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Incorporation of Whole Lupin, <i>Lupinus albus</i>, Seed Meal in Commercial Extruded Diets for Rainbow Trout, <i>Oncorhynchus mykiss:</i> Effect on Growth Performance, Nutrient Digestibility, and Muscle Fatty Acid Composition

2011· article· en· W1983545276 on OpenAlexaff
Aliro Bórquez, Adrián J. Hernández, Patricio Dantagnan, Patricio J. Saez, Edison Serrano

Bibliographic record

VenueJournal of the World Aquaculture Society · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBiologyRainbow troutFish mealFood scienceComposition (language)Polyunsaturated fatty acidMealFleshFatty acidAnimal scienceNutrientTroutBiochemistryFish <Actinopterygii>FisheryEcology

Abstract

fetched live from OpenAlex

Whole lupin seed meal was evaluated as partial replacement for fishmeal in extruded diets for rainbow trout, with particular emphasis on the effect on growth performance and apparent digestibility coefficient (ADC) of protein, lipids, carbohydrates, and energy. Effect on muscle fatty acid composition was also evaluated. All diets were formulated to be isonitrogenous and isoenergetic and to contain approximately 45% crude protein and 5.5 kcal energy g/diet. Diets were formulated to include whole lupin seed meal at 0, 10, 15, and 20%. Triplicate groups of fish weighing 65.9 ± 15.1 g on average were fed twice a day until apparent satiation during 12 wk. Growth, feed intake, hepatosomatic index, hepatic histology, proximate composition of whole body, and muscular fatty acid profile were determined. Growth and feed utilization were similar in all treatments and whole‐body composition did not vary among treatments. Polyunsaturated fatty acids of the n‐6 and n‐3 series remained constant in muscle as the amount of lupin in diets increased. Furthermore, the ADCs were similar among all diets. These results suggest that inclusion of whole lupin seed meal up to 20% in extruded diets for rainbow trout do not have any negative effect on growth, feed performance, or flesh quality.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.221
Teacher spread0.204 · 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".

Quick stats

Citations14
Published2011
Admission routes1
Has abstractyes

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