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Schmidtmann C, Thaller G, Kargo M, Hinrichs D, Ettema J. Derivation of economic values for German dairy breeds by means of a bio-economic model-with special emphasis on functional traits. J Dairy Sci 2020; 104:3144-3157. [PMID: 33358794 DOI: 10.3168/jds.2019-17635] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 10/13/2020] [Indexed: 11/19/2022]
Abstract
To assess the economic importance of breeding traits, economic values (EV) were derived for 3 German dairy cattle breeds: German Holstein (HOL), Angler (ANG), and Red and White Dual-Purpose (RDN). For that purpose, the stochastic bio-economic model SimHerd (SimHerd A/S, Viborg, Denmark) was used, which simulates the expected monetary gain in dairy herds. The EV was calculated as the alteration in average net return of the herd responding to a marginal change in the trait of interest. When deriving EV using SimHerd, economic consequences resulting from changes in the age structure of a dairy herd (i.e., structural herd effects) are considered. However, this requires the simulation of relationships between traits in the bio-economic model. To avoid double counting, the EV of a trait was corrected for effects from alterations in correlated traits using multiple regression analysis. The EV were derived for 23 traits in terms of production, conformation and workability, dairy health, calf survival, and reproduction performance. Furthermore, the relative economic importance of the breeding traits was calculated. Relative emphasis on production was between 39.9 and 44.4% in the breeds studied. Total costs per case of ketosis and metritis ranged from €167 to €196 and €173 to €182, respectively. Highest marginal EV of direct health traits were found for mastitis (€257 to €271 per case) and lameness (€270 to €310 per case). Consequently, relative emphasis on direct health traits was between 15.7 and 17.9%. The EV of reproduction performance showed largest differences among the cattle breeds. Overall relative emphasis on reproduction was 10.5% in HOL, 10.8% in ANG, and 6.5% in RDN. The relative economic importance of cow mortality ranged from 15.5 to 16.0% across the breeds. Collectively, the study showed the high economic importance of functional traits in the cattle breeds studied.
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Affiliation(s)
- C Schmidtmann
- Institute of Animal Breeding and Husbandry, Christian-Albrechts-University Kiel, 24098 Kiel, Germany.
| | - G Thaller
- Institute of Animal Breeding and Husbandry, Christian-Albrechts-University Kiel, 24098 Kiel, Germany
| | - M Kargo
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, 8830 Tjele, Denmark; SEGES, Agro Food Park 15, 8200 Aarhus N, Denmark
| | - D Hinrichs
- Department of Animal Breeding, University of Kassel, 37213 Witzenhausen, Germany
| | - J Ettema
- SEGES, Agro Food Park 15, 8200 Aarhus N, Denmark; SimHerd A/S, Agro Business Park, Niels Pedersens Alle 2, 8830 Tjele, Denmark
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Besson M, Komen H, Rose G, Vandeputte M. The genetic correlation between feed conversion ratio and growth rate affects the design of a breeding program for more sustainable fish production. Genet Sel Evol 2020; 52:5. [PMID: 32033525 PMCID: PMC7006397 DOI: 10.1186/s12711-020-0524-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 01/21/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Most fish breeding programs aim at improving growth rate and include feed conversion ratio (FCR) neither in the breeding goal nor in the selection index, although decreasing FCR is known to increase farm profit and decrease environmental impacts. This is because FCR is difficult to measure in fish that live in groups and FCR is assumed to have a favourable (negative) genetic correlation with growth, although the magnitude of this correlation is unknown. We investigated the effect of the genetic correlation between growth and FCR on the economic and environmental responses of a two-trait breeding goal (growth and FCR), compared to a single-trait breeding goal (growth only). Next, we evaluated the weights to assign to growth and FCR in a two-trait breeding goal to maximize sustainability of fish production. METHODS We used pseudo-best linear unbiased prediction (BLUP) index calculations to simulate a breeding program for sea bass. For the single-trait breeding goal, the trait in the breeding goal and in the index was thermal growth coefficient (TGC) and for the two-trait breeding goal, the traits in the breeding goal were TGC and FCR and the traits in the index were TGC and percentage of fat in the dorsal muscle (an indirect measure of FCR). We simulated responses to selection for genetic and phenotypic correlations between TGC and FCR ranging from 0 to - 0.8. Then, in the two-trait breeding goal, we calculated the economic return and the change in eutrophication when using economic values (EV) or environmental values (ENV). RESULTS When the genetic correlation between TGC and FCR was lower than - 0.45, we found major differences in economic returns and in eutrophication between single and two-trait breeding programs. At a correlation of - 0.25, the two-trait breeding goal based on EV increased economic return by 25% compared to the single-trait breeding goal, while using ENV decreased eutrophication by 1.34% per ton of fish produced after one generation of selection. CONCLUSIONS The genetic correlation between TGC and FCR affects the magnitude of economic losses due to omitting FCR in the breeding program. In addition, the genetic correlation affects the importance of choosing EV or ENV to reduce eutrophication and increase profit.
