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Replacement of fishmeal by canola protein concentrate in diets fed to rainbow trout (Oncorhynchus mykiss)

2004· article· en· W2125109550 on OpenAlexaff
D.L. Thiessen, D.D. Maenz, Rex W. Newkirk, H.L. Classen, Murray D. Drew

Bibliographic record

VenueAquaculture Nutrition · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsFish mealCanolaBiologyCorn gluten mealRainbow troutSoybean mealFood scienceDry matterMeat and bone mealAnimal scienceTroutMealFisheryFish <Actinopterygii>Ecology

Abstract

fetched live from OpenAlex

A dephytinized protein concentrate prepared from canola seed (CPC) was assessed for nutrient digestibility and performance in rainbow trout (Oncorhynchus mykiss). The apparent digestibility coefficients of CPC were: dry matter, 817 g kg−1; crude protein, 899 g kg−1; gross energy, 861 g kg−1; arginine, 945 g kg−1; lysine, 935 g kg−1; methionine, 954 g kg−1; threonine, 893 g kg−1. A 9-week performance trial assessed 7 diets. Fishmeal provided 940 g kg−1 of the protein in the control diet. Test diets consisted of CPC or water-washed CPC replacing 500 and 750 g kg−1 of fishmeal protein; and CPC plus an attractant replacing 500 and 750 g kg−1 of fishmeal protein. No significant differences in performance were observed (P > 0.05). A subsequent 9-week performance trial evaluated the effect of adding CPC into compound diets containing fishmeal/soybean meal/corn gluten meal. Five diets were prepared: fishmeal provided 670 g kg−1 of the protein in the control diet, in the remaining diets CPC was incorporated into commercial-like trout diets at 100, 200 and 300 g kg−1 replacement of fishmeal protein, the fifth diet included an attractant in the 300 g kg−1 replacement diet. No significant differences in performance were obtained (P > 0.05). These studies show that dephytinized canola protein concentrate has potential to replace substantial levels of fishmeal in diets for carnivorous fish without compromising performance.

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)0.000
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 score0.130
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.223
Teacher spread0.212 · 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

Citations127
Published2004
Admission routes1
Has abstractyes

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