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Record W2525920222 · doi:10.5539/ijb.v8n4p66

Effect of Beta-propeller Phytase from Pichia pastoris on Energy Partition in Juvenile Litopenaeus vannamei Fed a Plant Protein-Based Diet

2016· article· en· W2525920222 on OpenAlexvenueno aff
Jorge Gamboa, Gérard Cuzon, Martha Guerrero‐Olazarán, José María Viader-Salvadó, Gabriela Gaxiola

Bibliographic record

VenueInternational Journal of Biology · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y TecnologíaHort Innovation
KeywordsPhytasePichia pastorisLitopenaeusPhytic acidBiologyFood scienceAnimal scienceBiochemistryEnzymeShrimpRecombinant DNAGeneFishery

Abstract

fetched live from OpenAlex

The main objective of this study was to evaluate the effect of a new isolated exogenous Beta-propeller phytase (FTEII) obtained from Pichia pastoris, on growth, survival and energy partition of juveniles of Litopenaeus vannamei fed a plant protein diet. Two treatments were designed for the experiment: a plant protein-based diet without phytase (T1), and adiet comprisingpretreated plant protein with Beta-propeller phytase (T2). The gowth rate monitored over 30 days significantly improved when phytase was added to the diet (T2) compared to control T1(p<0.05), and survival rates were similar between treatments (p>0.05). Energy partitioning was affected by basal metabolism (HeE) which was similar in both dietary treatments (p> 0.05) but the heat increment of feeding (HiE) was higher with T1 than T2 (p<0.05), whereas retained energy (RE) increased in T2 compared to T1 (p<0.05). In summary, exogenous phytase added to a plant protein-based diet decreased the negative effect of phytic acid, released phosphorus, and therefore improved weight gain.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.012
GPT teacher head0.238
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2016
Admission routes1
Has abstractyes

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