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Affiliation(s)
- Mathieu Besson
- Animal Breeding and Genomics Centre, Wageningen University, PO Box 338, 6700 AH, Wageningen, The Netherlands. .,Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
| | - Hans Komen
- Animal Breeding and Genomics Centre, Wageningen University, PO Box 338, 6700 AH, Wageningen, The Netherlands
| | - Gus Rose
- Animal Breeding and Genomics Centre, Wageningen University, PO Box 338, 6700 AH, Wageningen, The Netherlands
| | - Marc Vandeputte
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.,Ifremer, Chemin de Maguelone, 34250, Palavas-les-Flots, France
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Janssen K, Saatkamp HW, Calus MPL, Komen H. Economic optimization of full-sib test group size and genotyping effort in a breeding program for Atlantic salmon. Genet Sel Evol 2019; 51:49. [PMID: 31481013 PMCID: PMC6724325 DOI: 10.1186/s12711-019-0491-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Accepted: 08/19/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Breeding companies may want to maximize the rate of genetic gain from their breeding program within a limited budget. In salmon breeding programs, full-sibs of selection candidates are subjected to performance tests for traits that cannot be recorded on selection candidates. While marginal gains in the aggregate genotype from phenotyping and genotyping more full-sibs per candidate decrease, costs increase linearly, which suggests that there is an optimum in the allocation of the budget among these activities. Here, we studied how allocation of the fixed budget to numbers of phenotyped and genotyped test individuals in performance tests can be optimized. METHODS Gain in the aggregate genotype was a function of the numbers of full-sibs of selection candidates that were (1) phenotyped in a challenge test for sea lice resistance (2) phenotyped in a slaughter test (3) genotyped in the challenge test, and (4) genotyped in the slaughter test. Each of these activities was subject to budget constraints. Using a grid search, we optimized allocation of the budget among activities to maximize gain in the aggregate genotype. We performed sensitivity analyses on the maximum gain in the aggregate genotype and on the relative allocation of the budget among activities at the optimum. RESULTS Maximum gain in the aggregate genotype was €386/ton per generation. The response surface for gain in the aggregate genotype was rather flat around the optimum, but it curved strongly near the extremes. Maximum gain was sensitive to the size of the budget and the relative emphasis on breeding goal traits, but less sensitive to the accuracy of genomic prediction and costs of phenotyping and genotyping. The relative allocation of budget among activities at the optimum was sensitive to costs of phenotyping and genotyping and the relative emphasis on breeding goal traits, but was less sensitive to the accuracy of genomic prediction and the size of the budget. CONCLUSIONS There is an optimum allocation of budget to the numbers of full-sibs of selection candidates that are phenotyped and genotyped in performance tests that maximizes gain in the aggregate genotype. Although potential gains from optimizing group sizes and genotyping effort may be small, they come at no extra cost.
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Affiliation(s)
- Kasper Janssen
- Wageningen University & Research, Animal Breeding and Genomics, P.O. Box 338, 6708 PB Wageningen, The Netherlands
| | - Helmut W. Saatkamp
- Wageningen University & Research, Business Economics, P.O. Box 8130, 6706 KN Wageningen, The Netherlands
| | - Mario P. L. Calus
- Wageningen University & Research, Animal Breeding and Genomics, P.O. Box 338, 6708 PB Wageningen, The Netherlands
| | - Hans Komen
- Wageningen University & Research, Animal Breeding and Genomics, P.O. Box 338, 6708 PB Wageningen, The Netherlands
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Besson M, Allal F, Chatain B, Vergnet A, Clota F, Vandeputte M. Combining Individual Phenotypes of Feed Intake With Genomic Data to Improve Feed Efficiency in Sea Bass. Front Genet 2019; 10:219. [PMID: 30984235 PMCID: PMC6449465 DOI: 10.3389/fgene.2019.00219] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Accepted: 02/27/2019] [Indexed: 11/18/2022] Open
Abstract
Measuring individual feed intake of fish in farms is complex and precludes selective breeding for feed conversion ratio (FCR). Here, we estimated the individual FCR of 588 sea bass using individual rearing under restricted feeding. These fish were also phenotyped for their weight loss at fasting and muscle fat content that were possibly linked to FCR. The 588 fish were derived from a full factorial mating between parental lines divergently selected for high (F+) or low (F–) weight loss at fasting. The pedigree was known back to the great grand-parents. A subset of 400 offspring and their ancestors were genotyped for 1,110 SNPs which allowed to calculate the genomic heritability of traits. Individual FCR and growth rate in aquarium were both heritable (genomic h2 = 0.47 and 0.76, respectively) and strongly genetically correlated (−0.98) meaning that, under restricted feeding, faster growing fish were more efficient. FCR and growth rate in aquariums were also significantly better for fish with both parents from F– (1.38), worse for fish with two parents F+ (1.51) and intermediate for cross breed fish (F+/F– or F–/F+ at 1.46). Muscle fat content was positively genetically correlated to growth rate in aquarium and during fasting. Thus, selecting for higher growth rate in aquarium, lower weight loss during fasting and fatter fish could improve FCR in aquarium. Improving these traits would also improve FCR of fish in normal group rearing conditions, as we showed experimentally that groups composed of fish with good individual FCR were significantly more efficient. The FCR of groups was also better when the fish composing the groups had, on average, lower estimated breeding values for growth rate during fasting (losing less weight). Thus, improving FCR in aquarium and weight loss during fasting is promising to improve FCR of fish in groups but a selection response experiment needs to be done. Finally, we showed that the reliability of estimated breeding values was higher (from+10% up to +125%) with a genomic-based BLUP model than with a traditional pedigree-based BLUP, showing that genomic data would enhance the accuracy of the prediction of EBV of selection candidates.
