Defining the breeding goal for a sheep breed including production and functional traits using market data
In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, long...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
A. Theodoridis [verfasserIn] A. Ragkos [verfasserIn] G. Rose [verfasserIn] D. Roustemis [verfasserIn] G. Arsenos [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Animal - Elsevier, 2021, 12(2018), 7, Seite 1508-1515 |
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| Übergeordnetes Werk: |
volume:12 ; year:2018 ; number:7 ; pages:1508-1515 |
| Links: |
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| DOI / URN: |
10.1017/S1751731117003007 |
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| Katalog-ID: |
DOAJ056464150 |
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| 520 | |a In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of −0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). Also, sub-clinical mastitis that affects a higher proportion of flocks could have a higher contribution to breeding goals. | ||
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10.1017/S1751731117003007 doi (DE-627)DOAJ056464150 (DE-599)DOAJe4b4c03cdc714595b84c8e338437e90d DE-627 ger DE-627 rakwb eng SF1-1100 A. Theodoridis verfasserin aut Defining the breeding goal for a sheep breed including production and functional traits using market data 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of −0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). Also, sub-clinical mastitis that affects a higher proportion of flocks could have a higher contribution to breeding goals. Breeding goal Chios sheep dairy ewes profit function economic values Animal culture A. Ragkos verfasserin aut G. Rose verfasserin aut D. Roustemis verfasserin aut G. Arsenos verfasserin aut In Animal Elsevier, 2021 12(2018), 7, Seite 1508-1515 (DE-627)534060382 (DE-600)2365209-3 1751732X nnns volume:12 year:2018 number:7 pages:1508-1515 https://doi.org/10.1017/S1751731117003007 kostenfrei https://doaj.org/article/e4b4c03cdc714595b84c8e338437e90d kostenfrei http://www.sciencedirect.com/science/article/pii/S1751731117003007 kostenfrei https://doaj.org/toc/1751-7311 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2088 GBV_ILN_2089 GBV_ILN_2093 GBV_ILN_2098 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2145 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2158 GBV_ILN_2190 GBV_ILN_2193 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2924 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_4753 AR 12 2018 7 1508-1515 |
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10.1017/S1751731117003007 doi (DE-627)DOAJ056464150 (DE-599)DOAJe4b4c03cdc714595b84c8e338437e90d DE-627 ger DE-627 rakwb eng SF1-1100 A. Theodoridis verfasserin aut Defining the breeding goal for a sheep breed including production and functional traits using market data 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of −0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). Also, sub-clinical mastitis that affects a higher proportion of flocks could have a higher contribution to breeding goals. Breeding goal Chios sheep dairy ewes profit function economic values Animal culture A. Ragkos verfasserin aut G. Rose verfasserin aut D. Roustemis verfasserin aut G. Arsenos verfasserin aut In Animal Elsevier, 2021 12(2018), 7, Seite 1508-1515 (DE-627)534060382 (DE-600)2365209-3 1751732X nnns volume:12 year:2018 number:7 pages:1508-1515 https://doi.org/10.1017/S1751731117003007 kostenfrei https://doaj.org/article/e4b4c03cdc714595b84c8e338437e90d kostenfrei http://www.sciencedirect.com/science/article/pii/S1751731117003007 kostenfrei https://doaj.org/toc/1751-7311 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2088 GBV_ILN_2089 GBV_ILN_2093 GBV_ILN_2098 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2145 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2158 GBV_ILN_2190 GBV_ILN_2193 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2924 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_4753 AR 12 2018 7 1508-1515 |
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10.1017/S1751731117003007 doi (DE-627)DOAJ056464150 (DE-599)DOAJe4b4c03cdc714595b84c8e338437e90d DE-627 ger DE-627 rakwb eng SF1-1100 A. Theodoridis verfasserin aut Defining the breeding goal for a sheep breed including production and functional traits using market data 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of −0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). Also, sub-clinical mastitis that affects a higher proportion of flocks could have a higher contribution to breeding goals. Breeding goal Chios sheep dairy ewes profit function economic values Animal culture A. Ragkos verfasserin aut G. Rose verfasserin aut D. Roustemis verfasserin aut G. Arsenos verfasserin aut In Animal Elsevier, 2021 12(2018), 7, Seite 1508-1515 (DE-627)534060382 (DE-600)2365209-3 1751732X nnns volume:12 year:2018 number:7 pages:1508-1515 https://doi.org/10.1017/S1751731117003007 kostenfrei https://doaj.org/article/e4b4c03cdc714595b84c8e338437e90d kostenfrei http://www.sciencedirect.com/science/article/pii/S1751731117003007 kostenfrei https://doaj.org/toc/1751-7311 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2088 GBV_ILN_2089 GBV_ILN_2093 GBV_ILN_2098 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2145 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2158 GBV_ILN_2190 GBV_ILN_2193 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2924 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_4753 AR 12 2018 7 1508-1515 |
