
,
A.N. Hristov
,
Pekka Huhtanen
,
Arjan Jonker
,
Michael Kreuzer
,
B. Kuhla
,
Cécile Martin
,
Peter J. Moate
,
Puchun Niu
,
Nico Peiren
,
C.K. Reynolds
,
S.R.O. Williams
,
Peter Lund
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3168/jds.2023-24414
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3168/jds.2023-24414
Automated measurements of the ratio of concentrations of methane and carbon dioxide, [CH4]:[CO2], in breath from individual animals (the so-called "sniffer technique") and estimated CO2 production can be used to estimate CH4 production, provided that CO2 production can be reliably calculated. This would allow CH4 production from individual cows to be estimated in large cohorts of cows, whereby ranking of cows according to their CH4 production might become possible and their values could be used for breeding of low CH4-emitting animals. Estimates of CO2 production are typically based on predictions of heat production, which can be calculated from body weight (BW), energy-corrected milk yield, and days of pregnancy. The objectives of the present study were to develop predictions of CO2 production directly from milk production, dietary, and animal variables, and furthermore to develop different models to be used for different scenarios, depending on available data. An international dataset with 2,244 records from individual lactating cows including CO2 production and associated traits, as dry matter intake (DMI), diet composition, BW, milk production and composition, days in milk, and days pregnant, was compiled to constitute the training dataset. Research location and experiment nested within research location were included as random intercepts. The method of CO2 production measurement (respiration chamber [RC] or GreenFeed [GF]) was confounded with research location, and therefore excluded from the model. In total, 3 models were developed based on the current training dataset: model 1 ("best model"), where all significant traits were included; model 2 ("on-farm model"), where DMI was excluded; and model 3 ("reduced on-farm model"), where both DMI and BW were excluded. Evaluation on test dat sets with either RC data (n = 103), GF data without additives (n = 478), or GF data only including observations where nitrate, 3-nitrooxypropanol (3-NOP), or a combination of nitrate and 3-NOP were fed to the cows (GF+: n = 295), showed good precision of the 3 models, illustrated by low slope bias both in absolute values (-0.22 to 0.097) and in percentage (0.049 to 4.89) of mean square error (MSE). However, the mean bias (MB) indicated systematic overprediction and underprediction of CO2 production when the models were evaluated on the GF and the RC test datasets, respectively. To address this bias, the 3 models were evaluated on a modified test dataset, where the CO2 production (g/d) was adjusted by subtracting (where measurements were obtained by RC) or adding absolute MB (where measurements were obtained by GF) from evaluation of the specific model on RC, GF, and GF+ test datasets. With this modification, the absolute values of MB and MB as percentage of MSE became negligible. In conclusion, the 3 models were precise in predicting CO2 production from lactating dairy cows.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3168/jds.2023-24414
- http://www.journalofdairyscience.org/article/S0022030224007847/pdf
- OA Status
- gold
- Cited By
- 6
- References
- 38
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4396917132
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4396917132Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3168/jds.2023-24414Digital Object Identifier
- Title
-
Predicting CO2 production of lactating dairy cows from animal, dietary, and production traits using an international datasetWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
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2024-05-15Full publication date if available
- Authors
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Maria Holst Kjeldsen, Marianne Johansen, Martin Riis Weisbjerg, Anne Louise Frydendahl Hellwing, A. Bannink, S. Colombini, L.A. Crompton, J. Dijkstra, Maguy Eugène, Abdulai Guinguina, A.N. Hristov, Pekka Huhtanen, Arjan Jonker, Michael Kreuzer, B. Kuhla, Cécile Martin, Peter J. Moate, Puchun Niu, Nico Peiren, C.K. Reynolds, S.R.O. Williams, Peter LundList of authors in order
- Landing page
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https://doi.org/10.3168/jds.2023-24414Publisher landing page
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https://www.journalofdairyscience.org/article/S0022030224007847/pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.journalofdairyscience.org/article/S0022030224007847/pdfDirect OA link when available
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Production (economics), Milk production, Lactation, Animal science, Animal production, Milk fat, Dairy cattle, Biotechnology, Biology, Food science, Pregnancy, Linseed oil, Genetics, Economics, MacroeconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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6Total citation count in OpenAlex
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2025: 5, 2024: 1Per-year citation counts (last 5 years)
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38Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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