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Affiliation(s)
- Mathieu Besson
- GABI, INRA, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France.,MARBEC, Univ Montpellier, CNRS, Ifremer, IRD, Palavas-les-Flots, France
| | - François Allal
- MARBEC, Univ Montpellier, CNRS, Ifremer, IRD, Palavas-les-Flots, France
| | - Béatrice Chatain
- MARBEC, Univ Montpellier, CNRS, Ifremer, IRD, Palavas-les-Flots, France
| | - Alain Vergnet
- MARBEC, Univ Montpellier, CNRS, Ifremer, IRD, Palavas-les-Flots, France
| | - Frédéric Clota
- GABI, INRA, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France.,MARBEC, Univ Montpellier, CNRS, Ifremer, IRD, Palavas-les-Flots, France
| | - Marc Vandeputte
- GABI, INRA, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France.,MARBEC, Univ Montpellier, CNRS, Ifremer, IRD, Palavas-les-Flots, France
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Janssen K, Saatkamp H, Komen H. Cost-benefit analysis of aquaculture breeding programs. Genet Sel Evol 2018; 50:2. [PMID: 29378517 PMCID: PMC5789754 DOI: 10.1186/s12711-018-0372-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Accepted: 01/08/2018] [Indexed: 11/18/2022] Open
Abstract
Background Profitability of breeding programs is a key determinant in the adoption of selective breeding, and can be evaluated using cost-benefit analysis. There are many options to design breeding programs, with or without a multiplier tier. Our objectives were to evaluate different breeding program designs for aquaculture and to optimize the number of selection candidates for these programs. Methods The baseline was based on an existing breeding program for gilthead seabream, where improvement of the nucleus had priority over improvement of the multiplier tier, which was partly replaced once every 3 years. Alternative breeding programs considered were annual multiplier tier replacement, annual multiplier tier replacement with priority on improvement of the multiplier tier, and a program without a multiplier tier. Cost-benefit analyses were performed to compare breeding programs. The outcomes were used to describe relationships between profitability and the number of selection candidates, length of the time horizon, and production output, and to estimate the optimum numbers of selection candidates. Results The baseline breeding program was profitable after 5 years and reached a net present value of 2.9 million euro in year 10. All alternative programs were more profitable up to year 17. The program without a multiplier tier was the most profitable one up to year 22, followed by the program with annual multiplier tier replacement and nucleus priority. The optimum number of selection candidates increased with the length of the time horizon and production output. Conclusions The baseline breeding program was profitable after 5 years. For a short time horizon, putting priority on improvement of the multiplier tier over the nucleus is more profitable than putting priority on nucleus improvement, and vice versa for a long time horizon. Use of a multiplier tier increases the delay between costs made for selection and resulting benefits. Thus, avoiding the use of a multiplier tier will increase the profitability of the breeding program in the short term. The optimum number of selection candidates increases with the length of the time horizon and production output. Using too many selection candidates relative to the optimum leads to less reduction in profitability than using too few selection candidates.
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Affiliation(s)
- Kasper Janssen
- Animal Breeding and Genomics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands. .,Business Economics Group, Wageningen University and Research, Hollandseweg 1, 6706 KN, Wageningen, The Netherlands.
| | - Helmut Saatkamp
- Animal Breeding and Genomics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands.,Business Economics Group, Wageningen University and Research, Hollandseweg 1, 6706 KN, Wageningen, The Netherlands
| | - Hans Komen
- Animal Breeding and Genomics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands.,Business Economics Group, Wageningen University and Research, Hollandseweg 1, 6706 KN, Wageningen, The Netherlands
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