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10.1017/S1751731117003007 doi (DE-627)DOAJ056464150 (DE-599)DOAJe4b4c03cdc714595b84c8e338437e90d DE-627 ger DE-627 rakwb eng SF1-1100 A. Theodoridis verfasserin aut Defining the breeding goal for a sheep breed including production and functional traits using market data 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of −0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). Also, sub-clinical mastitis that affects a higher proportion of flocks could have a higher contribution to breeding goals. Breeding goal Chios sheep dairy ewes profit function economic values Animal culture A. Ragkos verfasserin aut G. Rose verfasserin aut D. Roustemis verfasserin aut G. Arsenos verfasserin aut In Animal Elsevier, 2021 12(2018), 7, Seite 1508-1515 (DE-627)534060382 (DE-600)2365209-3 1751732X nnns volume:12 year:2018 number:7 pages:1508-1515 https://doi.org/10.1017/S1751731117003007 kostenfrei https://doaj.org/article/e4b4c03cdc714595b84c8e338437e90d kostenfrei http://www.sciencedirect.com/science/article/pii/S1751731117003007 kostenfrei https://doaj.org/toc/1751-7311 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2088 GBV_ILN_2089 GBV_ILN_2093 GBV_ILN_2098 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2145 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2158 GBV_ILN_2190 GBV_ILN_2193 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2924 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_4753 AR 12 2018 7 1508-1515 |
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10.1017/S1751731117003007 doi (DE-627)DOAJ056464150 (DE-599)DOAJe4b4c03cdc714595b84c8e338437e90d DE-627 ger DE-627 rakwb eng SF1-1100 A. Theodoridis verfasserin aut Defining the breeding goal for a sheep breed including production and functional traits using market data 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of −0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). Also, sub-clinical mastitis that affects a higher proportion of flocks could have a higher contribution to breeding goals. Breeding goal Chios sheep dairy ewes profit function economic values Animal culture A. Ragkos verfasserin aut G. Rose verfasserin aut D. Roustemis verfasserin aut G. Arsenos verfasserin aut In Animal Elsevier, 2021 12(2018), 7, Seite 1508-1515 (DE-627)534060382 (DE-600)2365209-3 1751732X nnns volume:12 year:2018 number:7 pages:1508-1515 https://doi.org/10.1017/S1751731117003007 kostenfrei https://doaj.org/article/e4b4c03cdc714595b84c8e338437e90d kostenfrei http://www.sciencedirect.com/science/article/pii/S1751731117003007 kostenfrei https://doaj.org/toc/1751-7311 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2088 GBV_ILN_2089 GBV_ILN_2093 GBV_ILN_2098 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2145 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2158 GBV_ILN_2190 GBV_ILN_2193 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2924 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_4753 AR 12 2018 7 1508-1515 |
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Theodoridis</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Defining the breeding goal for a sheep breed including production and functional traits using market data</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of −0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). 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A. Theodoridis |
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A. Theodoridis misc SF1-1100 misc Breeding goal misc Chios sheep misc dairy ewes misc profit function misc economic values misc Animal culture Defining the breeding goal for a sheep breed including production and functional traits using market data |
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SF1-1100 Defining the breeding goal for a sheep breed including production and functional traits using market data Breeding goal Chios sheep dairy ewes profit function economic values |
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defining the breeding goal for a sheep breed including production and functional traits using market data |
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Defining the breeding goal for a sheep breed including production and functional traits using market data |
| abstract |
In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of −0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). Also, sub-clinical mastitis that affects a higher proportion of flocks could have a higher contribution to breeding goals. |
| abstractGer |
In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of −0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). Also, sub-clinical mastitis that affects a higher proportion of flocks could have a higher contribution to breeding goals. |
| abstract_unstemmed |
In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of −0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). Also, sub-clinical mastitis that affects a higher proportion of flocks could have a higher contribution to breeding goals. |
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7 |
| title_short |
Defining the breeding goal for a sheep breed including production and functional traits using market data |
| url |
https://doi.org/10.1017/S1751731117003007 https://doaj.org/article/e4b4c03cdc714595b84c8e338437e90d http://www.sciencedirect.com/science/article/pii/S1751731117003007 https://doaj.org/toc/1751-7311 |
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| author2 |
A. Ragkos G. Rose D. Roustemis G. Arsenos |
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A. Ragkos G. Rose D. Roustemis G. Arsenos |
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SF - Animal Culture |
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| doi_str |
10.1017/S1751731117003007 |
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| up_date |
2024-07-03T21:00:32.577Z |
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1803593116633006080 |
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| score |
7.402669 |