Selection indexes for residual feed intake derived from milk spectra
The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. Improving production efficiency and minimizing the environmental impact of dairy farming are 2 important goals of the dairy industry. Achieving these object...
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Veröffentlicht in: | Journal of dairy science 2024-12, Vol.107 (12), p.11164-11179 |
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creator | Toledo-Alvarado, H.O. Tempelman, R.J. Lopez-Cruz, M. VandeHaar, M.J. Santos, J.E.P. Peñagaricano, F. Khanal, P. de los Campos, G. |
description | The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes.
Improving production efficiency and minimizing the environmental impact of dairy farming are 2 important goals of the dairy industry. Achieving these objectives requires improving the feed-to-milk conversion efficiency. One way to achieve this goal is through genetic selection. However, measuring feed efficiency in commercial herds is currently not feasible. As such, we conducted a study to evaluate the genetic accuracy of various selection indexes derived from Fourier-transform mid-infrared (FTIR) spectra or milk composition. We used 7,793 weekly records on 537 genotyped cows (78,964 SNPs), with information on residual feed intake (RFI) and FTIR spectra. We fitted various types of selection indexes using the complete FTIR spectra of milk samples. The estimated heritability of RFI (± SD) was 0.12 ± 0.02. The accuracy of indirect selection using the FTIR spectra was maximized by using a principal components selection index (0.16 ± 0.07), followed by a least absolute shrinkage and selection operator-type penalized selection index (0.14 ± 0.06). We determined that an index based on milk spectral data recorded on ∼25 daughters produced a progeny average with an accuracy comparable to direct phenotypic selection for RFI. We conclude that indirect selection for RFI using FTIR spectra data can be effective for sires with progeny; however, future studies with a larger sample size are needed to validate these results. |
doi_str_mv | 10.3168/jds.2023-24425 |
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Improving production efficiency and minimizing the environmental impact of dairy farming are 2 important goals of the dairy industry. Achieving these objectives requires improving the feed-to-milk conversion efficiency. One way to achieve this goal is through genetic selection. However, measuring feed efficiency in commercial herds is currently not feasible. As such, we conducted a study to evaluate the genetic accuracy of various selection indexes derived from Fourier-transform mid-infrared (FTIR) spectra or milk composition. We used 7,793 weekly records on 537 genotyped cows (78,964 SNPs), with information on residual feed intake (RFI) and FTIR spectra. We fitted various types of selection indexes using the complete FTIR spectra of milk samples. The estimated heritability of RFI (± SD) was 0.12 ± 0.02. The accuracy of indirect selection using the FTIR spectra was maximized by using a principal components selection index (0.16 ± 0.07), followed by a least absolute shrinkage and selection operator-type penalized selection index (0.14 ± 0.06). We determined that an index based on milk spectral data recorded on ∼25 daughters produced a progeny average with an accuracy comparable to direct phenotypic selection for RFI. We conclude that indirect selection for RFI using FTIR spectra data can be effective for sires with progeny; however, future studies with a larger sample size are needed to validate these results.</description><identifier>ISSN: 0022-0302</identifier><identifier>ISSN: 1525-3198</identifier><identifier>EISSN: 1525-3198</identifier><identifier>DOI: 10.3168/jds.2023-24425</identifier><identifier>PMID: 39218062</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Animal Feed - analysis ; Animals ; Cattle ; Eating ; feed efficiency ; Female ; FTIR spectra ; Genotype ; indirect selection ; Lactation ; Milk - chemistry ; Phenotype ; Selection, Genetic ; Spectroscopy, Fourier Transform Infrared</subject><ispartof>Journal of dairy science, 2024-12, Vol.107 (12), p.11164-11179</ispartof><rights>2024 American Dairy Science Association</rights><rights>2024, The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c295t-f9df8fc8df286a70a743af4f3c882e9ed9e3de3a7da82003246c901f082db9c73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.3168/jds.2023-24425$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,864,2100,3548,27922,27923,45993</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39218062$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Toledo-Alvarado, H.O.</creatorcontrib><creatorcontrib>Tempelman, R.J.</creatorcontrib><creatorcontrib>Lopez-Cruz, M.</creatorcontrib><creatorcontrib>VandeHaar, M.J.</creatorcontrib><creatorcontrib>Santos, J.E.P.</creatorcontrib><creatorcontrib>Peñagaricano, F.</creatorcontrib><creatorcontrib>Khanal, P.</creatorcontrib><creatorcontrib>de los Campos, G.</creatorcontrib><title>Selection indexes for residual feed intake derived from milk spectra</title><title>Journal of dairy science</title><addtitle>J Dairy Sci</addtitle><description>The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes.
