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Record W3112435472 · doi:10.7717/peerj.10430

Effect of dietary oil from<i>Camelina sativa</i>on the growth performance, fillet fatty acid profile and gut microbiome of gilthead Sea bream (<i>Sparus aurata</i>)

2020· article· en· W3112435472 on OpenAlexaff
David Huyben, Simona Rimoldi, Chiara Ceccotti, Daniel Montero, Mónica B. Betancor, Federica Iannini, Genciana Terova

Bibliographic record

VenuePeerJ · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEicosapentaenoic acidPolyunsaturated fatty acidFood scienceBiologyFish oilCamelina sativaDocosahexaenoic acidFish mealCamelinaIngredientLinoleic acidFatty acidFisheryBiochemistryAgronomyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Background In the last two decades, research has focused on testing cheaper and sustainable alternatives to fish oil (FO), such as vegetable oils (VO), in aquafeeds. However, FO cannot be entirely replaced by VOs due to their lack of omega-3 (n-3) long-chain polyunsaturated fatty acids (LC-PUFA), particularly eicosapentaenoic (EPA; 20:5n-3) and docosahexaenoic (DHA; 22:6n-3) acids. The oilseed plant, Camelina sativa , may have a higher potential to replace FO since it can contains up to 40% of the omega-3 precursors α -linolenic acid (ALA; 18:3n-3) and linoleic acid (LA; 18:2n-6). Methods A 90-day feeding trial was conducted with 600 gilthead sea bream ( Sparus aurata ) of 32.92 ± 0.31 g mean initial weight fed three diets that replaced 20%, 40% and 60% of FO with CO and a control diet of FO. Fish were distributed into triplicate tanks per diet and with 50 fish each in a flow-through open marine system. Growth performance and fatty acid profiles of the fillet were analysed. The Illumina MiSeq platform for sequencing of 16S rRNA gene and Mothur pipeline were used to identify bacteria in the faeces, gut mucosa and diets in addition to metagenomic analysis by PICRUSt. Results and Conclusions The feed conversion rate and specific growth rate were not affected by diet, although final weight was significantly lower for fish fed the 60% CO diet. Reduced final weight was attributed to lower levels of EPA and DHA in the CO ingredient. The lipid profile of fillets were similar between the dietary groups in regards to total saturated, monounsaturated, PUFA (n-3 and n-6), and the ratio of n-3/n-6. Levels of EPA and DHA in the fillet reflected the progressive replacement of FO by CO in the diet and the EPA was significantly lower in fish fed the 60% CO diet, while ALA was increased. Alpha and beta-diversities of gut bacteria in both the faeces and mucosa were not affected by any dietary treatment, although a few indicator bacteria, such as Corynebacterium and Rhodospirillales , were associated with the 60% CO diet. However, lower abundance of lactic acid bacteria, specifically Lactobacillus , in the gut of fish fed the 60% CO diet may indicate a potential negative effect on gut microbiota. PICRUSt analysis revealed similar predictive functions of bacteria in the faeces and mucosa, although a higher abundance of Corynebacterium in the mucosa of fish fed 60% CO diet increased the KEGG pathway of fatty acid synthesis and may act to compensate for the lack of fatty acids in the diet. In summary, this study demonstrated that up to 40% of FO can be replaced with CO without negative effects on growth performance, fillet composition and gut microbiota of gilthead sea bream.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.204
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations34
Published2020
Admission routes1
Has abstractyes

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