Evidence map›Paper›PMID 41390360›Full record

ArticleGenetics, selection, evolution : GSE2025

Deriving breeding goals and expected selection responses to reduce environmental impacts in rainbow trout farming.

Simon Pouil, Joël Aubin, Florence Phocas

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Article in Genetics, selection, evolution : GSE, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Simon PouilUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France. simon.pouil@inrae.fr.ORCID http://orcid.org/0000-0003-1531-0362
Joël AubinINRAE, Institut Agro, SAS, Rennes, France.ORCID http://orcid.org/0000-0003-4081-5426
Florence PhocasUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France.ORCID http://orcid.org/0000-0003-1161-3665

Funding

National Research Agency ANR-22-PEAE-0003
6 · The paper itself

Abstract

backgroundWith growing societal concerns about the sustainability of food production systems, there is increasing interest in considering not only economic gains but also environmental issues in breeding programs of farmed species. In this study, we compared expected selection responses for breeding programs aiming to minimize environmental impacts of the production of rainbow trout in France, one of the most important fish species in salmonid aquaculture. The consequences of genetic improvement based on environmental merit indices were investigated in a hypothetical rainbow trout production farm with a constant annual production of 300 tonnes of fish. The merit indices included three different traits: thermal growth coefficient (TGC), daily feed intake (DFI), and survival (SR). A cradle-to-farm-gate life cycle assessment was conducted to evaluate the environmental values of each trait, which served as weightings in breeding goals aiming at minimizing expected environmental impacts by genetic selection. We explored nine different environmental impact categories: climate change, terrestrial acidification, freshwater eutrophication, marine eutrophication, terrestrial ecotoxicology, freshwater ecotoxicology, land use, water dependence, and cumulative energy demand.

resultsSelection accuracy ranged from 0.34 to 0.43, with the lowest accuracy observed for the breeding goal targeting reduced water dependence, and the highest for those targeting reductions in eutrophication and terrestrial ecotoxicity. Annual genetic gains in reductions of environmental impacts, expressed per tonne of trout, were high for reducing eutrophication potential (- 6.80 to - 2.61%) and terrestrial ecotoxicity (- 4.14 to - 1.59%), but negligible for water use reduction (- 0.04 to - 0.01%). Genetic changes in DFI and TGC led to substantial annual gains in feed conversion ratio, from 1.7 to 4.8%. However, SR showed no improvement and often declined, highlighting the difficulty of balancing genetic gains across traits.

conclusionsWe demonstrated the benefits of using environmental values in breeding goals to minimize environmental impacts at the farm level, while maintaining high genetic gains in feed efficiency traits. Nevertheless, we also showed that selection efficiency was highly dependent of the impact category. Our results suggested that another selection strategy should be considered to avoid unfavourable consequences on SR.

Indexed as

AquacultureBreedingOncorhynchus mykissSelection, GeneticAnimalsClimate ChangeEnvironmentFrance

Identifiers

PMID41390360
PMCPMC12715902

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.