Improving production efficiency and minimizing the environmental impact of dairy farming are 2 important goals of the dairy industry. Achieving these objectives requires improving the feed-to-milk conversion efficiency. One way to achieve this goal is through genetic selection. However, measuring feed efficiency in commercial herds is currently not feasible. As such, we conducted a study to evaluate the genetic accuracy of various selection indexes derived from Fourier-transform mid-infrared (FTIR) spectra or milk composition. We used 7,793 weekly records on 537 genotyped cows (78,964 SNPs), with information on residual feed intake (RFI) and FTIR spectra. We fitted various types of selection indexes using the complete FTIR spectra of milk samples. The estimated heritability of RFI (± SD) was 0.12 ± 0.02. The accuracy of indirect selection using the FTIR spectra was maximized by using a principal components selection index (0.16 ± 0.07), followed by a least absolute shrinkage and selection operator-type penalized selection index (0.14 ± 0.06). We determined that an index based on milk spectral data recorded on ∼25 daughters produced a progeny average with an accuracy comparable to direct phenotypic selection for RFI. We conclude that indirect selection for RFI using FTIR spectra data can be effective for sires with progeny; however, future studies with a larger sample size are needed to validate these results.</description><subject>Animal Feed - analysis</subject><subject>Animals</subject><subject>Cattle</subject><subject>Eating</subject><subject>feed efficiency</subject><subject>Female</subject><subject>FTIR spectra</subject><subject>Genotype</subject><subject>indirect selection</subject><subject>Lactation</subject><subject>Milk - chemistry</subject><subject>Phenotype</subject><subject>Selection, Genetic</subject><subject>Spectroscopy, Fourier Transform Infrared</subject><issn>0022-0302</issn><issn>1525-3198</issn><issn>1525-3198</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>DOA</sourceid><recordid>eNp1kb1vFDEQxS1ERI5AS4m2pNljPN4Pu0SBhEiRKAK15fOMkS-758Pei8J_j5NL0lFZY7_3G_k9IT5IWCs56M9bKmsEVC12HfavxEr22LdKGv1arAAQW1CAp-JtKds6SoT-jThVBqWGAVfi6w1P7JeYdk3cEd9zaULKTeYS6eCmJjBTfVncLTfEOd7VMeQ0N3Ocbpuyr97s3omT4KbC75_OM_Hr4tvP8-_t9Y_Lq_Mv161H0y9tMBR08JoC6sGN4MZOudAF5bVGNkyGFbFyIzmNAAq7wRuQATTSxvhRnYmrI5eS29p9jrPLf21y0T5epPzburxEP7H1vZSDMRrAdN1I3abulCPhCDiEQFhZn46sfU5_DlwWO8fieZrcjtOhWAXV3feIqkrXR6nPqZTM4WW1BPvQgq0t2IcW7GML1fDxiX3YzEwv8ufYq0AfBVzTuoucbfGRd54p5ppo_U78H_sf7laUpQ</recordid><startdate>202412</startdate><enddate>202412</enddate><creator>Toledo-Alvarado, H.O.</creator><creator>Tempelman, R.J.</creator><creator>Lopez-Cruz, M.</creator><creator>VandeHaar, M.J.</creator><creator>Santos, J.E.P.</creator><creator>Peñagaricano, F.</creator><creator>Khanal, P.</creator><creator>de los Campos, G.</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>DOA</scope></search><sort><creationdate>202412</creationdate><title>Selection indexes for residual feed intake derived from milk spectra</title><author>Toledo-Alvarado, H.O. ; Tempelman, R.J. ; Lopez-Cruz, M. ; VandeHaar, M.J. ; Santos, J.E.P. ; Peñagaricano, F. ; Khanal, P. ; de los Campos, G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c295t-f9df8fc8df286a70a743af4f3c882e9ed9e3de3a7da82003246c901f082db9c73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Animal Feed - analysis</topic><topic>Animals</topic><topic>Cattle</topic><topic>Eating</topic><topic>feed efficiency</topic><topic>Female</topic><topic>FTIR spectra</topic><topic>Genotype</topic><topic>indirect selection</topic><topic>Lactation</topic><topic>Milk - chemistry</topic><topic>Phenotype</topic><topic>Selection, Genetic</topic><topic>Spectroscopy, Fourier Transform Infrared</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Toledo-Alvarado, H.O.</creatorcontrib><creatorcontrib>Tempelman, R.J.</creatorcontrib><creatorcontrib>Lopez-Cruz, M.</creatorcontrib><creatorcontrib>VandeHaar, M.J.</creatorcontrib><creatorcontrib>Santos, J.E.P.</creatorcontrib><creatorcontrib>Peñagaricano, F.</creatorcontrib><creatorcontrib>Khanal, P.</creatorcontrib><creatorcontrib>de los Campos, G.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Journal of dairy science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Toledo-Alvarado, H.O.</au><au>Tempelman, R.J.</au><au>Lopez-Cruz, M.</au><au>VandeHaar, M.J.</au><au>Santos, J.E.P.</au><au>Peñagaricano, F.</au><au>Khanal, P.</au><au>de los Campos, G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Selection indexes for residual feed intake derived from milk spectra</atitle><jtitle>Journal of dairy science</jtitle><addtitle>J Dairy Sci</addtitle><date>2024-12</date><risdate>2024</risdate><volume>107</volume><issue>12</issue><spage>11164</spage><epage>11179</epage><pages>11164-11179</pages><issn>0022-0302</issn><issn>1525-3198</issn><eissn>1525-3198</eissn><abstract>The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes.
Improving production efficiency and minimizing the environmental impact of dairy farming are 2 important goals of the dairy industry. Achieving these objectives requires improving the feed-to-milk conversion efficiency. One way to achieve this goal is through genetic selection. However, measuring feed efficiency in commercial herds is currently not feasible. As such, we conducted a study to evaluate the genetic accuracy of various selection indexes derived from Fourier-transform mid-infrared (FTIR) spectra or milk composition. We used 7,793 weekly records on 537 genotyped cows (78,964 SNPs), with information on residual feed intake (RFI) and FTIR spectra. We fitted various types of selection indexes using the complete FTIR spectra of milk samples. The estimated heritability of RFI (± SD) was 0.12 ± 0.02. The accuracy of indirect selection using the FTIR spectra was maximized by using a principal components selection index (0.16 ± 0.07), followed by a least absolute shrinkage and selection operator-type penalized selection index (0.14 ± 0.06). We determined that an index based on milk spectral data recorded on ∼25 daughters produced a progeny average with an accuracy comparable to direct phenotypic selection for RFI. We conclude that indirect selection for RFI using FTIR spectra data can be effective for sires with progeny; however, future studies with a larger sample size are needed to validate these results.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>39218062</pmid><doi>10.3168/jds.2023-24425</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Animal Feed - analysis Animals Cattle Eating feed efficiency Female FTIR spectra Genotype indirect selection Lactation Milk - chemistry Phenotype Selection, Genetic Spectroscopy, Fourier Transform Infrared |
title | Selection indexes for residual feed intake derived from milk spectra |
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